We present in this paper the most important design considerations and optimizations of all elements of a low-cost WSN platform prototype for long-term, low-maintenance pervasive wildfire monitoring, its preparation for a nearly three-month field test, the analysis of the causes of failure during the test and the lessons learned for platform improvement. The main components of the total cost of the platform  are carefully analyzed and optimized for this application. The gateways are designed to operate with resources that are generally used for sensor nodes, while the requirements and cost of the sensor nodes are significantly lower. We define and test in simulation and in the field experiment a simple, but effective communication protocol for this application. It helps to lower the cost of the nodes and field deployment procedure, while extending the theoretical lifetime of the sensor nodes to over 16 years on a single 1 Ah lithium battery.Long-term wildfire monitoring using distributed  They are capable of autonomously monitoring, processing and transmitting various parameters at diverse locations for extended periods of time, using very limited energy and often without any maintenance in their lifetime.More than a decade after the WSN vision, the application domain experts expect the technology to solve application demands inexpensively and with low effort. However, the multidisciplinary challenges raised by WSN optimization to multiple application needs have been constantly acknowledged over the past decade, especially for outdoor applications –5. Most As for most maturing technologies, WSNs reached the stage where standards consolidate most existing achievements. IEEE 802.15.4 and 6LoWPAN set the groundwork for applications with IPv6 support. Software-defined radio efforts build on these, aiming at more robust and versatile communication architectures through antenna-, frequency-, modulation- and data-rate diversity, on which services for diverse application spaces can be built.At the same time, environmental monitoring has constantly grown in importance. Routinely collected data about the state and the evolution of the environment can help to detect and alert of hazardous events and to assess and optimize the long-term sustainability of, e.g., population growth, urban sprawl, invasive species, climate change and habitat destruction.Nevertheless, the outdoor monitoring application domain is often challenging . The quaWSN platforms typically rely on existing hardware and software components to support a broad range of applications, often using some cross-layer optimizations. However, applications with stringent requirements, such as low cost, a large number of nodes, long service time, fast field deployment and reduced maintenance, can motivate custom design and optimization of the entire WSN platform.in situ distributed temperature sensors. Early detection of forest wildfires is very important for fire fighting success and to effectively limit damage and cost. We comparatively analyze existing detection and alert solutions and define the design objectives of a WSN platform that can overcome most of their weaknesses. Then, we present the main design phases, the effort spent, the major pitfalls building the first prototype and the lessons learned from its field test. We also show how the resulting WSN platform can support a large class of environmental monitoring applications, increasing its value and reducing its return on investment.In this paper, we focus on the needs of a demanding application, pervasive wildfire monitoring using Platform specifications were defined in collaboration with an industrial beneficiary and respond to pragmatic and stringent requirements for pervasive wildfire detection and alerting. For this purpose, the company consulted several actors in areas subject to wildfires, such as firefighters, state forestry corps, civil protection and forest rangers.(1)A methodical holistic analysis of the effects of the application requirements and of the available design options for the platform hardware, software, communication protocols and field deployment procedures on the overall platform performance, the cost and the reliability of its nodes, of the platform commissioning and exploitation. This method can be applied for the analysis of other WSN platforms in the context of different application requirements.(2)Design criteria, optimization and field validation of cost-effective sensor nodes and gateways that use much lower resources and energy than the typical nodes in the literature based on off-the-shelf components.(3)Analysis, definition and field test of a cost-effective and reliable field deployment procedure for the network nodes that minimizes human-introduced errors.(4)Design, optimization and field test of a simple, yet effective field communication protocol that matches application requirements well, significantly contributes to the reduction of node energy consumption and cost and supports an effective field deployment procedure for the nodes. It can also scale up to support networks with a very large number of nodes.(5)Analysis and selection of the hardware and software features to implement on node prototypes designed for laboratory testing in order to adapt them, in a short time and with reduced effort, for a relatively long, unattended field experiment with two equally important purposes: to check and demonstrate the autonomous operation of the platform and to acquire sufficient visibility of node and system behavior that can be used to improve the design of the platform.The main contributions of the paper can be summarized as follows:The rest of the paper is organized as follows. Section 2 reviews related published works and defines the specifications of the system through comparative analysis of the strengths and weaknesses of existing methods. Section 3 outlines the design criteria, which drive the platform design decisions. Section 4 explores the most important design decisions made for the implementation of the WSN platform components. Section 5 presents how the prototype platform was prepared for a field test, on short notice. Section 6 presents the unfolding of the field test, the major issues during its various phases and the most important lessons learned to improve the WSN platform. Section 7 presents a summary of the future work and concludes the paper.2.To better define the specifications of the proposed wildfire monitoring method, we will briefly review several of the most representative existing techniques with a focus on cost, detection reliability and effectiveness for early alerting.2.1.Wildfires are quasi-natural hazards likely to occur under specific climatic, weather and vegetation conditions . A smallWhile most common wildfire causes may vary throughout the world ,14, earlWildfire frequency and devastation make the continuous monitoring of the areas at risk one of the most well-known environmental monitoring activities. Although many detection techniques were proposed, cost-effective and reliable early wildfire alerting is still difficult to achieve.2.1.1.Traditionally, wildfire monitoring is based on continuous human surveillance from selected vantage points in the field attempting to recognize smoke patterns during the day or the light from fire flames during the night using visible light ,17. The A class of detection methods look for combustion-generated heat using infrared (IR) imaging. The equipment is rather expensive, has reduced spatial resolution and is prone to false positives ,23. AccuOptical spectrometry can detect combustion-specific products in smoke ,26 by anLight detection and ranging systems (LiDAR) analyze the laser light backscattered by smoke ,29. HighRadio-acoustic sounding detection (RASS) can detect crown and surface wildfires from thermal maps built by inferring air temperature from shifts in the propagation time of acoustic waves . The sysRemote detection systems tend to generate false positives  and need the support of human analysts. Those that are more accurate are also more expensive due to higher equipment and maintenance cost .2.1.2.Satellite-based wildfire detection can reach low false alarm rates in near real time. However, geostationary satellites may have limited spatial resolution, while polar orbiting satellites have limited temporal resolution, which can be significant for rapidly-evolving wildfires ,37. The Unmanned aerial vehicles (UAV) can efficiently monitor for wildfires over large areas ,40. EquiThese methods also share most operating limitations of the ground-based remote detection techniques mentioned in Section 2.1.1, like unfavorable weather, obstructions of the direct line-of-sight, ambient light quality and incidence angle.2.1.3.In situ pervasive wildfire detection has several advantages over remote detection [in situ detection is implicitly redundant to some extent, since the higher sensor density makes it likely that more than one of them detects an event within a short time window. Nevertheless, natural occurring, non-fire-related phenomena  may still trigger false alerts, even for pervasive methods, or the effectiveness of some detection methods may be limited at night or in low visibility conditions.etection . First, in situ monitoring is usually higher than that of remote sensing, both for the initial deployment and for the maintenance [Moreover, it is important to note that the cost per unit of surface of ntenance . Thus, rin situ long-term environmental monitoring, even in wild and harsh conditions [WSNs are among the best-suited systems for pervasive nditions –50, althnditions . WSN nodnditions –55. The nditions  and periMost fire detection techniques used by pervasive WSNs are shared with the remote methods (see Sections 2.1.1 and 2.1.2) with various degrees of detection confidence, power profile and cost ,57. Low-Techniques based on low-power image processing  or radioOther methods are based on the detection of abnormal levels of combustion gases, standalone or combined with temperature detection . HoweverMeeting the stringent requirements for effective long-term outdoor environmental monitoring is generally challenging for WSN technologies –71. Node2.2.in situ pervasive sensing is among the fastest and most reliable monitoring methods. A low false alert rate due to higher detection reliability can reduce the need for human analysis and the effort of the field personnel, thus reducing the exploitation cost. Earlier fire detection can help the firefighters to contain the risks and damages, increasing safety and reducing costs.The analysis in Section 2.1 shows that WSN technology looks well suited for distributed sensing and reporting, but to be economically viable, it needs to scale well for large deployments and to have reduced initial and operation cost: low sensor node cost, reliable operation for extended periods and to require very few or no maintenance at all.Transducers on board the WSN nodes typically use energy sparingly to preserve their reserves and life time. Among the effects of the fire, heat is always present, and high temperatures are among its most devastating effects. The temperature of the surrounding air can be energy- and cost-effectively measured transducers), and the WSN nodes can periodically sample it looking for abnormal temperature patterns that are highly correlated with convection heating from fires. For example, the nodes can alert when the absolute temperature value or its rate of increase rises above specific thresholds . The thrAs discussed in Section 2.1.3, fire detection accuracy can increase by combining measurements from different types of transducers, each sensitive to different effects of the fire. For instance, abnormal air temperatures can be correlated with the levels of infrared radiation on wavelengths closely related to the presence of fire, for the same monitored area.Transducers of different types can be mounted on the same sensor node or on different, specialized nodes. A node with multiple transducers can correlate the measurements on board, reducing network traffic. However, multiple transducers also increase the node cost, energy consumption and resource requirements. They may also add deployment constraints, increasing its complexity and cost.Specializing the nodes by transducer type allows one to differentiate their deployment requirements to optimize their operation. For instance, nodes that sense infrared radiation can be attached to the underside of the lower branches of the trees, facing down, at heights of a few meters above the ground, while the temperature sensors can be attached on tree trunks, at 0.5–1 m from the ground, to have good thermal contact with the hot air rising from nearby fires. The deployment density may also differ by node type. Field data from nodes can be correlated upstream, e.g., on the gateway or server for a typical tiered structure, like the one shown in Application-specific trade-offs are usually made between the required detection accuracy and the implementation cost. The industrial partner initially considered fire detection solutions based on low-cost sensors, which consume no energy in standby mode and that are activated by fire  that can process the transducer data on board, perform self-tests and recover from errors (preserving field data if possible);receive software updates over the air with minimum service disruption and have one or more long-range communication channels (at least the gateway nodes);–network sizes from a few sparse nodes up to a very large number of nodes;–low data traffic per node, in small packets;–resource-constrained reliable operation, with small memory and energy overheads;–reliable operation in case of node failures, especially if several nodes are destroyed by fire;the field communication protocol should efficiently support:transmit events instead of raw data to reduce communication energy by processing the data close to the source (on sensor nodes and gateways);fast and reliable field deployment procedure for network nodes;adequate gateway hardware and software resources and interfaces for application-specific extensions ;node ruggedization to withstand long-term exposure to environmental conditions;long maintenance-free service (the beneficiary requirements were 5–10 years for the sensor nodes);high availability of service for nodes and servers;multimodal access to server data for human interfaces and automated processing;programmable multichannel alerts on field events;automatic detection and reporting of platform faults;extensible server architecture for integration in IoT applications.From the comparative analysis in Section 2.1, the requirements of a WSN platform well suited for reliable and cost-effective long-term pervasive environmental monitoring can be defined as follows:water level of lakes, streams, sewage. Sensor nodes can detect and alert about extreme levels (high or low) and periodically report level statistics;gas concentration in air for laboratories, deposits, ship holds, cities. Sensor nodes can detect potentially harmful concentrations of one or more gases;soil properties for precision agriculture;static or dynamic parameters for structures, e.g., the inclination of dams;position changes, e.g., land slides;lighting level, e.g., for intrusion detection in dark spaces, like cable channels;infrared radiation from combustion (fire) or human or animal presence, for security or habitat monitoring. On-node analysis using thresholds and speed of variation can screen alerts from natural-occurring patterns.These specifications would also allow the reuse of the platform for several event-based long-term applications besides wildfire monitoring, such as:in situ pervasive monitoring solutions.Platform reuse can improve the economic sustainability of its development and maintenance. This is important, since cost can be a major factor that prevents commercial adoption of Node cost, which is roughly proportional to the monitored area and can significantly weigh on the total cost. Generally, a WSN has fewer gateways than sensor nodes; thus, platform design needs to carefully optimize at least the cost of the latter.Exploitation cost basically made up of the cost of the analysts to validate the alerts and the cost of node and network maintenance. The rate of false alerts can be kept low through several techniques: performing the sensing close to the event source, using selective sensing methods less susceptible to interference from unrelated events and using data fusion from multiple sensor types . MaintenDeployment cost, which can significantly increase when the monitored area is difficult to access or if deployment errors are discovered later, during network exploitation, requiring additional field expeditions to correct them. Deployment cost depends also on other factors, such as the complexity and time needed for the deployment of the network nodes, the level of specific knowledge expected from the deployment personnel and node size and weight .The overall cost of the platform has several components that we consider in detail during platform design in Section 3:Most platform costs can be reduced through optimizations of the design of its components with a holistic view of the full system, as will be shown in Section 3.3.We will present in the following the most important node design considerations and decisions based on the specifications in Section 2.2.3.1.in situ monitoring may need to deploy many sensor nodes, which can affect several cost components of the platform. In the following, we will analyze the design options for the major contributors to sensor node cost, as well as their contributions to the various components of the platform cost that were presented in Section 2.2.WSN platforms for pervasive 3.1.1.Energy supply can be an important cost of the sensor nodes. Its role is to provide energy for node operation between maintenance , with the continuity necessary for the expected node quality of service (QoS).An important decision is whether to use a regenerative supply. Energy harvesting can be effective when ambient energy is available, such as vibration, fluid flow, temperature differences and light . AlthougPrimary batteries, on the other hand, store all of the energy needed for the entire node lifespan or the period between scheduled maintenance. The minimum battery capacity can be obtained by multiplying the node average energy consumption and the expected lifespan. Battery cost is roughly proportional to its capacity, but the scheduled maintenance for replacement of depleted batteries can be a major contributor to the overall solution cost.3.1.2.Radio communication is widely recognized as one of the major energy drains on sensor nodes. Thus, it influences the selection of the energy supply (with the criteria presented in Section 3.1.1) and some other node costs that we will analyze in the following.The largest part of the communication energy is typically spent by the receiver while listening for incoming data packets. For this reason, most communication protocols operate the receiver with very low duty cycles  or by radiation . Low-cost and power-efficient transducers, which can operate on very low duty cycles and with less energy, can significantly reduce node and maintenance cost.Radio devices with a baseband modem may reduce the software complexity and energy consumption.The microcontroller resources should fit the application needs closely, since oversizing it may increase the cost and energy consumption on most power levels.3.2.In typical WSN deployments, there are significantly fewer gateways than sensor nodes. Hence, the node cost of the gateways contributes less than the cost of the sensor nodes to the overall cost of the WSN platform. However, the features of the gateways can indirectly influence the cost of the platform in several ways, as we will show in the following.3.2.1.The gateways typically have two types of communication capabilities: long range and short range. The long-range communications are used to connect with the application server either directly or through the Internet. The short-range communications are mainly used to connect with the field nodes, either sensor nodes or peer gateways.Long-range communication can use several technologies. A cellular data network is commonly used in outdoor fields that are covered by mobile data services . AlternaThe constraints for the short-range in-field communications are less stringent for the gateways than for the sensor nodes (which were discussed in Section 3.1.2). The gateways have more energy reserves and computing resources, thus they can support most communication protocols: from simple low power listening (LPL) for random access MACs in star topologies and up to complex routing and synchronization schemes.Thus, the gateways can help reduce the overall cost of the WSN application by supporting the short-range communication protocol that optimizes the cost of the sensor nodes, which is a significant component of the overall cost of the solution.3.2.2.Long-distance communication of the gateways typically requires much more energy than the short-range in-field one of the sensor nodes. Gateways also have more hardware resources, such as larger program and data storage capacity, more powerful microcontrollers or microprocessors and accurate, always-running timers. All of these combined require significantly more energy than the sensor nodes.Thus, the gateways generally have higher energy reserves and may also have ambient energy harvesting devices to increase their lifespan between scheduled maintenance  battery or for the cleaning of the energy harvesting devices). Even if the gateways may require scheduled maintenance more often than the sensor nodes, its cost may be acceptable: a WSN deployment for pervasive environmental monitoring typically has fewer gateways than sensor nodes, and the gateways are generally deployed in locations that are more accessible than the sensor nodes (see Section 2.2), which further reduces the cost of gateway maintenance.Given that gateway energy reserves are far larger than those of the sensor nodes and that gateway maintenance is less expensive than the maintenance of the sensor nodes, it can be cost-effective at the network-level to bias the energy consumption towards the gateways if this helps with reducing the cost of the sensor nodes and their scheduled maintenance requirements.3.2.3.Besides the main function to collect and forward to the application server the field data from the sensor nodes , the gateways can implement other functions that improve the overall system reliability and cost.The gateways should prevent the loss of the aggregated field data in case of non-fatal hardware faults or of self-resets due to software defects. Moreover, in case of repeated or fatal software errors, the gateways should fall back to a safe operation mode, which allows remote debugging or recovery to reduce service interruptions and the cost of in-field maintenance.During field deployment, the gateways should assess the suitability of the installation position in terms of network reachability and link quality with the other nodes and the server, as well as the effectiveness of the energy harvesting (if available).3.3.The main purpose of the application server is to receive field data and store them reliably for later access upon request. It bridges the low-power communication segments (that operate under strict latency-energy trade-offs) with the fast and ubiquitous data access needed by human interfaces or IoT applications. As shown in For a high QoS, the server should implement high-availability techniques, e.g., a secondary server should be kept in sync and automatically take over the service if the main server fails.The protocol between the nodes and the server should be simple to reduce the resource requirements for the nodes and, as much as possible, stateless, because the long-range connections at the fringe of mobile data coverage can be often unstable and the overhead for resuming an interrupted transfer should be minimized. For the same reason, the protocol should provide acknowledgments for data reception, and these should be sent only when the data are successfully replicated on the secondary server to avoid field data loss due to single points of failure.Gateways that need to enter the fail-safe operation mode may use a communication protocol with the server that is optimized for the operations executed in this mode . The server should implement this protocol and the associated operations, as well as promptly notify the operators when a gateway connects using this channel, to take corrective actions.4.Platform design aims at a cost-effective implementation that closely follows the specifications in Section 2 and the design criteria in Section 3.Considering the multi-objective optimization needed to satisfy sensor node specifications and design criteria, we decided for a custom design and development of communication protocols (both for in-field communications and with the server) and node hardware and software.In the following, we describe the design of the prototype platform, the field test preparation and unfolding, the lessons learned from the test and how we can use them for improvements.4.1.The communication protocol can affect the performance of a WSN platform in several important ways. First, the protocol is mostly responsible for propagating the data across the network according to application requirements. Consequently, it controls the most part of the radio activity of the nodes, which is generally recognized as a major energy consumer. Thus, the protocol can significantly influence the selection of energy supply type and size, which relate closely to its cost and to the scheduled node maintenance. Moreover, the characteristics of the communication protocol may also affect the complexity and quality of the field deployment of the network, thus its duration, cost and the need for subsequent corrective network maintenance .Most WSN deployments tend to use simple communication protocols that are enough to satisfy the requirements of the applications . HoweverThe analysis in Section 3.1.2 presents some of the most significant trade-offs to consider when selecting the protocol for a specific application. For instance, using a radio receiver can increase the cost of the sensor node and of the application by adding to the cost of components, of the microcontroller (may require more resources), increases node energy consumption, thus adding to the cost of energy supply and/or the scheduled maintenance to change node batteries. However, a receiver also allows a better management of the communication channel, can increase the reliability of message delivery, can reduce the transmission power per node through multihop message forwarding and can support bidirectional network communication that allows one to remotely query or reconfigure the nodes in the field.normal state: the node periodically communicates its health status and, if possible, some background environmental measurements;fault state: the node communicates the nature of the fault (if the fault does not affect the radio); alert state: the node detected a fire and reports the event in the shortest time, with the highest priority.To define the specifications of the communication protocol, we started from the analysis of application requirements. The communication needs of sensor nodes by state can be summarized as follows:If the nodes periodically communicate their health status and some background environmental measurements, remote node interrogation becomes less important or even impractical for a large number of nodes, which are typical for pervasive monitoring methods (from hundreds to tens of thousands of nodes per application). Thus, for such applications, a bidirectional communication may be less important than the optimization of node cost.Multihop message propagation through the network using a mesh topology can reduce the transmit power of the nodes, which may lead to lower energy consumption at the node level. However, two other factors should be considered. First, operating a radio receiver, even with very low duty cycles, can still significantly raise the energy consumption of the node. Second, lower radio frequencies, which propagate better in forest environments ,89, haveThus, on the one hand, we decided to use the 433-MHz UHF industrial, scientific and medical (ISM)band for its better propagation in forests. On the other hand, we analyzed if a communication protocol based on unscheduled channel access can satisfy the requirements of the application.Communication protocols with unscheduled channel access are well known in the literature . In the Without receive capabilities, the sensor nodes have no means to know if a message reached its destination or was lost. Thus, sufficient communication redundancy should be built into the protocol to keep message loss to acceptable levels for the application. It should be noted that the application is more tolerant to the potential loss of low-priority periodic health status messages than to high-priority and delay-sensitive fire alerts.Higher transmission redundancy may increase the delivery probability of the messages, but it also increases the energy consumption of the node and the probability of collisions. Thus, protocol design should consider the effects of redundancy on message loss and on the delay of the detection of faulty nodes that are no longer able to transmit their status, for various network sizes.For this purpose, we have set up a network simulation model in SystemC  as folloThe gateway node was modeled as a receiver implementing LPLto listen for incoming messages from the sensor nodes. The wakeup period for RF sampling was set slightly shorter than the length of a message, 0.3 s (including the preamble). Normally, the radio receivers can correctly decode the strongest of two overlapping messages if the amplitude difference exceeds the receiver signal-to-noise ratio, thus losing only one of the two. The same stands for messages that overlap only partially over the preamble. However, for the purpose of the simulation, we opted to pessimistically consider that two overlapping messages are both lost, regardless of the amplitude ratio or the extent of the collision.We see that for a given heartbeat period and gateway window, the erroneous node missing events increase with the number of nodes. This is expected, since more nodes randomly sending heartbeat messages increase the probability of collisions, thus of message loss.We also note an increase of erroneous node missing events with the increase of the sensor node heartbeat period for a given number of sensor nodes in the field and a given gateway window. This result can be counterintuitive, since longer heartbeat periods mean less concurrent messages contending for the communication channel on average, thus lower collision probability. However, considering that the gateway window for receiving a heartbeat message from a sensor is constant, a longer heartbeat period means also that fewer heartbeats are sent within the window, which effectively decreases the protocol redundancy that is needed to overcome message losses typical for unscheduled MACs.We used these simulation results to choose a compromise between the frequency of sensor node heartbeats (which contribute to node energy consumption), the delay after which the gateway detects missing nodes and the frequency of false node missing reports. As we will show in Section 4.2, one heartbeat per hour increases node energy consumption by about one third, which we consider acceptable for this application. Furthermore, in under normal conditions, the sensor nodes send one heartbeat per hour;fire alert messages are sent with much higher frequency (every few seconds) to ensure their timely propagation, even at the cost of losing concurrent heartbeat messages. The communication channel capacity can support the alert traffic well, since, assuming no collisions, 1000 nodes sending one 0.3 s heartbeat message per hour each occupy at most 8.3% of the channel capacity;the gateways can detect a missing node in less than six hours.Thus, the main characteristics of the communication protocol can be summarized as:This simple protocol satisfies the requirements of the application well. It does not need a receiver on the sensor nodes, which primarily lowers node cost and energy consumption. Moreover, without a receiver, the operation of the sensor nodes is defined only by their own programming. This means that the energy consumption for each node in normal conditions is predictable, and we calculate it in Section 4.2. In the alert state, the node will spend much more energy in order to propagate in a timely manner the alert messages to the gateways, which can significantly reduce its energy reserves. However, this is not an issue, since the heat of a fire will very likely destroy the node shortly after detection.4.2.Early node prototypes were based on zero standby energy designs discussed in Section 2.2. Since their health status (QoS) cannot be observed, they were abandoned for a typical WSN node architecture: a microcontroller communicating with a radio device and powered by a primary cell, as shown in The prototype was designed mainly to test the operation of the low-resource microcontroller and radio in a compact format, including the radio frequency (RF) performance, and to develop the node firmware, software and in-field communication protocol. Thus, the node printed circuit board (PCB)did not include the transducer, the power supply pads did not fit a standard battery size and it had just generic soldering pads for the antenna .According to application specifications, the node prototype was primarily optimized for cost and size. In this regard, it is worth noting that it has significantly lower resources than a typical WSN node: the microcontroller is an ATtiny25 , one serial peripheral interface (SPI)); the radio for in-field communication is a TI CC1150 with a baseband modem (transmit-only for the 315-/433-/868-/915-MHz bands); and the external accurate resonator for the radio is a 27MHz quartz crystal. The microcontroller uses its internal oscillators (8MHz main clock and 128 kHz watchdog clock) to reduce the external components, the wake-up time and the energy consumption.The average standby current of the sensor node is about 4.7 μA, largely due to the watchdog timer. It samples the temperature once per second with an NTC transducer (discussed in Section 5.1), keeping both the microcontroller and the transducer active for less than 0.05% of the time. The former consumes about 600 μA in active state and the latter a few tens of microamperes; thus, their contribution to node average energy consumption is negligible. The transmission of one packet consumes about 27 mA for less than 0.3 s. Thus, in normal operation , the average current consumption is less than 7 μA, and the node theoretical lifespan with a 1 Ah 1/2-AA size lithium battery exceeds 16 years.4.3.The gateway prototype shown in The evolution shown in It is worth noting that the gateway node prototype is cost- and energy-effective, since it uses hardware resources that are typical for a low-end WSN sensor node (except for the GPRS modem).5.While the platform prototype was still in the early stages of development, it became unexpectedly necessary to prepare all of its components (the sensor and gateway nodes and the server) for an extended two and a half month field test (end of June to early September). The test was set to start in less than two months using 50 sensor nodes and two gateways deployed in an olive tree field in the south-west of Greece. In the following, we will present how we selected, developed and assembled in this short time a platform prototype with the most important features to test in the field. We will also show how we used the results and experience from the test to refine and enhance platform functionality and reliability.The time to field test was too short to design, produce and test new sensor nodes, and we decided to adapt the functionality and ruggedize the node prototypes designed for laboratory tests (described in Section 4). As expected, this adaptation has led to several issues during the test, but also fostered a thorough analysis of the platform operation before, during and after the test, ultimately helping us to significantly improve its reliability and cost, as we will show below.Because the test field was located far away (nearly 2000 km), on-site maintenance would have been costly and time-consuming. On the other hand, since the components of the platform were not developed with the quality necessary to withstand an extended environmental exposure in field, we expected to encounter hardware issues during the test.Thus, we made a development priority to add the necessary monitoring features to collect enough data about defects and anomalies that may manifest during the test, in order to understand their causes and effectively help with improving the future versions of the platform. Most of these features would be needed anyway, since QoS control is always important for long-term outdoor environmental monitoring platforms, especially when monitoring for potentially dangerous events, like wildfires, as was discussed in Sections 3.1.3 and 3.2.3.Based on the analysis in Sections 3.1.2 and 4.1, we chose a star network topology and a very simple communication protocol, because they can considerably simplify the sensor nodes: reduce the requirements for hardware resources, the size and complexity of the communication protocol stack, the energy consumption and the cost. All of these are important specifications for pervasive monitoring platforms and, most importantly, they simplify network deployment to a level where it can be efficiently done by application domain experts or low-skill workers.With the above considerations, we split the network into independent cells, as shown in The sensors in each cell are distributed with the density defined by the domain experts based on terrain and vegetation characteristics  and are covered by two gateways. Each gateway can independently contact the server in order to ensure redundant field message aggregation and upload. Larger application areas can be covered by joining elementary network cells, as shown in Although with a link budget of, e.g., 110 dBm, the communication range in the 433-MHz band can well exceed 10 km in optimal propagation conditions, the actual range in forest (or in the test field) conditions may be much shorter. Thus, the distances in This layout simplifies network deployment (presented in Section 6.1) and ensures full redundancy for field data collection, storage and communication to the server.5.1.The sensor node prototype described in Section 4.2 was designed for laboratory tests. It lacked several features for field tests, such as a temperature transducer, its interface circuit and a microcontroller input to read the transducer. Thus, the node schematic shown in  was manuThese hardware and software changes allowed the sensor node to perform its main functions, monitoring the ambient temperature and notifying about abnormal high levels or too steep increases. The sensor nodes were programmed to measure the temperature once per second and to send specific alert messages when levels highly correlated with wildfires are detected.The sensor node has to support also a fast and error-proof field deployment procedure, as discussed in Section 3.1.3. Even if the field test was using just a few dozen sensors, it was worth defining and testing from the beginning an effective field deployment procedure suitable for large applications, with hundreds or thousands of nodes that are deployed by personnel with no special WSN training.(1)the ID of the sensor node;(2)the quality of the reception of the sensor node messages by the gateways;(3)the field coordinates of the sensor node deployment spot.These three items are especially important during the deployment of homogeneous sensors:The node deployment procedure should minimize human input, because the operators may only have limited training and time. Thus, the automation of the procedure can significantly reduce deployment errors and cost.For an efficient field deployment, it is very important to be able to selectively address the node to be installed while other nodes are within comparable short distance . Relying on the operator to input the node ID can be very time consuming and error prone, so an inexpensive (component cost and energy) near field communication with the node to install is necessary.For this purpose, we added a reedswitch in parallel with the NTC see , which ctrigger the deployment mode of the node by rubbing a magnet on its case. This is an intuitive and error-proof way to address the node under installation;read on a handheld device the quality of the current deployment position;tap a button on the handheld display to validate the deployment and send the data to the server.This node installation flow requires minimum input from the operator, specifically:Because of the short time available to prepare the field test, we implemented this flow only partially. We mounted the reed switches on the sensor nodes and changed the gateway protocol to provide the reception quality in the acknowledgments. The handheld device was implemented using a modified gateway that was displaying only the lowest reception level of the gateways in range on three LEDs.During normal operation, the sensor node periodically tests the on-board temperature transducer given its importance for the detection of the fire. The node can detect short-circuits of the transducer  and open-circuits. The node notifies to the gateways both faults in order to propagate them to the server which warns the operators about the fault.Besides recognizing the extreme cases of short- and open-circuit, the selection of the temperature thresholds for alerts is very important. Low thresholds ensure timely alerts, but they also increase the sensor susceptibility to false alerts triggered by natural phenomena, such as sensor heating by direct exposure to sunlight. These considerations are especially important for fields with high solar exposure, as is the test field during summer time. After some testing, we decided that the fire alert threshold can be set to 60 °C and the threshold for warning of possible fire to a temperature increase rate of 1 °C/s.A normal mode helix antenna (NMHA) was soldered to the antenna pad on the right of the PCB, as shown in The sensor node package designed for the field test is shown in 5.2.To reduce the cost, the gateway node prototype for laboratory tests (described in Section 4.3) is implemented using resources that are typical for a WSN sensor node. The prototype can be used for the field test, although it is not optimized for low energy, as we will show below.The resources of the microcontroller are sufficient for the gateway tasks. However, more SRAM would allow it to aggregate additional field messages, reducing the frequency of connections to the server and the energy consumption.–it can send its field messages to peers, so that they forward them to the server;–send self-diagnostic data to the server through peers to provide the remote operators the necessary information for corrective actions;in case of failure of the GPRS link of a gateway:failures of the field receiver would prevent the gateway from receiving hello messages from peers; thus, the gateway would eventually declare all peers “missing”; however, since the peers would regularly contact the server without reporting errors, this condition can be detected and appropriately flagged on the server;failures of the field transmitter would prevent the peers from receiving the gateway hellos, which they will report to the server; the faulty gateway itself would not report any anomaly.The transceiver for in-field communication is used to receive messages from sensor nodes and to communicate with peer gateways for health checks and to increase the availability of service, e.g.:Gateways require much more energy than sensor nodes due to the continuous LPL of the sensor node channel (to support the random MAC) and energy consumption of the GPRS modem. Although the latter is turned off most of the time, the average energy consumption of the gateway is still too high to allow its long-term operation from a reasonably-sized primary cell. Thus, we installed solar panels on the gateway for energy harvesting, since the test field receives abundant sunlight.Considering the above, the gateway was embedded in a birdhouse, as shown in The solar panels for energy harvesting were placed on the roof, and the internal space of the birdhouse was divided horizontally into two compartments using a wooden separator. In the lower one were placed the gateway, the rechargeable battery and the GPRS modem in a sealed plastic package. The antenna of the GPRS modem was left inside the plastic package, because the test field had good cellular coverage. The antenna for in-field UHF communications, a λ/4 whip, was kept inside the birdhouse for aesthetic reasons. As expected, this position reduced the RF sensitivity, as we will discuss below.5.3.The structure of the application server is shown in For the field test, the application server was updated to support the extensions of the gateway protocol, such as to send the receive acknowledgments to gateways to prevent field data loss, support for new message types for field device health semantics, session initiation and termination and time synchronization with the gateways. The user interface was extended to effectively display many sensor nodes with multiple health states, to improve responsiveness and usability and provide several operator authorization levels.6.Field deployment was scheduled on two days. On the first day, the field planning that was prepared in advance (remotely) was checked, followed by the actual field deployment. During the second day, the operation of the system was checked in the field for final tunings before commissioning to field test. Larger deployments may take more effort and time to complete, but they can follow the same sequence of operations.6.1.Because the system was experimental and the field was rather small, we decided to monitor all communications between the nodes during field deployment from a fixed location near the field, using a modified gateway that was programmed to decode and display the messages as they were sent in the field. To detect abnormal behaviors during deployment and to improve the procedure, the meaning of these messages was manually compared with the state of the field displayed by the server, which was built using the field information received from gateways.6.1.1.The gateways were deployed in the locations shown in While the sensor node deployment procedure described in Section 5.1 provides the means to check the quality of its connectivity within the network, no such provision was made for the gateways, because of the short time we had to prepare the field test. The assessment of the quality of a gateway deployment would include cellular coverage for the GPRS modem, light exposure for energy harvesting and the coverage of the sensor nodes in the field.For this test deployment, we checked manually in the server log that the gateways were able to successfully connect. Furthermore, we monitored the field messages in real time for reports of success (or errors and retries) of the connection steps performed by the gateways: register with the cellular operator, access the GPRS service and open a socket with the server over the Internet.The deployment places for the gateways were chosen so that one solar panel was roughly directed towards south or on the east-west axis, and the sunlight was reaching them without major obstructions. 6.1.2.Once the gateways were in place and operational, we started to deploy the 50 sensor nodes in the locations shown in Using the node deployment procedure presented in Section 5.1 , we needed about 4–5 min to install one sensor node in a relatively simple field see  and 9b: Nevertheless, it took us about four hours to deploy all 50 sensor nodes. This means that node deployment is generally effort intensive and can significantly increase the cost of larger applications.6.2.6.2.1.Although the size of the test field was relatively small compared to the communication range in ideal conditions of about 17 km for the 433-MHz band with a 110 dBm link budget, we noticed during deployment that some nodes at more than 50–70m from gateways were received little or not at all.Several design decisions reduced the communication range. First, the placement of the gateway antenna for field communications between the solar panels of the birdhouse see  reduced After the test, we discovered two additional RF attenuation causes on the PCB of the sensor node. As shown in The layout of the baluns of both the sensor node and the gateway shown in  and 4a wThe package of the sensor node shown in  was intrAnother attenuation cause was due to terrain geometry. The test field shown in In general, the deployment positions of the gateways on hilly terrain should be carefully analyzed during planning. Nevertheless, there can always be propagation issues that are discovered only during deployment . Some of these issues can be fixed by changing the position of the sensors . In other cases, we can always add a gateway to cover these areas or, even better cost-wise, a repeater device.6.2.2.As the deployment of the sensor nodes progressed and the Sun approached the zenith, some of the sensor nodes waiting to be deployed started to send fire alerts. Apparently, this was because the nodes were transported in a dark color backpack which excessively heated them while lying idle in direct sunlight .6.3.After all nodes were deployed and the operation of all platform components was checked, the field test started for two and a half months.6.3.1.vs. charge relationship, shown in Post-deployment checks missed a very important fault. The battery charging circuit of the GPRS modem of Gateway 2 failed during deployment and was not charging the battery. We discovered this too late, after we left the field, because we were monitoring the battery voltage (measured by the GPRS modem), and the potential The battery charger of the modem of Gateway 2 may have failed because of overheating during deployment due to a combination of the following three factors. First, Gateway 2 was the first deployed, thus it received more sun heat, which increased its internal temperature. Second, it received and forwarded to the server most of the false fire alerts generated by the sensor nodes, which additionally increased the temperature of the modem. Third, since the solar panels were well illuminated, they were charging the battery, thus increasing the temperature of the charging circuit even more.As Gateway 2's battery progressively discharged, we monitored the effectiveness of the built-in in-field redundancy. The GPRS modem does not work below 3.2V, but the rest of the gateway (microcontroller and field radio) operates until the battery is completely discharged (lithium-ion batteries stop working around 2.7 V). When battery voltage dropped below the low threshold of the GPRS modem and it ceased to work, Gateway 2 continued to operate as a repeater, forwarding to its peer the messages received from the sensor nodes in its range. Gateway 1 aggregated them with its own messages and sent them all to the server, maintaining the redundant coverage of field nodes, as expected. When Gateway 2 eventually stopped working completely, Gateway 1 detected the new fault condition and notified the operators through an error message sent to the server.Another temperature-related issue was due to the limited range allowed for charging the lithium-ion batteries, 0–45 °C. Open nature temperatures can exceed this range, thus blocking battery recharging and, eventually, reducing its lifetime. These limits make lithium-ion rechargeable batteries less suited for open space environmental monitoring.During our field test, high daytime ambient temperature combined with heat from gateway direct sun exposure and heat released during GPRS communication and battery charging were often blocking battery charge during the central hours of hot days. 6.3.2.Thermal expansion mismatch between the PCB and the NTC leads generated repeated mechanical strains due to cyclic temperature variations of 15–20 °C between day and night. These eventually led to fatigue cracking of NTC solder joints on some sensor nodes, which, in turn, led to intermittent contacts, especially during morning and evening hours, when the temperature changed most rapidly. The sensor node decoded the imperfect contacts as fast ambient temperature changes, and notified these right away to the gateways as wildfire warnings (see Section 5.1). The gateways handled these warnings the same way as fire alerts, forwarding them immediately to the server to promptly notify the operators.Since the GPRS modem is one of the highest energy drains of the gateway, keeping it powered up for a few hours in the morning and evening every day to forward these warnings eventually consumed more energy than the harvesting capacity of the solar panels and discharged the battery of the only gateway left. Its failure required a maintenance operation to restore both gateways to full functional state and to replace the faulty sensor nodes.Such sensor node faults can happen also in large deployments that should run unattended for many years. Thus, the system should be able to exclude the network effects of faulty nodes before they can create larger problems that may lead to  loss of service. For this purpose, we decided to provide the gateways with a list of sensor node IDs that should be ignored and which can be set remotely by the operators when needed. Such a list would have helped us avoid a costly field trip for maintenance during the test.Last, but not least, all systems powered by harvested energy (which may fluctuate widely reaching very low levels) should have brown-out detection (BOD) enabled to avoid entering non-functional states when the battery voltage is too low. Because the BOD was not enabled on the gateway prototypes, Gateway 1 failed several times to return to normal operation after periods of insufficient energy.7.In situ pervasive environmental monitoring for wildfires has important advantages, but the relatively high area cost may limit its use. We have shown in this paper several domain-specific platform optimizations that reduce the cost and increase its economic viability.Sensor node hardware and a communication protocol optimized for application requirements can exceed 10 years of life time using a small, low-cost primary cell. Long node life significantly reduces the cost of the scheduled maintenance of the network, which can be important for large networks. The nodes and the communication protocol also speed up field deployment. The deployment procedure prevents most human errors, significantly reducing the cost, especially for networks with a large number of nodes.Field experiment preparation and unfolding highlighted several aspects that can improve the cost and reliability of the network components, their deployment, operation and maintenance.Long-term direct node exposure to climatic conditions increases the failure probability. Additionally, large networks are more likely to experience node failures. As we have seen during the field experiment, failed nodes may adversely affect network operation or strain the resources of the gateways in range, increasing maintenance cost. Thus, it is important to increase node and network robustness during design, production testing, functional and self-test specifications and run-time monitoring.As we have shown, node hardware design and production testing were not adequate for the field experiment and led to several node failures. Accumulation of mechanical stress should be reduced by design and during production, since it compounds, e.g., with the stress from daily and seasonal temperature variations or unforeseen mechanical interaction with wild animals. Manual soldering should be avoided, since it can inadvertently create strains in solder joints in the interaction with component leads.Faulty nodes should be detected as soon as possible to reduce production costs, e.g., by running specific self-test programs at the end of the production line.Lithium primary batteries have shelf lives in excess of 10 years. Compared to ambient energy harvesting techniques suitable for open nature, primary cells can reduce node cost, increase reliability and reduce node deployment complexity. These cells can supply very low power nodes cost effectively and maintenance free for more than 10 years, a life time suitable for many WSN applications.Brown-out detectors may consume too much energy and should not be needed for long lifetime nodes with soldered batteries. However, it is important to reset the nodes right after the battery is soldered to avoid leaving them in abnormal states that may excessively drain the battery.Sensor node functions and a communication protocol carefully tailored to the application requirements can bring important cost reductions. For instance, transmit-only nodes in star topologies can reduce the protocol stack and relax the accuracy requirements for on-node timing. In turn, these reduce microcontroller resources and energy consumption, significantly lowering the cost of components, battery and node maintenance. However, without a receiver, the nodes cannot create mesh topologies to improve network robustness and to reduce transmit power. Thus, the cost and benefits of such optimizations should be evaluated in the context of the specific application or application class.Periodic node self-testing and automatic error recovery increase the reliability and the QoS of the monitoring platform, reducing maintenance requirements and cost. In case of critical failures , the nodes may disable themselves after reporting the fault to avoid reporting false events or impairing the operation of the network or the gateway nodes, as we have witnessed during the field experiment.Small sensor node physical dimensions and protection from environmental conditions may reduce the RF efficiency in several ways. For instance, the antenna may end up too close to large ferromagnetic bodies, like the battery side seal or the case of the quartz crystal resonator in our experiment. While we could use a different case for the crystal resonator to avoid changing the node geometry, we had to increase node length to leave enough distance between the antenna and the battery seal. Furthermore, protecting the antenna inside the node package reduced its efficiency by 2 dB, but we found no cost-effective way to avoid it. However, component cost is less important for gateways, and we plan to install their antennas clear of the package or solar panel shielding, which have markedly reduced their performance during the field test.Changes in gateway behavior in the case of failures  need to be detected at the gateway or network level and reported to network operators to schedule corrective actions. Remote configuration or reprogramming should be available, at least for the gateways, in order to be able to remotely add functions, correct errors or protect the network against occasional faulty node behavior. As we have seen during the field experiment, this feature would have spared us an unscheduled maintenance, whose cost can be important for remote fields or large networks.Nodes that store field messages before forwarding  should implement suitable in-field redundancy to avoid loss in case of self-reset or failure. Additionally, we plan to implement a save-restore function on gateways to preserve node data across watchdog-triggered resets.Gateway nodes handle higher energies, which can generate significant heat, both during harvesting and consumption peaks . Thus, as we have seen during the field experiment, an adequate thermal dimensioning considering the climate and the internal and external heat sources is important. For some applications, we may consider other energy accumulation techniques instead of the widely-used lithium-ion batteries, which have limited charge-discharge cycles and temperature restrictions for charging and operation.We also consider redesigning the power supply of the gateways to automatically switch to a primary cell whenever the harvested energy reserves are too low, to increase the node QoS. Unlike the sensor nodes, which are reliably supplied by the battery soldered on-board, the energy reserves of the gateways can fluctuate due to unpredictable harvesting and consumption patterns. Moreover, the rechargeable batteries can be changed when they loose storage capacity. Hence, the use of the embedded brown-out detector can considerably improve gateway stability.The field experiment showed us that the deployment of the network can be very time-consuming, even for networks with just a few dozens of nodes. Thus, the procedure should be simple and automated as much as possible to be accessible to domain operators, to reduce human errors and cost. Nevertheless, it should allow one to thoroughly check the quality of node installations, since RF propagation in open nature can be unpredictable, not the least due to small and difficult to notice terrain features. We plan to improve the user interface of the handheld installation device, automate position collection and data reporting and extend it to the installation of the gateways. For the latter, it should assess cellular coverage for the GPRS modem, light exposure for energy harvesting and the coverage of the sensor nodes in the field. We also decided to develop a repeater node that can improve gateway coverage of the field in difficult propagation conditions.® Sensor Web Enablement [WSN platform design, development and maintenance has a high cost, which can be recovered faster if the platform can be reused for several related application domains. While the sensor nodes do not have sufficient resources to support an IP-based protocol, the gateways are IP-enabled, albeit they are sporadically connected. The server, however, is always accessible over the Internet, and in future versions, it can implement suitable interfaces  to f


Variability of Practice (VOP) refers to the acquisition of a particular target movement by practicing a range of varying targets rather than by focusing on fixed repetitions of the target only. VOP has been demonstrated to have beneficial effects on transfer to a novel task and on skill consolidation. This study extends the line of research to musical practice. In a task resembling a barrier-knockdown paradigm, 36 music students trained to perform a wide left-hand interval leap on the piano. Performance at the target distance was tested before and after a 30-min standardized training session. The high-variability group (VAR) practiced four different intervals including the target. Another group (FIX) practiced the target interval only. A third group (SPA) performed spaced practice on the target only, interweaving with periods of not playing. Transfer was tested by introducing an interval novel to either group. After a 24-h period with no further exposure to the instrument, performance was retested. All groups performed at comparable error levels before training, after training, and after the retention (RET) interval. At transfer, however, the FIX group, unlike the other groups, committed significantly more errors than in the target task. After the RET period, the effect was washed out for the FIX group but then was present for VAR. Thus, the results provide only partial support for the VOP hypothesis for the given setting. Additional exploratory observations suggest tentative benefits of VOP regarding execution speed, loudness, and performance confidence. We derive specific hypotheses and specific recommendations regarding sample selection and intervention duration for future investigations. Furthermore, the proposed leap task measurement is shown to be (a) robust enough to serve as a standard framework for studies in the music domain, yet (b) versatile enough to allow for a wide range of designs not previously investigated for music on a standardized basis. Playing music is a complex motor skill orchestrated by sequences of goal-directed movements. Given the overall difficulty of the skill and the volume of the pool of motor programs to be mastered, the efficiency of practice in the allocated practice time has to be optimized. In this respect, findings from motor learning research may be applicable to facilitate learning of musical instruments. Several concepts and parameters regarding the design of learning schedules have been introduced to research, specifically variability Schmidt,  and distschema as an abstract code for a class of movements with a common pattern. Schema learning, then, is the gradual formation of a central prototype from a number of specific experiences within a motor class. Introducing variability in practice therefore is a key concept as it relates to the idea of generalization of movement patterns. Regarding the potential benefits of variability, two contrasting hypotheses have been proposed:The specificity of practice hypothesis  feasible even in subjects with no previous exposure to the specific task. On the other hand, proper execution is challenging enough to leave ample space for improvement through practice, i.e., ceiling effects were unlikely. The same reasoning led to choosing (a) the left hand as the motor executor  similar or higher error rates after acquisition but (2a) lower error rates at RET and (2b) at transfer of the skill to a novel target.In addition to the primary hypotheses as derived from error rate measurements in previous motor learning research, our secondary aim is to exploit the dataset as observational pilot material in order to derive hypotheses for further variables that are closely tied to musical precision and expressiveness. These hypotheses may serve as a starting point for future empirical approaches in this young area of motor learning research.p-values > 0.05). Prior to the experiment, written informed consent was obtained from all participants. The experiments were performed in accordance with relevant institutional and national regulatory standards.Thirty-six right-handed music students took part in the experiment . All participants studied piano as their minor subject. Demographic information, handedness . Standardized instructions and tasks were presented on a monitor placed in front of the subjects using Presentation® software Version 16.1).6.1.1). PThe core task was to train to perform a wide interval leap on the piano with the left hand.The first musical event (upbeat), at the starting position of the leap, consisted of two notes (with an octave distance between them) to be played simultaneously by the thumb and little finger, respectively . The metronome provided a two-measure count-in but did not continue to provide an auditory pace once the movement was initiated.The three experimental groups Figure  performeFIX group: Participants in the fixed group underwent a massed practice of the target interval only, thereby repeating it 160 times.VAR group: These participants received variable training on the diatonic intervals 8, 12, 15, and 22 semitones, respectively, thereby spending 25% of their trials on each interval. The 40 instances of each interval were administered in a blocked-random order: intervals were presented in small blocks of five identical intervals each; the block order was randomized; yet immediate reruns of identical blocks were avoided. While the actual target interval was part of the item pool, the transfer interval was omitted.SPA group: Participants in the “spaced” group practiced the target interval only, but (unlike the FIX group) only for a total of 40 trials. The trials were bundled to blocks of five each (like the VAR group). These 1-min blocks were sparsely presented with intermittent 3-min phases of not playing. During these 3-min resting phases, the participants were instructed to read portions of a short story. Focus of attention on the reading was established by informing the subject to be quizzed on details of the content later (the quiz consisting of three simple multiple-choice questions).Between PRE and POST testing, participants underwent a 30-min standardized computer-interactive training session . Each of the three groups received a different practice schedule Figure :FIX groAfter each block, a screen display prompted the subjects to start the subsequent block actively by pressing the left piano foot pedal, providing the opportunity to insert moments of rest when needed. Besides the actual training intervention, participants gave written consent that on the day of the PRE measurement and during the period between POST and RET assessment (approximately 24 h), no further practice or other exposure to keyboard instruments was allowed.2700 trials from PRE, POST, and RET assessments were recorded. Of these, 2549 were included in the analysis after discarding unanalyzable trials . Data from the training phases were not included. Statistical tests were done using SPSS 19 (IBM).The MIDI and Presentation® logfile data were consolidated into single ASCII raw data files. These were subsequently preprocessed in order to extract first level (within-subject) sums (primary variable) or medians (secondary variables), respectively, for each phase , condition , and subject.primary variable of interest to assess musical performance precision (as formulated in the a priori hypotheses) was the overall number of missed and incorrectly played notes at the time points PRE, POST, and RET, hence indirectly reflecting spatial accuracy of the leap movement. The Median Error Score (MES) aimed at quantifying all relevant aspects of hitting a prescribed note correctly (or failing to do so) within the allocated time window. It was defined as the total count of all errors across all trials of each condition for each participant. The following events added to the gross error score, equally weighted: any required note that was missed; any slip note ; any additional wrong note within a time window from 500 ms before nominal onset to 500 ms after nominal end of the leap movement.The Statistical comparisons for specific hypotheses on group level were carried out using Mann-Whitney tests (between groups) and Wilcoxon tests (between sessions and between TGT/TSF within groups). Reported tests were Bonferroni-corrected for familywise Type I errors due to multiple comparisons. Global alpha was set at 0.05 level.Timing is a possible confound for error rates, because e.g., the more slowly a subject would play  the better the chances of avoiding wrong notes. Therefore, it was important to objectify that no systematic timing differences would account for any of the apparent error differences .secondary variables were defined, derived from the MIDI data, and subjected to an exploratory data analysis encompassing visual inspection of data. Based on these considerations, the following secondary metrics will be reported as promising candidates for hypothesis-generations and inferential tests in future research:Leap Execution Time (LET). LET is calculated (in milliseconds) between the times of the start point and end of the leap movement, i.e., the time needed to travel the interval distance. Since at each position two notes were played in octave grip almost simultaneously, the mid-time point of the two note onsets was considered, respectively. The LET metric is of relevance since the metronome-guided time goal for the leap was 187.5 ms (1/16 note at 80 BPM). This ambitious goal was deliberately set to be not within reach for any one of the subjects (showing average times of ~280 ms). Hence, achieving faster leap times while preserving low error scores serves an additional indicator of training success.Leap Loudness (LL): the MIDI key velocities of the end position of the leap. LL indicates how loud the musical downbeat was being played; analogue to the LET, the key velocities of both notes of the octave grip were averaged.Leap Loudness Homogeneity (LLH): the average difference between the MIDI key velocities of the end position of the leap  and the starting position of the leap (upbeat), respectively; as for the LET, both notes of the octave grip were averaged. LLH is different from LL as it independently quantifies the degree of loudness homogeneity across the movement (regardless of whether the leap was being played loudly or softly).This study is the first of its kind adopting the described motor learning paradigm to a musical context. Therefore, a series of possibly relevant Due to the exploratory selection of variables, and due to the pioneering nature of the data , the present work will report these secondary data on a descriptive statistical level only.p > 0.05, Mann-Whitney). Furthermore, longitudinal within-group comparisons revealed no significant PRE-to-POST or PRE-to-RET changes due to the training session . Immediately after training (POST), the FIX group performed with significantly more errors at the transfer (TSF) compared to the target (TGT) task . Conversely, at RET, the VAR group generated significantly more errors at TSF compared to TGT . No further differences were seen between the error rates in the transfer task and the target task for any group at any time point .MES for all groups, conditions, and time points are summarized in Figure Leap Execution Time  displayed slowest LETs, and vice versa (POST|TGT performance of FIX and VAR groups). Hence, a slower execution of the movement does not seem to facilitate hit rate.Leap Loudness (LL). MIDI key velocity is an arbitrary scale with a value range between 0 (silence) and 127 . Before training (PRE), all groups performed at similar velocities . After training (POST), no differences seemed to be present between groups either. During the RET session 24 h after initial acquisition, however, the VAR group apparently played louder in the TGT as well as in the TSF condition  compared to the other groups .As with LET reported above, longitudinal changes seemed to be most pronounced in the VAR group: compared to PRE, the POST loudness was greater for both TGT  and TSF , and the RET loudness was greater for both TGT  and TSF .Leap Loudness Homogeneity (LLH) data are summarized in Figure The present study aimed at the primary goal of testing whether the “VOP” hypothesis derived from Schmidt  schema tParticipants underwent different training strategies to improve their error on the task: a group of fixed learners (FIX) received a massed practice session on the target interval. Immediately after training, this group non-significantly improved performance on the trained task but showed significantly higher errors rates at a novel transfer task compared to the trained interval; however, after a 24-h RET period, performance on the transfer task was comparable to the performance on the original task.By contrast, the VAR group received the same amount of training but variably distributed across four different intervals (including the target). Like the FIX group, the VAR group also non-significantly improved during the training, yet the POST training error rate for the untrained transfer task was similar to the trained task. Following the RET period, target performance was still comparable to the state immediately after training, however, the error rate on the transfer task was significantly higher compared to the error rate in the target interval in the same group.Hypothesis (1), namely, no immediate advantage on target performance for VAR learners over FIX learners would occur, is therefore supported in the sense that all groups performed at almost identical error rates immediately after training.The error data at this specific time point (POST), however, may have to be taken with some caution: the lowest error scores achieved throughout the study  are all within the same narrow range (resembling an error incidence of around 0.26 per note). This might indicate the presence of some ceiling effect. Possibly, this error rate is close to rock bottom of what can be accomplished in this specific constellation .The theoretical underpinnings of hypothesis (1) stem from specificity-of-practice considerations Henry,  and fromIn line with these studies, in the present data a contextual interference effect could not be observed with respect to error rates: rather than showing an initially worse performance compared to the FIX group at the end of the acquisition phase, the VAR group performed equally well right after training. It has to be noted, however, that the one (and only one) specific schedule employed for the VAR group in the present study does not allow to conclusively disentangle the two CI hypotheses. The study design aimed at the general effect of presence/absence of VOP rather than addressing the specifics of CI phenomena. The findings also imply that the specificity (SOP) hypothesis Henry,  is not cWith respect to the ability to retain and consolidate the skill, hypothesis (2a) predicts a superior performance after a 24-h RET period without further training intervention in the VAR group compared to the other groups. Since the present data do not show significant changes due to the intervention in any of the groups, and, furthermore, since at RET no significant differences emerge between groups, our results are not in line with the RET hypothesis (2a). However, this does not conclusively reject the prediction and might as well simply indicate that the initial acquisition phase was not sufficiently long to generate immediate to-be-retained performance improvements in the first place.In terms of the ability to transfer the acquired skill to a novel task within the same movement class (hypothesis 2b), the VAR learners performed the transfer task at a similar level as the original target. In contrast, the FIX learners now showed a significantly higher error rate in the transfer condition than in the trained original task.The notion that the trained VAR group performed at the same error rate on the target interval as the FIX group is worth highlighting inasmuch as their acquired number of different content items was four times as high (compared to the FIX group). It is reasonable to assume that the three additional intervals practiced during the intervention (but not tested afterwards) would have yielded similar skill outcomes in the VAR group as the tested target interval. The FIX group, in contrast, was never exposed to these additional intervals and (if tested) might have shown similar performance as for the transfer interval that was used as the probe for transfer capabilities. Taken together, it is remarkable that after the same net amount of practice trials, the VAR group might be able to play five different intervals just as precisely as the FIX group is able to play just one of them (while probably failing at any one of the other four).prime rather than by genuine training-induced changes to the motor system. The plausibility of the “priming” interpretation receives additional support from the observation that the interference effect is washed out by the time of RET testing.Although this appears to be supportive of hypothesis 2b, it cannot be ruled out that this strong immediate effect is due to a motor interference rather than due to an actual lack of capacity to generalize to a transfer leap within the same movement class. In other words, the failure to play the transfer task correctly may be mediated by the obstinately imposed After the RET period, the VAR learners are the only group showing a significant difference between target and transfer performances. However, surprisingly the direction of the effect is opposite to what is predicted by hypothesis 2b.transfer condition (for any data obtained in this particular paradigm) do not necessarily allow for conclusions regarding generalization of an acquired motor skill (in terms of a skill extension within the same movement class). The TSF leap (19 semitones) lies within the range of trained intervals for the VAR group . This within-range position of the novel movement was chosen in order to reflect the original barrier knock-down design by McCracken and Stelmach . Since none of the within-group or between-group comparisons involving SPA yielded significant effects after correction, the following considerations are made only tentatively. In general, however, the lack of significant between-group effects indicates that neither the target nor the transfer performances in this group are different from the other two learning strategies, i.e., the present data do not show a general disadvantage of sparse practice for the task and timeframe under investigation.In this study, a third intervention for another group of participants  was included in order to circumvent an interpretative ambiguity for any learning-induced performance differences on the target interval: are the putative training effects of the VAR group due to the fact that the VAR group trained additional varying material besides the target, or could they be just due to the fact that the VAR group simply spent only 25% of their practice resources on the target in question? The SPA group provided the missing link as they did the latter  while at the same time An interpretation of the SPA results in the POST session is difficult: the overall level of (a) cognitive load and interference; (b) distraction; and (c) fatigue effects are probably different between the SPA group and the VAR/FIX groups. Interference effects between a motor task and a secondary task may occur if one or both of the tasks require sufficient attention and the two tasks share limited resources Schmidt, . ImpositThe final outcome (RET) of the SPA intervention is similar to VAR with regard to error rate (TGT and TSF) and, on descriptive level, appears slightly slower than any of the other groups with regard to execution times, and similar to FIX with regard to loudness. Therefore, it might be the case that spaced learning combines the “worst of both worlds” with respect to variable and massed-fixed training strategies, respectively.Massed practice (regardless of whether it introduces variability or not) leads to an overall increase of motor execution speed immediately after practice, and after a RET period.Variable practice schedules increases the execution speed to a greater extent than do constant or fixed schedules  applied to the instrument and may thus reflect a build-up of confidence regarding the acquired skill, both in the practiced condition as well as in novel challenges from the same movement class.Conversely, a fixed training intervention (regardless of massed or sparse schedule) leads to a substantial (immediate and retained) decrease of applied forces, for both the trained task and similar novel tasks. In the case of the piano interval leap, this might be interpreted (a) as a detrimental effect on self-evaluated confidence at the skill; or (b)—because of the correlation of key velocity and terminal speed of the moving hand –, as a positive indicator of heightened precision motor control compared to variable learners .The investigated secondary variables are not intended to represent a report of scientifically robust results. This study aims at empirically extending the idea of VOP to musical practice. Therefore, while being able to objectify hypotheses concerning the primary variable, in the current setting the quest for ecologically meaningful secondary variables is exploratory. In the following, the main observations on secondary variables are summarized and putatively formulated as predictions that may be addressed in future research:changes only would not narrow the distribution range either: the POST-to-PRE score difference was distributed between a maximum of +41 additional errors after training compared to before training, and a minimum of −23 errors in the best learner. This additionally indicates that participants might as well be differentially susceptible to specific types of training strategies like fixed vs. variable schedules. Table As is reflected in the error bars (quartiles) of Figures The design of this study involved the possibly rather limited impact of a single and short training session. In the motor learning literature, interventions typically range up to several weeks. Studies with a more ecologically valid schedule—although difficult to control—may involve multi-session training with long-term RET testing . Gradual increasing CI within-schedule has been shown to affect the outcome positively  or Knowledge of Results to the observed effects. While KP refers to the instant sensory feedback inherent to a motor action and practice situation, Knowledge of Results (KR) addresses offline forms of abstract or quantified information provided after a practice trial, like, in instructional settings, the verbal feedback given by an educator. The current design implies a characteristic feature of music instruments in that they provide intrinsic KP feedback for each single trial, thus often rendering KR redundant  in order to reflect actual real-world demands of music motor behavior. Previous findings suggest that the effects of VOP may depend on the qualitative properties of the task in training and transfer  produced significantly more errors in the transfer compared to the target task at RET testing. As a limitation, none of the participant groups measurably improved on the primary variable (error rate) after only one training session. Thus, the results provide only partial support for the validity of the VOP hypothesis for the given setting. In order to reach conclusive results, additional research is needed that addresses the recommendations derived from the current data, namely (1) a more homogeneous participant sample; and (2) a more extended multi-session training intervention.From a more general perspective, in many real-world musical challenges certain benefits of variability  cannot be overstated: firstly, greater diversity of the tasks may allow learners to extract the most relevant, task-invariant information. Especially in the initial stages of becoming acquainted with a new instrument or a new technique, this might facilitate faster training progress in the mid- and long-term. Using variable rather than rigid movement material has been shown to recruit additional brain areas like prefrontal cortex , or the acquisition , analysis , and interpretation  of data for the work. All authors were involved in drafting the work or revising it critically for important intellectual content, in the final approval of the version to be published, and consented to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.This research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Elderly patients with cancer are frequently undertreated as they are considered to be unfit for treatment due to inaccurate estimations of the operative risk. In the current study, the case of an 81-year-old female smoker with advanced breast cancer is presented. The patient had received numerous cycles of chemo- and hormonal therapy and the cancer only progressed locally. After six years, the patient developed a second type of cancer; a moderately differentiated squamous cell carcinoma of the tongue. The patient refused any local treatment and she received supportive care only. There is currently a lack of data regarding the molecular mechanisms of second primary cancers as well as other delayed outcomes following cancer treatment. Therefore, it is proposed that chemotherapy may promote the presentation of the second cancer as a result of immunosuppression. The incidence of breast cancer is higher in elderly patients (>65 years) when compared with younger patients (<65 years old), with the elderly being associated with an increased mortality risk . For eldde novo cancer  has been observed in the elderly .The development of squamous cell carcinoma of the tongue may depend on various factors, which include the human papilloma virus (HPV), alcohol consumption and smoking . In the 3/μl in September 2011, with the level of neutrophils above the normal range). This tumor progressed to involve the floor of the mouth and the left border of the tongue. The histological analysis determined that is had not originated as a result of metastasis from the breast lesion; it was diagnosed as a moderately differentiated squamous cell carcinoma. The patient refused any local treatment and received only supportive care. The involvement of the left breast and axilla by the breast cancer, and the tongue cancer are demonstrated in In March 2005, an 81-year-old female smoker was diagnosed at the Medical Oncology Unit of the San Giovanni di Dio Hospital  with advanced left breast cancer. The tumor was characterized as estrogen and progesterone receptor-positive, and human epidermal growth factor 2-positive. The tumor was treated with numerous cycles of chemo- and hormonal therapy and the cancer only progressed locally. The patient did not show metastases to any sites during the follow-up period. The patient received the following combination treatments: Capecitabine, anastrozole, pegylated liposomal doxorubicin and vinorelbine; trastuzumab and fulvestrant; docetaxel, gemcitabine and trastuzumab; and capecitabine and lapatinib. In August 2011, the patient presented with a painful nodule on the tongue, which had been gradually increasing in size. The patient’s clinical analysis identified an elevated leukocyte count (19.32×10Tobacco smoking and alcohol consumption are the principal risk factors for developing tongue squamous cell carcinoma . In addiThe percentage of elderly people with HNC is rising as a result of the increasing average lifespan; ~10% of HNC occur in patients aged ≥80 years . ManagemDecision-making in the present case was based on the patient’s characteristics and age, however, was also based on a performance status evaluation, comorbidity and a patient-reported outcomes assessment. This mode of conduct is similar to that which was proposed in a recent study regarding geriatric patients with HNC .An additional case of a young female who presented with tongue cancer that later developed into breast cancer was identified in the literature . In addiIn conclusion, in the present case, the origin of the second cancer was unknown, however, the patient was an elderly female who smoked, which may have been a possible cause of the tongue tumor. Furthermore, previous chemotherapeutic treatment may have been involved in predisposing the patient to develop the second neoplasm. A possible mechanism is chemotherapy-induced immunosuppression, which is a well-recognized cause of skin tumors, specifically squamous cell carcinomas . The pre