In this study, an on-road driving experiment was designed to investigate the visual attention fixation and transition characteristics of drivers when they are under different cognitive workloads. First, visual attention was macroscopically analyzed through the entropy method. Second, the Markov glance one- and two-step transition probability matrices were constructed, which can study the visual transition characteristics under different conditions from a microscopic perspective. Results indicate that the fixation entropy value of male drivers is 23.08% higher than that of female drivers. Under the normal driving state, drivers’ fixation on in-vehicle systems is not continuous and usually shifts to the front and left areas quickly after such fixation. When under cognitive workload, drivers’ vision transition is concentrated only in the front and right areas. In mild cognitive workload, drivers’ sight trajectory is mainly focused on the distant front area. As the workload level increases, the transition trajectory shifts to the junction near the front and far sides. The current study finds that the difference between an on-road test and a driving simulation is that during the on-road driving process, drivers are twice as attentive to the front area than to the driving simulator. The research provides practical guidance for the improvement of traffic safety. With the improvement of vehicle automation technology, we can see human-machine co-driving or partially automated systems existing in the foreseeable future. The world’s major automobile manufacturers will continue the development of driver assistance systems, which would improve the safety and comfort of drivers and moreover, provide better protection as well. However, with the assistance of vehicle automation, drivers can feel freer to get distracted or bold to disengage from driving. Obviously, these automated systems interfere with drivers to make safe decisions during important moments and can result in misjudged safety risks . As in oDriving demand has been described as a satisfactory task ,4, whichMany advanced driver assistance systems also detect driver distractions. The AutoRate system can use the front camera of the smartphone installed on the windshield to monitor the driver’s attention . The BerAt present, driving behavior research mainly adopts various technologies to evaluate drivers’ eye movement information, such as bioelectricity , head infrared sensors, and eye trackers. Some studies have compared eye movements and dangerous reaction times between simulated driving tasks and similar but video-based passive danger perception tasks. They found that during active driving, participants scanned the road less and fixed their gaze near the front of the vehicle . When seIn summary, previous works in this domain have accomplished a series of achievements in the study of driving workload, visual attention distribution, and transition. For visual attention, previous studies have focused on the changes of eye movements on the radio inside the vehicle, billboards outside the vehicle, and in-vehicle gestures, etc. At present, studies have only looked at macroscopic cognitive distraction and there is a lack of in-depth exploration of visual attention under different degrees of cognitive distraction. Moreover, most tests have been conducted in a driving simulation environment and few have performed on-road driving experiments. In-depth studies on the characteristics of drivers’ gaze fixation and transition under cognitive workload conditions are lacking and the relationship between visual and cognitive attention has not been fully explored. In view of these research shortcomings, the participants generated three different levels of cognitive workload through the calculation of math problems of different difficulties. We designed the on-road driving experiment under a real driving environment, exploring the driver’s visual attention fixation characteristics through visual entropy theory and researching the driver’s visual transition characteristics through Markov one-step and two-step transition matrix under different cognitive workloads. The main research ideas are illustrated in Many studies have proved that subject to the constraints of experimental conditions, small samples can also be used in driver characteristic tests. Usually, the number of samples is greater than 6 to be effective ,31,32,33The test vehicle was a 2017 Sagitar 1.6T , equipped with an advanced data acquisition system to capture data related to drivers’ action and status in real time. The data acquisition system includes a laser distance sensor ; radar rangefinder ; Tobii Glasses 2 wearable eye tracker ; and BIOPAC MP160 16-channel physiological recorder . The four synchronized camera outputs include the front and rear of the vehicle, drivers’ face and in-vehicle operation video, drivers’ recorded eye movement, vehicle running characteristics, and traffic environment information for the whole process. The drivers operate in accordance with their own daily driving behaviors and habits, thereby collecting their natural driving behavior in a real environment, as shown in The drivers fix their vision on a certain area during the driving process and transfer such vision between different areas. The visual attention fixation characteristics are analyzed by recording drivers’ gaze duration. The visual attention transfer characteristics are studied by recording the horizontal and vertical coordinates of the fixation target.Participants were required to work in strict accordance with the instructions of the research staff during the test. Under normal driving circumstances, drivers perform the main driving task; that is, to control the vehicle to drive at different speed limits on different sections and carry out the prescribed operations as prompted. In this experiment, the method of listening to and performing mathematical calculations was selected. All the participants had a bachelor’s degree or above and good mathematical calculation ability. According to the difficulty level of the questions, they can be divided into three levels: simple, general, and complex. At the same time, three levels of cognitive workload are defined, namely, mild, moderate, and deep. The duration of each cognitive distracted driving test was approximately 2 min and each participant had to complete the tasks twice. During the mathematical calculation of each level, the experimenter flashed the camera and turned off the light, which is used for the calibration of the post-analysis data and keeps records about performance. The interval between the two groups depended on the drivers’ fatigue degree. See The cognitive workload task was set up to allow drivers to experience different levels of cognitive distraction during the driving process. All drivers were told to improve the calculation accuracy as much as possible before the experiment. It was found that the calculation accuracy rate of the simple tasks exceeded 90% and in general, tasks also exceeded 80%, but as for the complex tasks, this was less than 60% and for the driving safety, some participants even gave up and provided a random answer. So, the purpose of setting math problems of different difficulties is to cause different levels of cognitive distraction. This research considers the characteristics of eye movement behavior and the influence of the calculation accuracy is not considered in the actual process analysis.A road test was conducted during non-peak hours on weekdays . This paper selects the experiment with sunny weather conditions to analyze and when the temperature was suitable for driving. All the test drivers performed the actual vehicle test on the same road section to ensure that all the drivers had similar traffic conditions. Weather and other factors remained mostly consistent during the test. The test road section was selected to be at Zhongyuan Avenue in Harbin. The starting point was the intersection of Songpu Bridge and Zhongyuan Avenue and the ending point was the intersection of Zhongyuan Avenue and Xiang’an North Street. The whole journey was 10 km long and the route is depicted in (1)The experimental staff prepared the test notification. The test subject was informed of the whole process and the subject filled in the personal information form. Then, the staff placed the equipment on the test subject.(2)The staff guided the drivers into the test vehicle, switched on all the test equipment, and completed the calibration and synchronization of the equipment. Once the drivers were ready, they drove around the safety area for approximately 15 min to become accustomed to the setting.(3)The participants entered the designated test section to start driving and the staff recorded data from the start time of the test. The participants performed the prescribed operations under the guidance of the staff unless safety hazards arose. Data continued to be collected during the test to capture the driving environment and drivers’ behavior under different environments.(4)On a specific road section, the drivers performed the cognitive workload task while maintaining the main driving task. They completed the corresponding mathematical calculation according to the experimental design setting. In case hazardous situations occurred, the drivers had the option to terminate the task.(5)After the test, the staff turned off the test equipment and assisted the test subject to take off the test equipment. The participants completed the questionnaire and received the test compensation (200 RMB). The staff compiled, copied, and archived the test data.Peter et al.  divided n are given in Equation (3).The information entropy method was used to study the visual attention measure of different regions and the randomness of the drivers’ glance is reflected by the magnitude of the entropy rate, which was designed to bridge the gap between the qualitative methods currently used for evaluating vision in driving research and quantitative methods, which are actually desired . The disi is the serial number of the region .D is the number of fixation areas, D = 9; The fixation process is continuous and random and the fixation point continuously moves periodically to form their eye movement. To study the characteristics of fixation transition, considering the correlation among the current, previous, and next fixed gaze behaviors is usually necessary.i, Assume that The drivers’ visual transition characteristics are studied by constructing a Markov transition matrix. When the steady state is reached, the steady distribution of fixation can reflect the probability of each area during driving. By solving the steady distribution of the matrix, the degree of drivers’ attention to each area can be determined when the time is long enough.One-step transition is defined as the transition of a fixation point from the previous to the current fixation point or from the current fixation point to the next. The probability of this transition is called one-step transition probability. The process in which the fixation point is transferred from the previous fixation point to the next through the current fixation point is defined as a two-step transition. Its probability is called two-step transition probability. The K step transition probability matrix is represented by P(k).j tends to be stable from the initial state i. If a state probability vector The Markov chain has ergodicity. After a period, the system can reach a stable state. After a certain transition duration in the Markov process, the probability of reaching Visual entropy is the subjective measure of the human eye on image information, which can reflect the driver’s visual attention. When E = 0 and In this study, the visual entropy of the entire driving process is statistically analyzed from a macro level. After data processing and analysis, the fixation duration and probability of each region of the 10 test subjects are shown in The average fixation duration can reflect drivers’ attention in each region at the time. The samples tested for normality are shown in The fixation trajectory of drivers in mild, moderate, and deep cognitive workloads along with normal driving state is displayed in Based on previous works  and the Areas A and B belong to the left side of the current driving lane; areas D and E belong to the front of the current driving lane; and areas G and H belong to the right side of the current driving lane. These areas are divided for analysis in the statistical data. The one- and two-step transition probability matrices of drivers’ vision in each fixation area are obtained by the statistics of drivers’ vision in mild, moderate, and deep cognitive workloads and normal driving states. The one-step transition probability matrix can reflect the position change of drivers’ vision at a continuous moment, whereas the two-step transition probability matrix can reflect the looking back of drivers. Whether the line of sight returns to the same area after two shifts is observed; that is, whether a certain area needs a continuous gaze.By comparing Further comparison of Assuming that the drivers’ visual attention transfers to a sufficient number of times, a steady state is observed in which their visual attention can be analyzed. The steady distribution of fixation is shown in Equation (8). Note that X1, X2, X3, and X4 represent the steady distribution values under mild, moderate, deep cognitive workloads, and normal driving state.From the perspective of the smooth distribution value in the normal driving state, the fixation point of drivers is scattered to each fixation area, with the largest probability of occurrence in the front of the current lane, followed by the right of the current lane. In mild and moderate cognitive workloads, drivers’ fixation point can only appear in the front and right lanes of the current lane. In deep cognitive workload, drivers’ gaze can also have a small probability to focus on the left lane.FALKMER research shows that both urban roads and rural roads increase the driver’s cognitive needs, but after the driver enters the city, they pay more attention to the outside world and require a higher level of cognitive attention . Figure (1)At present, we only studied the overall accuracy of mathematical calculations under different cognitive workload conditions, but did not consider the relationship between mathematical calculation accuracy and driver’s visual attention. Future research will take calculation accuracy as an indicator to analyze the influence of different cognitive workloads on such accuracy.(2)At present, there is no analysis of the visual entropy of different cognitive levels, but only the whole process of driving. The next step will be to explore its changes under different levels of cognition.(3)Other comprehensive eye movement indicators, such as pupil diameter change and blink frequency, can be considered to analyze the visual attention of drivers under the cognitive workload condition. Dynamic AOI division will also be adopted for research.(4)More participants will be recruited to explore the visual attention characteristics of drivers under cognitive workload and we will add some driving simulation experiments for supplementary comparative analysis.(5)At present, we have generated three different degrees of cognitive workload for participants through the calculation of mathematical problems. In future work, we will quantify the indicators and give specific definitions for the three different levels.The study has certain limitations and the following problems will be solved in future research:(1)Drivers’ fixation entropy rate values for each area are calculated from the experimental data and their visual attention is measured by a quantitative method. The comparison between male and female drivers shows that the mean fixation entropy rate of males is 23.08% higher than that of female drivers.(2)Under normal circumstances of driving, drivers can cover almost the front fixation area. In the case of mild workload, drivers’ eyes are mainly focused on the distant area directly in front. As cognitive workload increases, the area where the eyes are shifted moves toward the junction between the near and far areas directly in front. The relationship between cognitive and visual occupying attention resources is also analyzed. When driving normally, visual resources are sufficient. When cognitive workload occurs, visual and cognitive resources have a competitive relationship. As the degree of cognitive workload increases, cognitive attention occupies resources more than the visual.(3)Under normal circumstances of driving, drivers’ vision can be transferred well among various areas. Under mild and moderate cognitive workloads, drivers’ eyes shift between the front and right of the current lane and the number of times the drivers’ eyes stay in the fixation area in front of the current lane decreases as workload increases.(4)Under normal circumstances of driving, in-vehicle transfer is not a continuous behavior. Eyes shift to the left and the front area very quickly. In mild and moderate workloads, the proportion of drivers’ vision transition from the right side to the front area is increased, whereas the proportion of continuous stay in the right area is significantly reduced. Therefore, under the influence of mild and moderate cognitive workloads, drivers’ eyes still shift to the right and front areas. However, the proportion of improvement decreases as workload increases. In the case of in-depth workload, no significant change is observed in the one- and two-step transition probabilities of the drivers’ vision.(5)The geometry of the road is not considered because the driver’s line of sight is on the curve or tangent of the road and the effect on dynamic vision exists. This issue will be further considered in the next work.Our findings are summarized into the following observations:


Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the network’s reliability and therefore, enabling long-distance transmissions. Although most of these efforts are made at the expense of reducing the energy consumption of the NB-IoT network, they do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy-Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only selects an appropriate channel coding scheme based on the estimated channel conditions  but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission . This results in creating a single mixed gradient based on which a higher or lower Modulating Coding Scheme (MCS) is selected on each transmission. It is aimed at enhancing the overall energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions  considerations to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes in terms of the achieved energy efficiency as well as network reliability, latency, and scalability. Low Power Area Networks (LPWANs) are a promising technology of the Internet of Things (IoT) for future wireless communications. In the recent decade, LPWANs have rapidly developed and have been catching significant attention from many researchers around the globe. The authors in  identifiNarrowband Internet of Things (NB-IoT) is a new narrowband radio technology introduced in the Third Generation Partnership Project release 13 for providing low-power wide-area IoT  presenteM is the uplink packet size in bits,B is the transmission bit rate, andIn 3GPP standardization, repeating transmission data and the associated control signaling several times has been utilized as a base solution to achieve coverage enhancement for NB-IoT . HoweverOther previous research work such as  have higK is the number of cycles or iterations involved in the synchronization process for connection to be effectively established,k,K cycles, andThis article seeks to mitigate the high energy consumption by proposing an adaptive energy-efficient channel coding approach. It is also important to note that the choice of different Modulation Coding Scheme (MCS) levels considerably influences the overall network performance of the NB-IoT system in terms of its reliability, its energy efficiency, its scalability, and latency. This is because the higher the modulation coding scheme, the higher the transmission power per modulated bit of information (lower energy efficiency) but the higher the resilience of the transmitted packet to noise and other channel impairments (more transmission reliability). The use of low MCS coupled with high transmitting power has been demonstrated to improve the transmission reliability and therefore, enhance the network coverage in terms of longer transmission distance and immunity to noise . HoweverWhile the repeating of transmission data or control signals has been selected as a promising approach to enhance coverage of NB-IoT systems according to the 3GPP rel 13 because a larger repetition number would enhance the transmission reliability, it however results in a significant spectral efficiency loss .To overcome this, this article proposes a 2-dimensional channel coding and link adaptation scheme capable of providing a trade-off between the transmit reliability and the throughput of the system by selecting a suitable MCS on one hand and an appropriate transmission repetition number on the other hand. This is proposed based on the fact that it has been identified that most existing link adaptation schemes found in the literature are solely focused on the selection of a suitable MCS value without consideration of the repetition number which as demonstrated in the paragraphs above is has demonstrated potential benefits towards addressing the energy efficiency of the NB-IoT network.In this article, key technologies in uplink scheduling and the design of an uplink link adaptation scheme for NB-IoT systems are focused on. The remainder of the article is organized as follows: First, in The stochastic energy consumption model analytically developed for the NB-IoT network at an NB-IoT node can be represented as follows. Traditionally, energy consumption in NB-IoT is often analyzed in terms of its average value . The ene(a)During a specific operational state: data processing state (active), idle mode and even sleep mode.(b)During state transition time.During the execution of its task, the processor operates in general either in the active, sleep or idle state, and dissipates different amounts of energy in each of them. Its energy dissipation can be modeled at two levels namely:Determining the energy consumption at the processor’s level is not a deterministic experiment but a stochastic one. The process depends on multiple aspects especially the randomness of the duration quantity which itself is due to the random nature of the type of physical phenomena and events for which the NB-IoT is deployed. A typical example is a scenario in which the NB-IoT nodes are deployed within a water distribution system for leakage detection as in . In suchn active, m sleep and l idle states can be modeled asPart of the major sources of uncertainty of the energy consumption of IoT networks includes the uncertainty of time duration in each of its three power modes and the uncertainty of the number of transitions between the different power modes. During its operation, the Central Processing Unit (CPU) of the NB-IoT node goes through different power mode states. The total energy consumption  power of the random change of state process. Equations  and 4)  4) are uThere are existing statistical approaches for quantitatively estimating the relationship between the state transitions of a processor and the corresponding power consumption. Some of the well-known approaches include the Performance Monitoring Counters (hardware Monitoring Counters) and the complementary approach. The latter has been proposed by  and simpConsider a processor operation process as illustrated in Given a job arrival rate The request arrivals follow a Poisson process with a mean rate of The service time is exponentially distributed with a mean of T that the network designer heuristically defines depending on the energy consumption objective of the design under consideration versus the network reliability objective.The CPU enters sleep mode if there are no more tasks to be executed for a time interval longer than an energy-aware defined threshold D which depends on the type of processor being used.The power-up processor of the processor takes a constant time In the proposed model, it is considered that the processor remains in the idle state for some time interval greater than some threshold. The processor then moves back to the sleep mode. In our proposed model, the following assumptions are madeD which then makes the probability for the processor to stay in each of the active states n. This implies that the more active states that the processor’s operational process is involved in, the longer the duration it is in the active mode. On the other hand, the duration within the idle mode is any value from a few processor’s machine cycles to a maximum threshold duration of T. The duration of the transition from the active mode to the idle mode is directly proportional to the rate of arrival of tasks The operation process of the processor cannot naturally be modelled using the Markov model. Therefore, the method of supplementary variables as proposed in  is used Considering that the NB-IoT nodes do not stay in any of the states permanently but rather move from one mode to the other, the sum of probability of staying in either mode is equal to unity (certainty). This important constraint is modelled using the following equationSeveral research works have confirmed that radio communication dominates the power consumption in NB-IoT above all other functions ,21,22. Tn possible transitions that can occur during a network operation are modeled asj to occur. The value of this frequency varies with the type of operation that the NB-IoT node is carrying out  and j. It is also very important to point out that the number of possible transitions between power modes is stochastic and can be modeled as given below. Given thatThe state in which the processor of NB-IoT nodes normally remains in is mostly the sleep mode. This is the state in which it consumes the least of energy possible with most of its internal modules and clocks disabled. However, on event-driven instants, either time events or sensing events, the processor of the NB-IoT nodes will normally wake up and go from sleep mode to active mode to perform transmission or a reception handling activity.Upon completion of the activity, it might go to another activity. If all activities are completed successfully, then it would normally go back directly to sleep mode or would momentarily go to the idle mode for a threshold amount of time and only later to sleep mode. This would mean that there would be 3 transitions on successful executions of a single activity and 4 transitions on failed execution of an activity (task) by the processor.n between modes is therefore uncertain and can be modeled as followsThe number of possible transitions k activities to be carried out by the NB-IoT processor and given Given a set of In most cases, there are nine possible state transitions from the four power mode states. These include a transition from the transmission to the idle state, and vice versa, the reception to the idle state and vice versa the transmission state to the sleep mode and vice versa; the reception state to the sleep mode and vice versa and the single transition from idle to sleep mode. Taking into account all the nine-state transitions mentioned above the energy consumption Based on the above analysis, Equation  can be rThe transmission time Data size (M): represents the size of the data being transmitted over the link. This size is variable depending on the type of message being transmitted which could be the interest message, data message, or a control message such as acknowledgment messages (ACK). This quantity is usually measured in bits.Data rate (B): This quantity represents the bit rate and is usually measured in bits per second.Considering an ideal channel condition the transmission time duration can be modelled aspacket collision which can be described as follows: In a MAC protocol that makes use of a carrier sense multiple access, after a successful carrier sense has taken place, a collision could occur if another node transmits during the vulnerable period  and the random transmission time duration can be looked at as being caused by re-transmission attempts. In a very broad sense and with some level of abstraction, a random parameter defined as The probability of successful transmission is inversely proportional to the transmission time duration because the higher . The cumulative accounting of ACK and NACK packets on previous transmissions is used to categorize the state of the channel as either bad, medium or good conditions as well as to define the probability of successful transmission The energy consumption on a single link can, therefore, be modelled asThe energy consumption in the sleep mode , and therefore, consumes burst or periodic mode. For periodic sensing mode, the NB-IoT node’s energy consumption is almost equal to the sensing energy consumption (meaning when the sensing circuit is “ON”) added with the energy consumed during the “ON” to “OFF” as well as the “OFF” to “ON” state transitions. The electronic circuitry energy consumption can, therefore, be expressed asThough it is negligible in many cases, energy is also consumed by the NB-IoT node’s electronic circuitry. In general, the NB-IoT circuit is made of sensors and signal converters such as ADCs. Most NB-IoT nodes’ circuitry operates either in Low-Power Wide-Area Network (LPWAN) technologies both in the licensed and in the unlicensed bands such as the NB-IoT, Long Range (LoRa), and many others are striving to become energy efficient over very long distances . NB-IoT In its current form, NB-IoT reuses the LTE design extensively including the numerologies, downlink orthogonal frequency-division multiple-access (OFDMA), uplink single-carrier frequency division multiple-access (SC-FDMA), channel coding, rate matching, interleaving, etc. One of the factors for this extensive reuse of the LTE channel coding is to significantly reduce the time required to develop full NB-IoT specifications . HoweverOne of the most important issues in the design of NB-IoT systems is error correction. If well designed, the channel coding technique for NB-IoT can help save a considerable amount of energy by significantly reducing the number of required retransmissions. This justifies the fact that several research studies have proposed channel coding techniques to achieve energy efficiency. In its current form, the NB-IoT uplink baseband processing can be divided into channel coding and modulation. In the case of the NB-IoT uplink, the channel coding includes Cyclic Redundancy Check (CRC) generation and attachment, turbo or convolutional coding, and rate matching. Reliability is a key performance criterion in any form of wireless communication including the NB-IoT. It is therefore crucial that any NB-IoT design ensures that end-to-end communication occurs reliably between terminals. As in most engineering designs, the effort to enhance one performance often comes with an associated cost in terms of the other. Channel coding is often used in most communication systems to ensure resilience to channel impairments and ensure reliable link transmissions. Therefore, previous research work has proposed various channel coding approaches to ensure reliability. The main identified approaches have been the traditional repetition approach and the Narrowband Link Adaptation (NBLA) approach . DespiteAutomatic Repeat Request (ARQ) ApproachesIn this category of approaches, the receiver requests re-transmission of data packets if errors are detected, using some error detection mechanisms. Authors in  proposesAn approach proposed in  considerThe authors in  propose Forward Error Correction (FEC) ApproachesRecent research ,31,32) h,32 h31,3The authors in  have proThe authors in  proposedAnother Forward Error Correction channel coding approach for Narrowband IoT as proposed in  has beenAnother unique Forward Error Correction approach which is based on algebraic-geometric theory compares the BER performance of algebraic-geometric codes and Reed-Solomon codes at different modulations schemes over additive white Gaussian noise . In thisThe authors in ,41 propoOn the other hand, authors in  propose From the survey of the literature, the following main approaches provide a summary of the approaches that have been selected based on their relevance,Two main channel coding and uplink link adaptation schemes can be found in the literature. The first one termed an MCS-dominated approach, in which the MCS level is first adjusted based on feedback signals, after which the repetition number is adjusted. The second one is the repetition-dominated approach in which the focus is first on determining the appropriate repetition number based on the predefined NB-IoT network design criteria and then focusing on selecting the MCS level using the currently determined repetition number as part of the decision criteria. Apart from these two dominating approaches, there exist other approaches in literature such as the cooperative approaches  in whichThe design of an energy-efficient channel coding scheme for NB-IoT is directly linked to the selection of an appropriate modulation coding scheme (MCS). In order to achieve long-range communication, some work on efficient NB-IoT designs found in literature ,21,45,46ectively . The reaThese types of radio receivers are often used in the most sophisticated applications such as telemetry applications for example .Encoding more energy into signal’s bits (or symbols) results in very high decoding reliability on the receiver side. Typical receiver sensitivities could, therefore, be as low as (secure) .As opposed to other LPWAN technologies such as the LTE Cat-M1, which mainly uses spread spectrum modulation techniques, most work on NB-IoT designs found in literature ,45,48, pOne of the major differences between narrowband modulation techniques and spread spectrum techniques remains that spread spectrum techniques often require greater processing gain on the receiver side to decode the received signal(below the noise floor) while no processing gain is required to decode the signal at the receiver through frequency de-spreading for the case of narrowband modulation techniques. This results in simpler and less expensive transceiver designs. Different variants of spread spectrum techniques are used by existing standard LPWAN technologies such as Chirp Spread Spectrum (CSS) and Direct Sequence Spread Spectrum (DSSS).In the repetition-dominated method, the repetition number is first adjusted based on the feedback ACK/NACKs, and then the MCS level is updated. Repetition is the key solution adopted by most NB-IoT designs to achieve enhanced coverage with low complexity. On the other hand, for one complete transmission, the repetition of the transmission is required to be applied to both data transmission and the associated control signaling transmission. Therefore, in most NB-IoT systems, before each NPUSCH transmission, the corresponding control signal data of which includes the Resource Unit (RU) number, the chosen MCS, and repetition numbers are required to be sent via the Narrowband Physical Downlink Control Channel (NPDCCH) . The seqn from 0 to 7, the process follows a normal network automatic repeat request (ARQ) as defined by the 3GPP rel. 13 in [The selection of a repetition number from the set of l. 13 in . On the T, all transmission ACK/NACKs are computed to work out an estimated value of the BLER,During the duration of a single period of Based on the obtained BLER value, the transmission repetition number is adjusted accordingly to cope with the variation in the channel’s condition and to ensure that there is less probability of failed transmission.This is a way to save on energy consumption of the NB-IoT network.The NB-IoT link Adaptation (NBLA) approach is mainly focused on an inner loop link adaptation aspect that is mainly focused on addressing the issue of rapid changes that are often observed with the transmission BLER in NB-IoT systems. The NBLA approach as proposed in  works asThe main challenge faced by the NBLA approach resides in the fact that despite its effort in estimating the channel condition based on the computed BLER value, because of the reduced (narrow) bandwidth and considerably unstable channel conditions of the NB-IoT systems, the NBLA power control strategy often fails to ensure reliable uplink transmissions. This results in significant energy wastage due to repeated unsuccessful transmissions. The development of a new and more energy efficient approach that is capable of adaptively addressing the variations of channel conditions by looking at more than one-dimensional aspect of previous BLER performance but also considering the MCS level in selecting an appropriate repetition number is highly needed. This is expected to contribute towards adequate energy management within NB-IoT systems.In the uplink scenario, the NB-IoT network normally only supports an open-link power control as stated in . The reai for serving a cell c, given that the number of repetitions of the allocated NPUSCH RUs is less than 2 can be modelled asi for serving cell c,The possible values for fined in ,c, andAccording to the authors in ,50, the Should the number of repetitions of the allocated NPUSCH RUs be higher or equal to 2, then, the In summary, it is important to note that none of the existing approaches  consider the channel conditions in the selection of the repetition number for the traditional repetition schemes as well as dynamically minimizing this value based on the improvement of the channel conditions. At the same time, the existing NBLA scheme does not dynamically vary the Modulation Coding Scheme number based on the channel conditions. This is where the contribution of this study comes in.The objective of the EEACC approach is to design an appropriate link adaptation scheme integrated with a proper selection mechanism of repetition number and MCS for the NB-IoT systems solely based on the aim of achieving greater energy efficiency, transmission distance, and high throughput while maintaining high transmission reliability.The channel coding approach proposed by the present study is a 2-dimensional (2D) link adaptation approach which translates to a dual-objective optimization problem that aims at enhancing the NB-IoT network coverage without compromising on its energy efficiency performance. The proposed adaptive channel coding technique is twofold. It is composed of an inner loop and an outer loop adaptation scheme both aimed at enhancing the energy efficiency as well as the throughput of the network. In particular, the inner loop adaptation scheme is designed based on the channel conditions to guarantee transmission reliability and consequently, enhance the data rate of the network. On the other hand, the outer loop scheme is designed based on the Modulation Coding Scheme (MCS) number and the transmission repetition number.Because the channel conditions of NB-IoT systems are known to be quite unstable  as theirnth sampling time of the lth orthogonal-frequency-division-multiplexing (OFDM) symbol can be expressed aslth OFDM symbol and the kth sub-carrier, With phase noise The purpose of the inner loop link adaptation is to guarantee the transmission BLER to the target. Accordingly, the former is referred to as outer loop link adaptation that is inclusive of MCS level selection and repetition number determination. The proposed link-adaptation method is presented as follows.T, all transmissions of both positive and negative acknowledgments (ACK and NACKs) respectively are computed to work out the average BLER for the period which is then recorded for the specific period. Specifically, the appropriate evaluation period T for LTE systems is chosen to be in the order of tens of milliseconds while hundreds of milliseconds are used for the NB-IoT systems. This selection is mainly motivated by the realistic expected traffic rate on the LTE systems being normally higher than the NB-IoT counterpart.In a single period At the end of the considered period, the obtained BLER value is passed to the outer loop and used as a parameter in the selection of the appropriate transmission repetition number as clearly labeled in the description of the algorithm as presented in Algorithm 1,If the current BLER (the one of the present period) is found to be less than On the other hand, if the BLER is found to be between Finally, if the current BLER is greater than As discussed in a previous section, the inner loop link adaptation approach is designed to handle the rapid transmission of BLER fluctuations. This proposed inner loop approach works as described below:If a certain number of ACKs are successively successfully decoded at the NB-IoT receiver, then the MCS level is increased.On the other hand, when a certain number of NACKs are successively decoded at the NB-IoT receiver, then the MCS level is decreased.The outer loop link adaptation approach consists of the MCS level selection which is performed as described below:N/A implies discontinuous transmission (DTX) which happens when the eNB does not detect any NPUSCH signal.In general, the number of ACKs is greater than that of NACKs to ensure a slow increase of the MCS level with ACK feedback and a quick decrease of the MCS level with NACK feedback. Due to the narrowband and low data rate for NB-IoT systems, the settings for LTE systems may not be applicable. Therefore, two aperiodic and event-based actions are defined for the EEACC approach namely the fast upgrade (FUG) and the emergency downgrade (EDG). In the event of FUG, the MCS is increased by one while in the event of an EDG it is decreased by one. Thus, the EEACC approach introduces a compensation factor A targeted Block Error Rate (BLER) value of lease 13 . This talease 13 .The ications .The The initial value of Various values for simulation parameters are selected within the simulation of the proposed algorithm. The choice of these parameter values is motivated each time by the objective of making the simulation process as realistic as possible. These parameter values include,The proposed algorithm can be summarized as given in Algorithm 1.T period time, against the threshold values of N is either reduced to half, progressively increased by one or doubled respectively.The inner loop part is described between lines When the Modulation Coding Scheme (MCS) value is between the two predefined threshold values N in relation to the minimum predefined value N is reduced by half or doubled accordingly.When the MCS reaches the minimum value .Let also assume that the CPU has a machine cycle equal to The duration of a single machine cycle can be computed as Load (5 cycles)Store (4 cycles)R-type (4 cycles)Branch (3 cycles)Jump (3 cycles)Going from the principle that for a multi-cycle Microprocessor without Interlocked Pipelined Stages (MIPS) which considers the following five types of instructions with their respective number of machine cycles,By using a MATLAB R2019b Instruction Classification Learner application , it was This leads to an average of Cycles per instructions (CPI) of This means that for the implementation on a typical NB-IoT node with a basic cheap microcontroller such as the PIC16F627A running a on a external crystal oscillator with a clock frequency This processing duration significantly reduces with faster modern microcontrollers. Depending on the type of applications for which the NB-IoT system is deployed as well as the cost constraints, ultra low power and faster microcontrollers such as the Silicon Laboratories EFM32 microcontrollers can be used to implement the EEACC algorithm along with full LTE protocol stacks for complex applications such as the control of unmanned aerial vehicles (UAVs) .It is also quite critical to mention that, although small, the execution latency of the proposed algorithm has been assessed to form part of the overall up-link communication. This execution duration could be assumed to be quite negligible simply because of the remarkable progress that we now observed in the processing speed of nowadays micro-controllers. With the capability to be interfaced with clock frequencies of few dozens of MHz, nowadays microcontrollers that form the processor of the NB-IoT nodes, could have sampling speed of up to 70 MHz meaning sampling times of about 14.3 ns . HoweverIn order to assess and validate the performance of the proposed EEACC approach, various simulations were carried out under the NB-IoT network conditions summarized within the set-up parameters given in Furthermore, it is important to note that that a 4:1 Multiple Input Multiple Output (MIMO) with Alamouti decoding technique as well as an eNB antenna design is considered in these simulations.As the study was carried out in the context of a Narrowband Internet of Things (NB-IoT) network deployed in an LTE cellular network, the Quadrature Phase Shift Keying (QPSK) LTE modulation scheme is considered. The eNodeBs in an LTE network is usually built to support QPSK, 16 QAM, and 64QAM modulation techniques for the Down Link direction. But considering that the end nodes (NB-IoT motes) are often computationally limited devices that are micro-controller based in many cases , the choice of the modulation scheme is often oriented towards QPSK .First, a random NB-IoT network of nodes is generated on a planar using the uniform distribution functions of MATLAB.Then, the Base Station (BS) is positioned using the geometry middle point as root to generate a tree topology by the Dijkstra’s algorithm.Better efficiency: With its ability to quickly create robust ad-hoc networks, mesh technology is proven to be a high-performance data transfer solution which happens to be the core of most NB-IoT applications (example of Wireless Sensor smart metering NB-IoT networks and many more).Easier maintainability: Built-in diagnostics and fault reporting ensure you can respond to maintenance issues quickly and ensure continuity of service.Easy installation: The network builds as the NB-IoT system is deployed. This is very important for Internet of Things networks in general because one of the major challenges of IoT network deployment is its financial remuneration aspect as it takes millions of devices to be deployed for a network to start to become profitable. It is also important to mention that, the deployment of IoT networks follows a more contagious approach as more nodes connect to the network because of the demonstrated benefits of existing nodes. Therefore, the deployment of NB-IoT networks must follow a meshnet approach so that on a new installation of a new node, it can self-configure by identifying first its neighbouring nodes for relay purposes and secondly its associated Base Station.A meshnet topology is formed as NB-IoT nodes are progressively deployed. Upon deployed, every node broadcasts a small interest message to identify its neighbours and path to the BS as guided by the Friis transmission equation. It is also important to mention that the Meshnet is the most preferred deployment approach for the NB-IoT networks ,58. ThisThe proposed EEACC MATLAB simulation methodology consists of the following steps:A typical meshnet planar deployment scenario is represented in All the simulation parameters as described in Each NB-IoT node is assumed to be running from a Each NB-IoT node is assumed initially (upon network deployment) and for most of the time, to run its microcontroller chip in the sleep mode with only its time clock and NB-IoT radio interface external interrupt active to allow for radioactivity detection for possible data reception handling.A MATLAB timer class with an instantiated object for each NB-IoT node, based on the simulation computer’s clock is used to keep track of the timing function at each node.Based on a random uniform process, each NB-IoT node is due to send a single data packet at a predefined rate . For every single transmission, every single NB-IoT node described as an object of a defined class (mote), implements the EEACC algorithm as presented in Algorithm 1 for transmission of data packets.During the running of the simulation, every node maintains a history of its parameter values in the form of a table among which its residual energy value.At the end of the predefined simulation time, all the data from the different nodes are computed and compared for each of the three algorithms .This section critically discusses and interprets the obtained results in light of the research objectives and goals of the research. It is important to note that the sequential channel estimation considered in the study as proposed in , takes iFirst, the reliability performance of the proposed approach is assessed in comparison to the traditional repetition approach as well as the NBLA approach. This assessment is performed by varying the transmission power of the different NB-IoT nodes and for the same number of transmissions, the average BLER value is computed for each of the three approaches.T where the channel conditions remain more or less the same. The increase in the transmission power for the same noise floor level translates in a higher Signal-to-Noise Ratio (SNR). This is because the increase in SNR is directly proportional to the increase in the transmission power in terms of the SNR ratio value definition which translates in additional dB offset value. It is also important to observe that while for SNR values that range from The obtained results as illustrated in Secondly, the average energy consumption of the NB-IoT network was also computed as the number of NB-IoT nodes is varied with each of the three approaches, namely the traditional repetition, the NBLA as well as the proposed EEACC approach. The obtained results are depicted in It can be observed from Additionally, the behavior of the BLER performance is considered as the number of repeated transmissions was increased. This performance evaluation was aimed at assessing the impact of increasing the transmission repetition on the transmission reliability of the NB-IoT network. Therefore, the transmission power was kept constant at N reaches the preset maximum value As seen in Finally, the average transmission delay on a link basis was also evaluated as the number of NB-IoT nodes was scaled up within a cell. This is to assess the impact of network scalability on the latency performance of the NB-IoT network for the proposed EEACC approach as mechanism to evaluate the applicability of the proposed EEACC method in real-time IoT applications where low latency performance is critical. The obtained results are shown in the following figure.As it can be noticed in A new proposed 2-D adaptive channel coding and link adaptation technique is presented in this manuscript which is relevant to reducing the energy consumption of NB-IoT systems in lights with the current massive, time-critical, and industry ultra-reliable requirements of IoT applications. Part of this work has been accomplished through extended bibliography search and reviewing on the NB-IoT channel coding and link adaptation schemes with, each time, a brief analysis of the advantages and disadvantages of each. The proposed EEACC approach is then step-by-step developed and presented. The obtained results and their discussion clearly highlights the major contributions of the proposed approach as they clearly demonstrate a much more resilience of the proposed approach to channel impairments, resulting in enhancing the network reliability performance. The proposed novel 2-D adaptive channel coding and link adaptation technique proves to minimize the overall energy consumption of the NB-IoT system and demonstrates the ability to sustain network scalability without significant increases in network latency. The observed performance of the proposed EEACC in terms of network scalability, latency, energy efficiency, and reliability metrics, in comparison with the existing traditional repetition approach as well as the NBLA approach is the key contribution of this research work. Future work plans to implement and assess the performance of the proposed EEACC algorithm on an NB-IoT embedded test-bed platform for a smart water consumption monitoring application.The proposed energy efficiency approach (EEACC) has been demonstrated to be an energy efficiency approach as compared to the traditional repetition and the NBLA approaches. Therefore, our proposed future research work consists of firstly implementing and assessing the proposed energy-efficient approach on-chip by using an application scenario such as smart water metering or environmental monitoring sensor network to further practically validate the proposed approach. Secondly, we propose to theoretically assess the solution of the problem using an optimization approach.


Immobilization of proteins on a surface plasmon resonance (SPR) transducer is a delicate procedure since loss of protein bioactivity can occur upon contact with the untreated metal surface. Solution to the problem is the use of an immobilization matrix having a complex structure. However, this is at the expense of biosensor selectivity and sensitivity. It has been shown that the matrix-assisted pulsed laser evaporation (MAPLE) method has been successfully applied for direct immobilization (without a built-in matrix) of proteins, preserving their bioactivity. So far, MAPLE deposition has not been performed on a gold surface as required for SPR biosensors. In this paper we study the impact of direct immobilization of heme proteins (hemoglobin (Hb) and myoglobin (Mb)) on their bioactivity. For the purpose, Hb and Mb were directly immobilized by MAPLE technique on a SPR transducer. The bioactivity of the ligands immobilized in the above-mentioned way was assessed by SPR registration of the molecular reactions of various Hb/Mb functional groups. By SPR we studied the reaction between the beta chain of the Hb molecule and glucose, which shows the structural integrity of the immobilized Hb. A supplementary study of films deposited by FTIR and AFM was provided. The experimental facts showed that direct immobilization of an intact molecule was achieved.  Referen2 [8H8O3  has repoTo date, Hb and Mb have been immobilized mostly onto electrochemical transducers. Electrochemical biosensors possess high selectivity and biological compatibility but the main drawback is the low voltammetric response because heme groups are deeply buried. One approach to solving the problem is using mediators—small molecular compounds that are electroactive. However, this complicates the electrode process of proteins. Another approach is using a promoter—a small molecular compound which is electroinactive. The effect is orienting proteins toward the electrodes decreasing the distance between the redox center and the electrodes, therefore enhancing the electron transfer. 2)-modified pyrolytic graphite (PG) electrode [A step towards direct electrochemistry of proteins is incorporating them into films that are modified on the electrode surface. In  Mb has blectrode . Hb was lectrode .Hb and Mb have never been used as ligands in surface plasmon resonance (SPR) sensors despite the fact that a synergistic effect of SPR sensor technology and immobilization of Hb/Mb as specific ligands can be expected. This is likely to be due to the ability of proteins to adsorb irreversibly on the untreated metal surface of the SPR chip, often causing loss of 90 or more per cent of their activity . ProteinHowever, this statement is valid for conventional methods of immobilization. The matrix-assisted pulsed laser evaporation (MAPLE) method  has beenConventional immobilization methods require advanced chip architectures since they screen the ligand and analyte from undesirable contact with the underlying metal. However, the complex immobilization matrix raises the question of the SPR sensor selectivity and sensitivity. Moreover, the elaboration of the immobilization matrix is complex, labor-intensive and expensive. Therefore, an immobilization method that avoids the built-in matrix and provides directly immobilized ligands is highly desirable.In previous publications of ours we reported that MAPLE is a very promising method in this aspect ,30. Our -Preservation of the conformation state. This alters the ability of the molecule to transmit intramolecular messages to its various functional groups, maintaining a maximum affinity for the ligand of interest. For example, oxygen binding depends on the position of the porphyrin in relation to the plane of the heme.-The effect of dehydration on Hb/Mb activity. The structure of the heme pocket is preserved by the hydrogen bonding of water molecules with the protein surface . AdditioIn this paper we focus on the impact of direct immobilization on protein bioactivity and the general sensing ability of Hb and Mb, respectively. The successful immobilization of Hb/Mb requires the solution of two problems:Immobilization by the MAPLE technique can solve these problems at different stages of the immobilization process. The solution of the aforementioned problems can be assessed by registering the bioactivity of the directly immobilized ligands. This is accomplished by SPR registration of the molecular reactions of various Hb/Mb functional groups. By SPR we studied the reaction between the beta chain of the Hb molecule and glucose which shows the structural integrity of the immobilized Hb. In addition to these studies, Fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM) and atomic force microscope (AFM) examination of the deposited film were also used. A comprehensive review ,26 of prA significant problem is the choice of a volatile solvent in which the proteins are dissolved. Having in mind the reports of results obtained in MAPLE deposition of protein ,34, we u−3 Torr). Also, the cooling rate is very important, as discussed below. The conclusions are based on the analysis of FTIR spectrum—the spectrum of the starting substance (lyophilized Hb) was chosen for comparison.We have used a frozen target consisting of 5–7% Hb/Mb solution in deionized water. To study the impact of direct immobilization on protein conformation, in the first place we considered the MAPLE parameters which determine the status of proteins remaining in the target holder after deposition, without exposure to laser irradiation. We have shown  that theMAPLE processing parameters that define the structural composition and bioactivity of the deposited molecules. The most important parameters are pulse energy, pulse repetition rate and pulse duration. Since the target absorption increases with decreasing the temperature [2, with pulses varying between 18 k and 47 k. For the Mb solution the parameters were different, as discussed in Once optimal parameters have been established, we proceeded with studying the impact of perature , higher The bioactivity of MAPLE-deposited proteins is the main criterion for the efficiency of immobilization. Immobilized molecule bioactivity was assessed by SPR registration of the binding ability of the various functional groups of metalloprotein molecules with carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO) and oxygen (O2), as reported in ,30. For Another criterion is the adhesion quality of the film deposited on the gilded grating. The quality is evaluated by the solubility of the film when sonicated in water for 30 s. If this procedure does not impact SPR, adhesion is considered to be good. Achieving good adhesion involves balancing laser energy and target-substrate distance. Simultaneously, laser energy impacts the bioactivity of deposited films. Consequently, the optimization procedure is complex, since it requires a trade-off between a number of parameters, as discussed in 2, NO, O2) required were purchased from Messer Bulgaria .Hemoglobin  and myoglobin  were purchased from Sigma-Aldrich . The pure gases and gas mixtures , and nitric oxide (NO) to the corresponding Hb/Mb functional groups were studied by SPR. 2 (1000 ppm) and Hb/Mb molecules. The details regarding SPR set-up and registration were the same as those previously reported by us [It is interesting to evaluate to what extent the observed differences in the FTIR spectra  are relaed by us ,30.The deposition of the Mb film on the SPR transducer and the film on the Si substrate, the FTIR spectrum of which is shown in The structure of the deposited films was studied by TEM. This statement is supported by SPR observed in films deposited on gilded grating. Besides, the measured resonance spectral shift originating from binding reactions in the MAPLE-deposited film was more than twice smaller than the one observed in the spin-coated film. This supported the statement that the number of bioactive molecules in a MAPLE-deposited film is lower. As a consequence, the SPR shift is not well pronounced. 2, and NO, respectively. However, these experimental facts cannot prove the integrity of the molecules deposited—the bioactivity observed could be a consequence of fragmented Hb/Mb molecules that have the above-mentioned functional groups. In ,30 we shFor the purposes of providing convincing experimental evidence of an intact molecule immobilization, we studied the interaction between Hb and glucose. Glucose covalently binds to hemoglobin through the N-end of the Hb molecule beta chain  and formA reasonable question is whether directly immobilized ligands perform better in terms of sensitivity. In our experiments we achieved 28 Da (for CO). Compared with SPR sensors based on conventionally immobilized ligands that possess low response induced by binding of smaller analytes with a molecular mass less than 1000 Da, our result is a convincing proof of the higher performance of directly immobilized ligands. Also, the low detection limit was established as follows: 30 ppm for CO and 70 ppm for NO. The comparison with previously reported results is not possible since the sensing is based on different methods and incomparable units of measurement are used ,7. The performance of directly immobilized Hb is confirmed by the achieved very sensitive glucose detection with low detection limit 0.1 mmol/L . We cannOur attention was focused of the impact of direct immobilization on Hb and Mb bioactivity. FTIR spectra, TEM and AFM techniques were used to characterize it. Although FTIR spectra indicated that deposited films did not entirely preserve the proteins’ chemical structure, they possessed suitable bioactivity for sensor applications. So far, this bioactivity is smaller than the activity of films immobilized by spin-coating, hence the immobilization process parameters need to be further improved so that ligand molecule fragmentation could be avoided. By studying the specific binding reaction via SPR, the bioactivity of directly immobilized ligands was confirmed. To the best of our knowledge, this was the first time Hb was used to detect glucose. Glucose binding to Hb suggested that intact molecule immobilization was achieved. Since the first years of development of the SPR technology, it has been generally accepted that high sensitivity and selectivity of detection cannot be achieved through direct immobilization. This is likely due to the chemical/biological immobilization methods that have been used. We showed that the MAPLE technique provides unique opportunities for direct immobilization not only due to its ability to preserve the bioactivity of the immobilized molecules but also because it provides good adhesion between the deposited molecules and the substrate. The feasibility of directly immobilized Hb and Mb was demonstrated by achieving ultra-sensitive detection of glucose and the SPR sensing of light molecules as CO and NO.


Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations. Vehicle position tracking studies are crucial for accurately estimating distances. Position tracking is used in autonomous vehicle research when solving situations using detection alone is difficult. These types of studies use lidar sensors and radar cameras for detection and recognition. Cameras are useful for object recognition, but there are times when measuring distances robustly is difficult; recent sensor fusion studies attempting robust distance measurements have been undertaken ,2. MethoCamera sensors have difficulties recognizing objects and estimating positions at night, and sensor fusion compensates for these problems by reducing measurement distance errors to improve detection ,8,9. PrePrevious sensor fusion studies using lidar and radar do not reflect the relationship between sensor characteristics and distance ,19. SensIn this study, a reliability function was designed to reflect the distance characteristics using lidar and radar by analyzing the errors between the sensors according to distance. An extended Kalman filter (EKF) was designed, which confirmed that using the reliability function improved the accuracy of distance estimation.A lidar sensor displays the reflected object as dots when it hits the object with a laser, and the points measured by the laser produce an unstructured point cloud. Detection through deep learning includes Voxel, MV3D, and Vote3Deep ,25,26,27Obstructions are included in the object detection in frustum images. However, a study using an unsupervised learning method, clustering, provided a solution to these problems . We usedEven if the background and obstacles are completely removed, accurately measuring the distance from the detected region of interest (ROI) must be considered. This distance was measured by removing the obstacle from the detected vehicle area and averaging the values at the ROI’s center. However, as the target vehicle moved further away, the measured value produced an error. The lidar data are dependent on various factors, such as the measurement distance and the slope angle of the scanned object ,31. A chIf the target vehicle is close to the sensor or at a high-channel lidar, a relatively accurate value can be obtained by averaging and measuring the detected ROI. However, vehicles far from low-channel lidars have fewer beams reflected, and measuring the distance with a lidar beam in a small area was necessary. This distance was measured by averaging the lidar data measured with the point cloud of the detected ROI. A radar sensor is not dependent on the time of day and can measure distances more robustly than cameras. Thus, the distance was measured using a camera sensor combined with radar, which is affected by the frequency used or the target object’s speed ,33. A raThe radar confirmed that the lower part of the vehicle was measured from a close distance . Some caThe measurement errors of the lidar and radar sensors were calculated and summarized according to distance . DistancThe system structure was divided into detection and tracking processes . In the t. Lidar detection was performed using convolutional neural networks (CNNs) based on polar view [t. The result of the integration of camera and radar sensors is expressed using the formula lar view . The detRecent studies have shown the possibility of obtaining a vehicle’s heading using a 3D bounding box ,36. Howetion (1) .(1)ΔxliThe extended Kalman filter was used to estimate the position and speed of the target vehicle.The state variable of the Kalman filter is the The process model of the state vector is expressed as Equation (4).Equation (4) is nonlinear, and was linearized by obtaining the Jacobian matrix in Equation (5).Next, For the lidar sensor, the closer the vehicle was to the front, the more reliable the measured value became, while the opposite was true for the radar sensor. In Equation (6), The position estimation of the vehicle using the Kalman filter predicted the next state using the value measured by the sensor. Numerous factors caused differences between the predicted position and the actual position, such as erroneous measurements. As explained earlier, this study focused on minimizing distance errors by designing a reliability function to reflect the distance characteristics of the sensors in the Kalman filter. In the longitudinal direction, the reliability of the lidar and radar sensors’ values was measured based on distance .The sigmoid function was used to implement the reliability function with Equation (6) by differentiating the matrix, The differential sigmoid function had the same distribution as the Gaussian function, which reflected the measurement vector’s errors. Meanwhile, the reliability function was expressed as Equation (8). In general, a Kalman filter analyzes the errors of each sensor and reflects measurement noise using a Gaussian function. Measurement noise should analyze and identify as many errors as possible, but this is not easily performed. A direct substitution into the measurement transformation matrix aimed to reflect this error.As shown in The state vector Next, the error covariance In Equation (11), For Equation (12), In Equation (13), updates of the error covariance were obtained using the updated Kalman gain.Tracking management  was desit were used as the inputs. When the detected vehicle was called The detection results of the lidar and radar obtained at the time The detection result used as input calculated the similarity to the The similarity was calculated using two matching pieces of information (Equation (16)), and the similarity calculation used Euclidean distance.Data association used a Hungarian algorithm, frequently used for allocation problems where cost must be lower than the threshold to allocate . For exaThe fuzzy algorithm sets fuzzy rules and membership functions that represent various situations. This study used sensor fusion while considering distance characteristics. Fuzzy rules were based on this idea and are shown in When the target vehicle was close, the lidar measurement was more reliable than radar; at greater distances, radar was more reliable than lidar. This relationship served as the basis of the fuzzy rules. The output Object tracking was performed using an experimental vehicle that compared the sensor fusion of the camera and radar and the fusion of the camera lidar sensor. The distance between the camera and the radar was calibrated by using the coordinates of the pillars in the image to obtain a matrix that converted the value of the image pixel into a radar distance coordinate system . The camThe measurements used a thin object to maintain the accuracy of the camera and radar’s projection transformation matrix. For these thin objects, the matrix was computed using the image’s x and y ground coordinates, and the radar detection results were projected onto the image coordinate system using the calculated matrix .The perspective transformation matrix allowed the measurement of distances by comparing the results detected in the image with the radar detection results, which were also obtained using the above method. The result of the radar camera sensor fusion and lidar camera sensor fusion was expressed as Equation (18), and the algorithm used in the experiment was a Kalman filter. Said equation is equal to Equation (18).The data used in the study were obtained using the experimental vehicle. A total of 17 data scenarios were generated by combining left and right turns and approaching or moving away from the ego vehicle. GT was determined manually by viewing the lidar data, and the distance accuracy was evaluated by calculating the GT and the root-mean-squared error (RMSE) of the tracking results. As testing multiple vehicles in real-world environments was difficult, experiments were conducted using simulations. The data were generated using a Prescan simulator with multiple vehicles in three different scenarios . Sensor The first scenario showed several vehicles changing lanes; the proposed method was similar to GT . The mulThe next scenario illustrated a vehicle passing an intersection. In this case, the vehicle’s lateral movement was tracked. The final scenario showed the vehicle moving closer to and further away from a curve. As it moved closer, then further away, the data obtained by the sensors were inaccurate. When the vehicle moved away from or close to the ego vehicle, the values measured by the lidar or radar sensors were imprecise. In this scenario, the simulation data were generated, and the experimental results showed that the proposed method was more precise than the sensor fusion using fuzzy results. The results of the experiment are summarized in The above results confirmed that the distance estimation along the x-axis was more accurate. Although the simulation and actual vehicle test results were similar, the y-axis method was correct, but the performance only showed a small improvement.In this study, a fused sensor combined the characteristics of lidar and radar sensors according to distance. A point cloud, measured with lidar, provided a top-view image that removed ground and obstacle points before being converted into a frustum image. Meanwhile, the radar was fused with the camera for detection and distance measurement. The lidar obtained accurate measurements when objects were close to it, and the radar sensor was accurate when measuring distant objects. An extended Kalman filter was constructed to reflect the characteristics of each sensor while obtaining measurements. A combination of the two sensors was created using a Kalman filter, which was designed as an extended filter that reflected distance characteristics by adding a reliability function. The experiment utilized an actual vehicle to evaluate the method’s performance. While estimating the distance by identifying the characteristics of the sensor, the system noise of the Kalman filter was compared with a fuzzy method or the proposed method. The study confirmed that the accuracy of distance measurements was improved as a result of the lidar and radar sensor fusion, and the method that reflected distance errors was more accurate in the extended Kalman filter’s composition.


Promoting both a healthy diet and at the same time considering the environmental sustainability aspects of production and consumption of the diet are urgent global issues. We developed the WISH  to evaluate diets for healthiness and sustainability. The WISH seeks to measure two complex multidimensional concepts, diet quality and environmental sustainability, in one scoring system. The WISH is based on the EAT-Lancet recommendations for a healthy and sustainable diet in the general population with global applicability across multiple settings. Thirteen food groups are scored between 0 and 10, based on their association with disease and impact on environmental indicators. The scoring system was applied using a dataset of duplicate 24 h dietary recalls from 396 urban Vietnamese men and women. Out of a maximum score of 130, the mean total WISH score was 46 (SD 11), and scores for the healthy and high-environmental impact sub-scores were mean 25 (11) (out of 100) and mean 26 (8) (out of 70) respectively. A higher score was observed for the less-healthy (mean 20 (2) out of 30) sub-score. Our initial analysis shows that the WISH is able to differentiate between the healthiness and the environmental sustainability of a Vietnamese diet. Current food systems are being increasingly challenged to provide healthy food for all, while doing so in a sustainable and equitable way. Worldwide, diets of poor quality are the main contributors to morbidity and mortality as well as all forms of malnutrition ,2,3, excAdding considerations beyond health creates a complex problem. There is growing pressure for agricultural production to intensify to meet rising global demands for animal source foods, fish, fruits and vegetables, as well as cereals and legumes. Food is being transported farther from where it is grown to where it is eaten, creating mixed consequences for diets : increasCharacteristics of diets with low environmental impact are broadly similar to those of a healthy diet across multiple settings ,15. AnimTo assess whether a population consumes a healthy diet, numerous diet quality indices are available, though the majority of these are developed for a specific country or region and such indices are often designed for use in high-income countries/regions . The outThe challenge is to find an optimum balance where a healthy diet goes hand in hand with a sustainable diet, without compromising too much on the quality of the diet on the one hand, or the sustainability of the food system that delivers the diet on the other. This paper describes the development of the WISH , an index that is based on globally applicable recommendations for a healthy diet for the general healthy adult population within environmental sustainability targets. Optimal levels of intake of different food groups to promote health are formulated by WHO  or the gThe WISH aims to score the healthiness and the environmental impact of the diet in one scoring system. Scoring of the WISH does not require food composition table (FCT) or life-cycle assessment data (LCA) as these are not available for all countries or regions. The WISH is designed to monitor the healthiness and environmental sustainability of the diet of a population at a certain timepoint and can also be used to monitor changes over time and allows for comparison amongst different population groups in different countries or regions.The individual components of the WISH are based on the set of recommendations for food groups from the EAT-Lancet report . The EATEnvironmental impact is based on the findings of Clark et al.  and inclAll 13 components are scored between 0 and 10, where 0 indicates no adherence to our set of reference recommendations and 10 indicates complete adherence. Higher scores on the individual components and the total and sub-scores indicate a healthier, environmentally friendlier diet. Scores are assigned within the range of 0 to 10 assuming a linear relationship between the component and the health outcomes .For all the protective food groups, a certain amount of the food group needs to be consumed before the full health benefits are observed. Assuming a linear relationship between the component and the health outcomes, for a consumption between the lower recommended intake and the recommended intake, a score between 0 and 10 is assigned according to the following formula:For the food groups, whole grains, fruits, vegetables and legumes, no restrictions at the upper ranges are modeled. Consuming the recommended, upper or an intake above the upper recommended intake level results in the maximum score of 10.For the food group unsaturated oils consumption between the recommended intake level and the upper recommended intake level is scored as 10. However, as a higher intake increases the energy consumption and could thus contribute to overweight and obesity, the score is capped at the upper recommended intake. This means that an intake above the upper recommended intake is scored as 0.For the protective food groups nuts, dairy foods and fish intakes between the recommended intake and the upper recommended intake are scored as 10. However, as these food groups pose a medium or high impact on the environment, intakes above the upper recommended intake are assigned a score of 0 given the impact on the environment.For red meat, saturated oils and added sugars consumption should not exceed the recommended amount, as negative health effects increase from that intake level onwards. For the two neutral healthy groups  a medium environmental impact is observed, with higher intakes consequently increasing the burden on the environment. Therefore, an intake between the lower recommended intake  and the recommended intake by EAT-Lancet is scored as 10. An intake between the recommended amount and the upper recommended intake is scored between 10 and 0 assuming a linear relationship and an intake exceeding the upper recommended intake is scored as 0. The score for the intake between the recommended intake and the upper recommended intake is calculated according to the formula below:For saturated oils and added sugars, no upper range of intake level is given by the EAT-Lancet recommendations. Both components are scored as a bi-variate component (so a score of either 0 or 10 is obtained). A consumption between 0 and the recommended intake was scored as 10 and intakes above this recommended level are scored as 0 points.For the calculation of the total WISH score, all components are summed up and are given equal weight in the total score. However, when summing up everything in one score a diluting effect is expected . ConsumiHealthy sub-score: Summing the 8 protective and 2 neutral food groups: whole grains, vegetables, fruits, dairy, fish, eggs, chicken and other poultry, legumes, nuts and unsaturated oils. A higher sub-score for protective foods means a higher adherence to the recommendations for these protective foods and thus a healthier diet.Less healthy sub-score: Summing the 3 limiting food groups: red meat, saturated oils and added sugars. A higher sub-score for limiting foods means a higher adherence to the recommendations for these limiting foods and thus a healthier diet.Low environmental impact sub-score: Summing the 6 low environmental impact food groups: whole grains, vegetables, fruits, legumes, unsaturated oils, and added sugars. A higher sub-score for low environmental impact foods means a higher adherence to the recommendations for these low environmental impact foods and thus a relatively low impact on the environment. A low sub-score means primarily that consumption is below recommended amounts for the components , since more of these foods could be consumed as part of a healthy diet, with relatively limited impacts on the environment. However, for the unsaturated oils and added sugars food groups consumption should not exceed the recommendations due to possible health constrains.High environmental impact sub-score: Summing the 4 medium and 3 high environmental impact food groups: saturated oils, dairy foods, red meat, fish, eggs, chicken and other poultry and nuts. A higher sub-score for high environmental impact foods means a higher adherence to the recommendations for these high environmental impact foods and thus a relatively low impact on the environment. A lower sub-score would mean consumption beyond recommended amounts and so greater negative impacts on the environment.Below is a detailed description of the 13 food groups that are included in the WISH with reference to their association with health, their impact on the environment, a listing of the food items in each group, and description of their scoring. No information from an FCT is needed for the scoring of the different components.This is a protective food group with relatively low impact on the environment . Health This is a protective food group with relatively low impact on the environment. No distinction between different types of vegetables  was included here as it is not clear to the authors how the EAT-Lancet arrived at the amounts for the different vegetable groups. Health benefits of vegetable consumption are seen for mortality, cancer and CVD . EnvironThis is a protective food group with relatively low impact on the environment. The EAT-Lancet commission does not make a distinction in different fruits such as vitamin A rich or citrus fruits. Health benefits of fruit consumption are seen for mortality, cancer and CVD  and enviThis is a protective food group with medium impact on the environment. Health benefits of dairy consumption are observed on cancer occurrence  with medThis food group is considered a limiting food group with relatively high impact on the environment. No distinction between red meat from ruminants or non-ruminants is made in the EAT-Lancet classification. Red meat is associated with negative health impacts on mortality, cancer, type 2 diabetes and CVD . FurtherThis is a protective food group with relatively high impact on the environment. Fish consumption is associated with health benefits for CVD and total mortality . Fish haThis is a neutral food group with medium impact on the environment. Egg consumption is not specifically linked to either beneficial or detrimental health effects for the adult population . SustainThis is a neutral food group with medium impact on the environment. Chicken and poultry consumption is not specifically linked to either beneficial or detrimental health effects , whereasThis is a protective food group with relatively low impact on the environment. Legumes have been associated with health benefits for CVD and mortality  whereas This is a protective food group with intermediate impact on the environment. Health associations between nuts and type II diabetes and mortality have been observed . The envThis is, within the indicated range, a protective food group with relatively low impact on the environment. Positive health impacts of unsaturated oils are observed for mortality and CVD , and envThis is a limiting food group with relatively high impact on the environment, and scored as a bi-variate component (so a score of either 0 or 10 is obtained). Health impact for saturated oils intake are seen for CVD  and the This is a limiting food group with relatively low impact on the environment, and scored as a bi-variate component (so a score of either 0 or 10 is obtained). Negative health impact of the consumption of sugars is seen for type II diabetes and CVD , whereasThe above described WISH was applied using dietary intake data from a Vietnamese population. In this population the total WISH score as well as sub-scores and individual component scores were calculated.https://anh-academy.org/increasing-fruit-and-vegetable-intake-low-income-populations-vietnam-and-nigeria-through-food). The target population was composed of males and non-pregnant females, 18–49 years old from low-income households, 200 from a peri-urban and 200 from an urban area of Hanoi in Vietnam. Data were collected between March and April 2019. Low income was defined as a monthly household income below 2.65 million Vietnamese Dong (VND), per capita within the household. This income criterion was used to create a list of eligible households by the responsible government bodies resulting in 458 and 639 eligible households for the urban and peri-urban area respectively. Households were selected randomly in each area from this household list. All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Hanoi Medical University ethical committee .The dataset on dietary intake collected in the framework of the BMGF/FCDO funded project on Fruits and Vegetable Intakes in Vietnam and Nigeria was used (Dietary intake of adults (both women and men from the same household) was assessed by using a multi-pass quantitative 24 h recall (24hR) method. Duplicate, non-consecutive 24hRs were conducted for all, carried out with a difference of at least two days between the recalls.Conversion factors for the cooking method, waste factors, total volume cooked, and portion consumed were used to calculate the amount of food item consumed in grams. The individual food items were grouped into the WISH food groups based on the description given by the EAT-Lancet commission ,22. The n = 396).Analysis was performed using R version 3.6.1. All food intakes were averaged over the two collection days before being used to score individual dietary intakes. To provide insights into the relation amongst the components and to determine which components have the highest influence on the total and sub-scores of the WISH, Spearman’s correlations were calculated where all food groups were included in the total score and correlated to the individual scores. Only dietary intake data of persons with two 24-h dietary recalls were maintained  out of 130 . This poThis article describes the development process of the WISH and its application using dietary intake data from a Vietnamese population. Based on the WISH, the diet of this Vietnamese population can be characterized as having an insufficient intake of healthy foods and intake of foods with a high environmental impact could also be reduced. WISH scoring of this population could be improved by increased intake of whole grains, vegetables and fruits. The consumption of dairy foods and nuts can be slightly increased, but with moderation to stay within the bandwidth of EAT-Lancet recommendations. Chicken and poultry and egg consumption should be decreased for the consumers, though the non-consumers could still increase their intake but with moderation. Red meat and fish consumption should be lowered and one could think of substituting this with dairy, chicken and poultry, eggs and nuts. The limiting food groups added sugars and saturated oil consumption are within the recommended range, and consumption levels for these food groups should be maintained or reduced.Overall, it can be concluded that a major dietary shift is needed in this Vietnamese population to meet the EAT-Lancet recommendations. However, our study population are low income groups living in Hanoi, so the results cannot be generalized to the entire Vietnamese population. It should also be noted that the relatively low WISH sub-component scores could be due to the fact that the participants were selected from low-income households. Vietnam, being a middle-income country, has seen a steep increase in ASF consumption in the past 35 years . Though,The EAT-Lancet recommendations recognize that major dietary changes are needed to address the negative influence of the diet on health and environmental sustainability. Another approach, which is used for many national food based dietary guidelines (FBDG) often take into account the current dietary pattern and recognize that even small deviations towards a healthy dietary pattern can lead to positive health outcomes ,29. It iFollowing a dietary pattern as recommended by the EAT-Lancet commission was shown to minimize the impact on the environment compared to currently consumed diets in many countries . UnderlyThe WISH is developed taking into account ease of use while at the same time trying to combine two dimensions, the healthiness and environmental impact of the diet, in one scoring system. These two concepts are modeled in one scoring system using cut-off points, based on recommendations of the EAT-Lancet commission for the 13 food groups. This scoring system was adopted, as the EAT-Lancet commission considered environmental factors and health factors when setting the recommended consumption amounts for the food groups. Previous scores measuring the healthiness and environmental sustainability of the diet use a scoring for the healthiness of the diet  and a scoring for the environmental impact (using LCA data) of the diet and combine this in one overall score ,20. AnotFor the calculation of the WISH, consumption amounts in grams for the 13 EAT-Lancet food groups are needed. Dietary data obtained from 24 h recalls, (weighed) food records or from a food frequency questionnaire, which includes the relevant food groups and questions on amounts consumed, can be used for this purpose. These dietary intake assessment methods are more intensive to collect and analyse compared to data needed for a basic dietary diversity score, such as Minimum Dietary Diversity-Women (MDD-W), for which only the consumption (not the quantity consumed) of a food group is needed .Some points to keep in mind during further evaluation and adjustments of the WISH related to local applicability, environmental sustainability, healthiness and costs of the diet are discussed below. Generally, the EAT-Lancet recommendations are based on global averages, and therefore not adapted to the local context. Local adaptations, based on cultural dietary practices, could therefore be a necessity. One could, in this case, think of adapting the recommendations for the protein source foods to the local context. Regarding environmental sustainability one could consider sub-groups of the red meat component in ruminant and non-ruminant categories. Emissions from ruminants  are generally greater than from non-ruminant species (such as pork)  and takiCosts of the diet are not considered in the WISH scoring, however, an environmentally sustainable and healthy diet should also be an affordable diet. It is shown that the EAT-Lancet diet is not affordable for poor households ,36. FurtEvaluation of the feasibility of modeling the environmental impact and healthiness of the diet in one scoring system should be tested with additional datasets. This could lead to refinements in components scoring and food group classifications for health and environmental impact. Evidence on healthy and sustainable diets is growing, different foods, cut-off points for the recommendations or level of impact on the environment for the different food groups for different regions in the world and food, especially production, systems might be desired . FurtherThe WISH aims to measure the healthiness and environmental sustainability of the diet with potential application in various global contexts. The recommendations used for the construction of the WISH are the only set developed for global promotion of a planet-friendly and healthy diet. A single globally applicable sustainable diet quality index allows for comparing healthiness and environmental sustainability of the diet across various countries, which is often an important prerequisite of such a metric in food system research. Our initial analysis shows that the WISH is able to differentiate between the healthiness and the environmental sustainability of the diet in Vietnam. Further evaluation of the index should be done across countries using indicators of diet quality and environmental sustainability. Additionally, assessing whether the WISH can reflect changes over time would be an interesting evaluation exercise.