Research on the development and functioning of technology platforms specifically for health applications in sub-Saharan Africa (SSA), is limited. The healthcare sector has also been resistant to platform adoption due to characteristics such as sensitive data and high cost of failure. A framework for the design, development and implementation of technology platforms in the South African health context could therefore contribute to the gap in research as well as provide a practical tool that platform owners could use to potentially increase the adoption of platforms in this context.The research design for this study was based on the Grounded Theory Conceptual Framework Analysis process. The process focused on mapping and investigating data sources, categorising and integrating concepts, synthesising these concepts into a framework and iteratively evaluating the framework. The first stage of the evaluation process was a preliminary evaluation exploring an existing Health platform in South Africa (MomConnect). The second evaluation stage included local and international interviews with nine experts to identify any missing concepts in the framework. Stage three included a case study and case study interviews which led to the formulation of the final framework and management tool.The developed and evaluated framework comprised three components, namely the pre-use component, which includes considerations the platform owner should be aware of prior to using the framework. The framework comprises of two dimensions, 1) an ecosystem dimension to guide the platform owner to consider different ecosystem actors before embarking on designing a platform 2) a platform development dimension that include typical platform development components and presents an interpretation of the viewpoints included in the ecosystem levels.The final framework can be used by platform owners as a management tool. A unique contribution of this study is that the framework draws from two platform perspectives, namely the engineering and the economic perspectives to provide a holistic understanding of platforms. Finally, a contribution of this article is the tailoring of the framework for the South African health context. Health systems in sub-Saharan Africa (SSA) are in dire need of effective and sustainable solutions . InitiatTechnology platforms refer to the technology that provide a software-base upon which interactions and transactions between several actors can take place  and can The accessibility of large volumes of health-related data obtained from sources such as Electronic Health Records (EHRs), data banks, Internet of Things (IoT) sensors, other data-obtaining medical devices and mHealth applications , can be Building on this premise, the purpose of this research was to develop a framework that can serve as a guide to support the design, development and implementation of technology platforms in the SSA health context and can thereby ultimately contribute to improved experiences for the end-users of health services. It is envisaged that the proposed framework could contribute to the increased and sustained adoption and use of health platforms. By adopting an ecosystem perspective, the proposed framework provides a useful perspective of the platform actors and the environment they encounter in the SSA context. Often ICT4D interventions in healthcare fail due to a lack of uptake, lack of interoperability and coordination among ecosystem participants. For example, end-to-end visibility in the medicine supply chain in South Africa’s (SA’s) public health sector remains an elusive goal with a wide range of participants with different systems and reporting processes – here there remains a lack of a common platform used by all participants –15.How can the design, development and implementation of technology platforms in the SSA health context be better managed?The core issue that this study aimed to address was: The proposition made in this article is therefore that if a set of guidelines or a framework for developing technology platforms could be developed it may act as a practical and facilitating tool for platform owners to meet the needs of various actors in its ecosystem. In order to develop the tool, the perspectives of different ecosystem actors and the conditions under which they will be able to develop solutions in a platform environment need to be better understood.The project included a theoretical component with a literature review, leading to preliminary theoretical framework or inventory framework of concepts that could be considered. The subsequent evaluation of the framework entailed a three-step progressive evaluation process namely 1) a theoretical exploratory case study, 2) interviews with industry experts and 3) an application of the framework on an industry-based case study. The following section reflects on the technology platform concept within the ecosystem perspective after which the methodology is discussed in section 3, the evaluation process is discussed in section 4, followed by the proposed framework in section 5.the notion of platforms refers to disparate things in marketing (product lines), software engineering (software families), economics , four different platform types have also been identified, namely transaction platforms, innovation platforms, integrated platforms and investment platformsThis research interprets a technology platform as a combination of innovation and transaction platforms and aims to draw from the synergism between the engineering and economic perspectives. Mindful that a platform can be embedded within other platforms, the platform framework proposed here presents a holistic understanding of platforms by integrating both perspectives in the analytical approach as well as acknowledging specific SSA health-related components into the framework.a network of interconnected organisations, organised around a focal firm or platform, which incorporates both production and use side participants”. A technology platform is therefore a central part of such an ecosystem and vice versa.To better understand the context of platforms in SSA healthcare, an ecosystems perspective was adopted, a construct that draws from natural ecosystems. This metaphor allows for a useful understanding of ecosystem behaviour and dynamics. It is referred to in management research , 24 and In the software industry, firms that are connected by a technological platform form a part of the software ecosystem (SECO). SECOs can be regarded as a subset of business ecosystems  and usuaThe governance of a platform ecosystem is central to its success and is part of the challenges platform owners face. It was therefore a design consideration for the framework developed in this research.Resourcing challenges including staff shortages and resource constraints, the absence of managers and supervision, insufficient information technology (IT) support, limited funds and infrastructure, power blackouts, digital illiteracy as well as financial, resource and usage sustainability , 39–41.IT infrastructure challenges comprising limited availability of internet connectivity in some areas, network stability concerns, the inconsistency of infrastructure across locations and infrastructure reliability , 39, 42.Existing or planned support structures such as the proposed National Health Insurance (NHI) to be implemented in SA, where interoperability challenges and compliance to industry standards are important , 42, 43.Data collection challenges including the lack of standardisation and interoperability incentives and the need for data quality control , 42, 43.Within the healthcare context, the uptake of platforms are enhanced by various enabling factors (enablers), but simultaneously face barriers to uptake. In general these enabling factors include, convenient to use data, expansion of digital networks, increased connectivity and advances in the Internet of Things (IoT) all contribute to the adoption of such platforms , 31. In Further work can be done to overcome these challenges in order for technology platforms in the SSA country context could reach its full potential. To tailor the proposed framework for use in the SSA health context, an understanding of the relevant ecosystem and environment is therefore essential.The objective of the research was to develop a framework for the design, development and implementation of technology platforms in the SSA health environment, mindful that the use of technology platforms to address health challenges in this context has not been researched extensively .A Grounded Theory-based approach was followed to develop the platform framework, using the Conceptual Framework Analysis (CFA) proposed by Jabareen  as a proWith reference to Part 1 as indicated in Table The next phase included choosing the final data sources to be used in the systematized review by assessing the search results against the inclusion criteriaThe process of identifying the primary papers is illustrated in Fig. The 26 articles identified were therefore analysed and data was extracted by following a 4-step iterative coding procedure developed by . The iteInsights obtained from the review directed the subsequent conceptual literature review viz. (1) key concepts related to this research, (2) the importance ranking of these concepts, (3) challenges facing platform owners, (4) the multi-disciplinary nature of the research, (5) the void of relevant research specifically for the African context, (6) different types of ecosystems and (7) typical ecosystem actors in a platform ecosystem.The platform owner is the firm responsible for the development of the software, maintaining the software and governing the ecosystem.The developers refer to the complementors or innovators who develop complementary products, services or technologies using the technology platform.The end-users are the final users of the applications, extensions or modules developed by the developers using the platform.The systematized literature review also highlighted the importance of three ecosystem actors, particularly the platform owner, the developers and the end-users:The ecosystem actors, their roles and how the key concepts relate to each of the ecosystem actors are shown in Table Subsequently, Part 2 of the process entailed the framework that was formulated . The ca“[to deliver] targeted stage-based health information to pregnant and postpartum women, [to] enable women to reach out with pressing questions, and [to] establish an important feedback loop to improve services [”.The investigation was conducted on a National Department of Health (NDoH) initiative - the MomConnect digital health platform. The MomConnect programme is a comprehensive digital health program, launched in SA in 2014. The objectives of the MomConnect platform are services ”.MomConnect case study was selected based on three main reasons: 1) The success and scale of the platform – it is one of very few platform initiatives at the time to achieve national scale, registering 500,000 women in its first year of operation which was more than 50% of the pregnant women served by the SA public sector; 2) The platform operational context was South Africa and 3) There was good data availability of the platform initiative to enable a case study based on secondary sources , 66.The case was thematically investigated with regard to its strategic management, the technology platform and architecture as well as its user-centric design approach. The findings were related to the three ecosystem levels of the framework, i.e. platform owners, developers and end-users. The various elements of the framework were tested against the case study to see where thy are present and where there were additional components that had to be added. From this preliminary evaluation it became evident that the inventory framework could be successfully applied to a developing country health platform. This provided a starting point for tailoring the inventory framework specifically to the SA health context.The application proved that the inventory framework could provide useful insight into the concepts a platform owner should consider in the design and management of a platform and its ecosystem. At the platform owner level, MomConnect could be linked to the strategy, architecture, governance structure, internal organisation and operations categories. Approximately all concepts within the first two categories could be confirmed to be present in the MomConnect platform. The developer level of the framework also applies to the platform owner. Factors regarding the entry barriers, ecosystem-related concepts, the architecture, support structures and methods of control of the MomConnect initiative were identified. As the platform involves multiple partners and stakeholders, there were concepts that related to an ecosystem perspective. The initiative also leveraged the innovative skills of public and academic partners and allowed them to share innovations. The third and final level of the inventory framework related to end users refers to the mothers, caretakers and the healthcare workers. The categories that could be applied to the MomConnect platform included the context of use, ensuring quality during app use, enabling user feedback, and considering the attractiveness of the app for end users.The theoretical insight obtained during the preliminary evaluation of the inventory framework, it also led to the reconstruction of the categorisation within each of the three levels See . The plaSemi-structured interviews were conducted to further validate the concepts of the framework. The nine participants included platform owners and developers as well as experts in health, ecosystem governance and technological innovation. The reason for the variety of interviewees was to obtain vast perspectives in this initial part of the validation process. Although this is admittedly a small sample size, the process was not a statistical one, but a process to gain insight into the core components of platform management and the applicability and validity of the framework in the platform and platform ecosystem context. The principle of data saturation was followed which settled on this number of interviews.Rabionet’s  intervieThe subsequent data analysis included three coding cycles, each with specific outcomes and conclusions, shown in Table The first cycle coding was conducted on paper and in MS Excel. The approach was to go through each interview’s data and to mark which of the concepts were validated. This was done for all the interviews independently. The interview data in MS Excel was formulated in such a way as to enable the recording of the amount of times each concept in the framework was mentioned or discussed by interviewees. By tabulating the concepts and sorting them in descending order, trends in popular concepts could be identified and interpreted.The second cycle of coding adopted five lenses derived from the notes and highlights of the first coding cycle. The aim of this cycle is for further refinement and investigation of any additional concepts that should be added to the framework. Five lenses were adopted for the second cycle coding: (1) health-related, (2) SSA considerations, (3) platform control, (4) support structures and (5) financing and pricing related aspects. The second cycle of coding also pursued the identification of voids in the framework, highlighting of disagreements and the identification of additional concepts to add to the framework. The five platform development parts and the five lenses formed the basis of identifying the voids and additional concepts to include in the framework. The qualitative analysis process considered the interviews against the framework for (1) confirmed topics, (2) voids and disagreements, (3) additional concepts and then (4) relating to the five lenses, if applicable.The third and final cycle of coding yielded themes, patterns and deeper insights into the data building on the outcomes of the previous two cycles. In the previous two cycles there were certain topics that featured continuously throughout the interviews. These were identified as trends and patterns that should be considered when designing, developing and implementing a technology platform in the SA health context.The third and final stage of the framework evaluation process included an in-depth industry case study on a platform-based firm in the SSA context, Mezzanine ware. The case study conducted in this research is classified as an explanatory case study. A detailed process for conducting case studies proposed by  was follData sources included the firm’s website, news articles, published material, organisational notes as well as interviews with five employees and the CEO.As with the previous two evaluation stages, results-based modifications and adaptations were made to the framework. Structural modifications included the renaming and re-categorisation of several categories and concepts throughout the framework, adding a feedback loop to the platform development dimension and a segmentation of the end-user level. The modifications of the framework included the addition of a combination of 26 concepts and tools related to both the ecosystem and platform development dimensions.The segmentation of the end-user level of the framework into two user-groups was a significant change. In the SSA health context, wide spread poverty and the digital divide means that the actual end-users of applications are often not well informed regarding the possibilities and impact of the technology and often cannot afford the application themselves –70. A clThe proposed framework for health-related platforms has four overarching aims, namely to 1) act as a practical and facilitating tool for platform owners; 2) account for each of the three ecosystem levels at the design stage; 3) highlight and address a number of challenges relating to each ecosystem level and 4) integrate the economic and engineering platforms perspectives into an overarching management tool.As shown in Fig. Dimension One) is to guide the platform owner regarding various issues to consider from the ecosystem perspective of the different groups to consider before embarking on designing a platform (See section 4.2). Three perspectives are included namely the platform owner, developer and end-user perspectives.The purpose of the ecosystem dimension . This second dimension also brings in specific aspects related to geography (SSA) and application industry . Dimension Two comprises of five parts, viz. 1) Establishing the platform core 2) The ecosystem and environment 3) The platform governance and design and 4) Managing and operation of the platform and ecosystem and 5) Evolution of the platform and ecosystem (See section 4.3).The platform type should be determined, i.e. transactional, innovation or integrated platform as defined previously.It should be established whether the platform firm functions as an internal or external platform. This specifically has an effect on the developer and end-user levels of the framework.The desired distribution channels and context(s) of operation should be identified.The application industry in which the platform will operate should be specified.During the framework development process, particularly the evaluation process, the importance of defining the platform characteristics became evident. Especially throughout the interview process, the authors realised that clearly defining the platform was an essential step to ensure that the user has the correct perspective when using the framework and understands his own point of reference within the larger platform definition. Four elements that a platform owner should establish regarding the platform under consideration were identified  were addressed during the evaluation phase of the framework.The category of ‘control’ has two subcategories, viz. rules and regulations and performance. Rules and regulations refer to concepts such as policies applicable to platform use or developer end-products, intellectual property rights of both the platform and developer complementary products, services or technologies , 29. It The final category developer-level category is ‘support’ and comprises community and platform support sub-categories. Support for all ecosystem actors has shown to be key in platform and ecosystem success. Firstly, a platform owner can motivate or facilitate external communities providing platform support . The plaClient group: Dedicated to the clients who typically act as intermediaries between the platform firm and a group of end-users. Pricing, value creation and the precise product or service specifications are some of the focus areas of the client.Actual end-users’ group: End-users of the products, services or technologies developed using the platform and usability, competition where user satisfaction and feedback are important.The third level of the framework refers to the platform ecosystem end-users and is shown in Fig. To illustrate the roles of the two groups, consider for example the case where the government of a SSA country identifies the need for a digital health tool in a government hospital. The hospital itself does not necessarily know of the benefits of such a tool and cannot pay for it, therefore the government acts as an intermediary.The end-user level may not always be completely applicable to platform owners. If the platform is an external platform firm, the platform owner may not have any effect on the end-users . HoweverTwo main categories, viz. technology and the proposition-related concepts, are relevant to the client group of the end-user level. ‘Technology’-related concepts include the desired application type and its envisaged use and establishing how the data gathered will be used and governed. The rules, regulations and standards related to the use-case should also be noted . The plaThe ‘proposition’ category relevant to the client group has three sub-categories which should all be understood prior to designing the end product, service or technology: financial, operational and evolution. Financial concepts refer to how economic value will be created and distributed between the client, actual end-users, developers and platform . The iniFinally, with regard to the ‘proposition’ category, there should be clarity regarding the evolution of the product, service or technology. Sustainability is one of the most important concepts, especially within the SSA context. The platform should be sustainable in terms of the technology itself, the financial considerations, the client and platform owner’s firms as well as sustained use .The evaluation of the framework suggested that the platform owner should consider the relevance and significance of the client in terms of its long-term vision. A ‘wrong’ client may result in scope creep or misaligning the firm with its vision and goals. However, the opposite may also be true. In the SSA health context, partnering with large and influential organisations may open numerous doors in future. Acknowledging that technology is constantly evolving, it follows that the end-product and service will also need to evolve. Hence, there should be clarity on the co-evolution between the client, the platform firm, the applications and the platform and whether the software may be re-used for other projects with different clients.The second group of end-users refer to the actual end-users of the products, services or technologies. This group is divided into three main categories, viz.according to the context of use, the operation and the interface considerations.Context of use includes organisational, physical, social and geographic contexts which may all have an effect on the design of the application , 86. UndThe operation category comprises deployment, feedback and privacy and security-related concepts. Deployment refers to the releasing of the application to the end-users and includes the infrastructure or setup costs, ensuring adoption, facilitating change management and providing deployment training and support if required . All theFeedback and privacy and security are vital, specifically in the SSA health context. User data should be collected and used to implement rapid updates if required. The data of all end-users should be protected and subjected to stringent data governance, as it will typically be sensitive and personal health data , 89.The final category of the end-user level refers to the interface of the application. The interface is divided into the usability and design considerations. The application developer should ensure the learnability and understandability of the application whilst meeting all user requirements . The intThis concludes the ecosystem dimension of the framework and the second dimension focuses on platform development.Establishing the platform coreThe ecosystem and environmentThe platform governance and designManaging and operation of the platform and ecosystemEvolution of the platform and ecosystem.The second dimension outlines typical platform development components and presents an interpretation of the concepts included in the ecosystem levels (Dimension One). This second dimension also incorporates specific aspects related to SSA and health. The ‘platform development’ dimension comprises of five parts, viz.The aim of Dimension TwoThe ‘platform core’ part refers to the ‘what’ and ‘why’ considerations and does not include any sub-elements and forms the core of the platform development.The ‘ecosystem and environment’ part refers to the ‘who’ and ‘where’ of platform development. It includes four general elements and three SSA specific health-related elements. Platform owners should carefully select their ecosystem partners and actively build the ecosystem based on this vision. Depending on the platform profile, the platform may form a part of more than one ecosystem. This can lead to embedded ecosystems, such as the ecosystem involved with a specific project, which is embedded within the larger platform ecosystem . This, in turn, may be embedded within a larger stakeholder ecosystem. The platform owner should be aware of the relevant ecosystems and the roles and responsibilities within each. A useful approach is to create personas for ecosystem actors to understand their roles, identify their potential for value creation, capture and delivery, relevant financial considerations and adoption mechanisms for each actor involved.Competition amongst platforms is a dynamic and complex landscape . Four poIn the SSA health context, a platform owner should be aware of the rules, regulations, protocols and regulatory authorities within the selected ecosystem and direct environment. In the health context, it is particularly important to build trust within the ecosystem. This may require partnering with local and trusted organisations and deliberate trust-building initiatives.The third part of the platform development dimension relates to the ‘design and governance’. It comprises three general elements and four elements related specifically to SSA health. Firstly, the platform owner should focus on defining the value creation logic. This may include clarifying the platform offering, establishing who will be the value-creating actors within the ecosystem and formulate a monetisation strategy to capture and fairly distribute the value. Secondly, some options for monetisation are included. The platform owner may choose to charge a subscription fee, to determine the price based on the project scope, to charge transaction fees, calculate the charges based on a percentage profit, implement credits for users or offer enhanced access at a greater cost. Other options include charging per user or per feature costs, based on the size of the customer base, licensing agreements, outsourcing certain functionalities or obtaining sponsorships for certain projects.The third element is specifically design-related. Mindful of the importance of being aware of the rules and regulations of the industry and operational environment, a collection of healthcare-related standards, rules and regulations should be considered and incorporated into the software and hardware during the design process. Popular approaches that surfaced during the literature reviews and evaluation process include designing a minimum viable product (MVP) and adopting the Service Oriented Architecture (SOA)  or agileThe fourth part of ‘platform development’ refers to the ‘management and operation’ of the platform and ecosystem and comprises of five general elements. A platform owner should clearly devise its market-entry strategy, as each application industry and context may have different requirements for success. In the USA, for example, health-related applications may be enforced by medical schemes or large businesses. A partnership with one of these could hence be the key to market entry. In Uganda, on the other hand, most people will not have access to or cannot afford medical aid and therefore a different strategy will be required. Transactional platforms (relating to economic perspective) also have to consider the chicken-or-egg-dilemma , referriA platform owner should carefully consider possible formal and informal control mechanisms , the difThe final general element of ‘managing and operation’ of the platform and ecosystem relates to the ecosystem health. Five possible components that should be monitored within the ecosystem include the health of the platform owner firm itself, the platform and its software and hardware, the software projects developed on the platform, the environment external to the platform ecosystem and the complex relationships within the platform ecosystem.Five SSA health-related elements have an impact on the platform development. It is recognised that users may not be aware of or be ill-informed regarding health-issues and the use of technology and may not have access to cutting edge technological devices. They will often have very basic mobile devices and may not be aware of the latest features of smart-devices. In addition, they may also face challenges regarding access mobile data, including availability and cost , 70, 98.These elements all affect the design process and the platform owner/developers need to be aware of the implications. Platform designers should therefore be mindful to design applications so as to reduce data traffic, as uploading and downloading speeds may be limited. In addition to the end-user context, the end-user her/himself should be considered to ensure initial and sustained adoption. Initiatives in SSA involving platforms may not go beyond the pilot stage as a result of decreasing usage or lack of funding.The fifth and final part of the platform development dimension refers to the ‘evolution of the platform and ecosystem’ and comprises ten considerations for evolution , the incorporation of feedback from the ecosystem and its use as sources for further development.The platform owner can also evaluate the success of balancing factors such as openness and modularity of its platform boundaries. Finally, the external environment should continuously be monitored for the proclamation of new legislation, protocols, standards or technologies.The proposed health-technology platform framework can be used as a tool to inform and aid platform owners in designing, developing and implementing healthcare-related platforms and resulting ecosystems, specifically in the SSA context. The tool was deliberately developed to integrate the economic and engineering platform perspectives and to be usable by different types of platforms. Subsequently, the platform framework is generalised and not all concepts and elements will be relevant for all platforms. The industry case study evaluation stage, confirmed the framework as a useful tool for platform owners.The framework and associated development tool can be useful in practice as well as a research instrument. Mindful that research frameworks and tools are often not practically usable by industry due to it being complicated and difficult to follow and relate to , 99, thiPre-use canvasOverview canvasPlatform Owner canvasDeveloper canvasEnd-user canvasPlatform Development canvasThe framework supplemented by additional information and insights into the SSA health context obtained from the evaluation stages, lead to the development of a practical management tool. The tool is comprises six canvasses, viz.These canvasses provide a practical approach and interpretation of this framework and was proven to be useful to platform owners during its evaluation stages. These canvasses can be accessed in the Addition files section of this article.A number of insights into the broader SSA health context are also worth mentioning. SSA as a developing area will require different design and management strategies that other developed countries . At the Whereas the framework can be useful, as was demonstrated in the case study, it will benefit from further improvement. Future work could include further evaluation and refining of the framework, particularly as more experience is gained through its practical use. As proposed, the framework is generalised for different types of platforms, therefore future work could also include refining the elements for each type of platform. The framework concepts are also not yet ranked based on importance or weightings. Some concepts have a higher importance than others and rankings for the different categories in the framework could prove useful in future. The framework can be developed further for different geographical regions and health systems.The platform framework lends itself to form the basis for a software or app implementation, either as a product or a service. This can be a promising avenue for further research given the demand for software-based products and services and the need to continuously revaluate, adapt and evolve.Additional file 1. Pre-use Canvas. This canvas aims to guide the platform owner through establishing the profile for his own platform. Four platform profile factors were found to influence the approach towards the framework: (1) the platform type, (2) whether the platform is an internal or external platform, (3) the platform distribution channels and (4) the application industry of the platform.Additional file 2. Overview Canvas. The Overview Canvas has three functions. Firstly, the focus of the Overview Canvas is to show how these two dimensions overlap and thereby give an overview of the framework content. The Overview Canvas therefore comprises the platform development parts as the rows and the ecosystem actors as the columns. At the intersection of the two dimensions, the canvas includes the relevant categories and subcategories from the Ecosystem Canvasses. These primary and secondary categories highlight important considerations at each respective intersection point. Secondly, the Overview Canvas acts as a reference guide by which the platform owner can navigate through the remainder of the framework. An example is illustrated in Figure 98: if the focus is specifically on the end user (column 3) and the platform and governance design part (row 3), the Overview Canvas can be used to guide the platform owner where to focus his attention within the framework canvasses for more information. Figure 98 indicates the intersection point (dotted red) on the Overview Canvas and how it refers the framework user to the correct ecosystem canvas categories. Thirdly, the Overview Canvas can also be used to understand platform design, development and implementation on a high level. The primary and secondary categories on this canvas were selected to be descriptive in order to provide understanding on a high level. By understanding the two dimensions and their intersection points, the platform owner can potentially develop his own, customised breakdown of these primary and secondary categories. The platform owner therefore does not have to be limited to the category breakdown given in the remainder of the framework. Following this Overview Canvas are the dimension one Ecosystem Canvasses.Additional file 3. Platform Owner Canvas. The Platform Owner Canvas aims to inform a platform owner what to consider regarding his own firm, platform and the ecosystem forming around its platform. The user of the canvas should approach it by putting on the ‘platform owner’s hat’. The Platform Owner Canvas comprises four main categories that have proven to be key in the design, development and implementation processes. The first category refers to the platform owner’s own firm and the design thereof. Within this category, the concepts were grouped according to their respective relations to the platform vision, the internal organisation and the operations within the firm. The platform vision includes concepts concerning the core of the platform, its purpose and future trajectory. The second category comprises the platform design with two subcategories. These two subcategories refer to the technology infrastructure and corresponding rules and regulations. Technology infrastructure specifically includes the technical and software considerations of the platform. Next, the platform ecosystem considerations relating to the platform’s ecosystem and its external environment are included. The external environment focus on competition and it emphasises the need to look outside of the platform and ecosystem for sustained success and evolution. The final category for this canvas includes the evolution of the platform. Subsequent to understanding of the platform owner’s key concepts, the Developer Canvas follows.Additional file 4. Developer Canvas. The platform owner needs to put on the ‘developer hat’ when using the Developer Canvas and understand what developers’ characteristics and needs are regarding the platform and ecosystem as shown in Figure 101. The developers refer to the actors that are developing the extensions or modules such as applications using the platform. As discussed in the Pre-use Canvas, the developers can either be internal or external to the firm. Key focus areas of developers include the platform and ecosystem entry barriers, how well the platform enables them to innovate, the availability of boundary resources, how open these boundaries are and the ability to provide feedback regarding the platform. The Developer Canvas is divided into five main categories that aim to provide a general understanding of what a platform owner should consider with regard to the developers using his platform. The first category refers to the entry barriers. The entry barriers are those factors that would either cause a developer to resist joining the platform or encourage them to join the platform. The entry barriers were categorised according to their relation to the platform technology, to how the platform firm is perceived (mission), how value will be configured within the ecosystem and what the platform ecosystem looks like. Subsequent to the entry barriers, are the general ecosystem considerations. These refer to how the platform owner should manage and govern the developers within the ecosystem. The final three categories refer to the technology, control and support. The technology infrastructure includes what should be enabled or considered regarding the developers. Fourthly, the canvas elaborates on the control the platform owner should have in place. This specifically refers to the rules and regulations and to informal and formal control mechanisms. The final category is developer support. The support provided to developers can be from external developer communities or through the platform and platform firm itself. The common purpose of all these categories is to enable and encourage developers to develop complementary products, services or technologies for end users.Additional file 5. End-user Canvas. The end users portrayed in the canvas comprise two components: (1) a client acting as an intermediary between the platform owner and (2) the actual user of the product, service or technology developed using the platform. The canvas is therefore split according to these two components. In the case of no client being present, the remainder of the canvas can still be used as normal. The focus areas of the client typically include the price of the initiative, how value will be created through it and whether their specifications are being met. The actual users of the products, services or technologies typically focus on its usability in their context, other similar products available, user satisfaction, its sustained adoption and enabling user feedback. The canvas layout includes dedicated sections for both of the client and actual end user respectively. The client component of the canvas is presented first and covers two main categories of interest. The first category refers to the technology requirements. This includes determining the requirements of the product, service or technology as well as its specifications. The second category refers to the suggested plan of action, specifically with regards to the financial considerations, the operation of the product, service or technology and its evolution. The categories for the actual end-user component include the context of use, operation of the product, service or technology and its user interface. Thoroughly investigating the context of use is crucial for success. The platform owner should be informed regarding all deployment-related activities, enabling and incorporating feedback and focus on complying with all privacy and security standards and protocols. These considerations cover the major operational factors with regards to the end users. The final category is the interfaces of the products, services or technologies. Detailed attention should be given to the usability and general design of the front end as this directly influences the success of adoption and the potential subsequent health-related improvements.Additional file 6. Platform Development Canvas. Platform Development Canvas comprises five parts: (1) platform core, (2) ecosystem and environment, (3) platform and governance design, (4) managing and operation and (5) evolution. The Platform Development Canvas’ layout includes the five parts of platform development, additional SA health considerations and relevant literature for each development part. The canvas has three overarching aims. The first aim of this canvas is to facilitate the development of a strategy for the platform design, development and implementation as the canvas guides the platform owner through the typical development parts. Secondly, where the Ecosystem Canvasses educate the platform owner on various topics, the Platform Development Canvas gives structure to their implementation. The final aim of this canvas is to inform on practical and actionable elements that draw from the Ecosystem Canvasses. In other words, it also provides possible interpretations of the dimension one canvasses. The Platform Development Canvas can also be used for software products developed on the software platform.


Inferring the locomotor behaviour of the last common ancestor (LCA) of humans and African apes is still a divisive issue. An African great-ape-like ancestor using knuckle-walking is still the most parsimonious hypothesis for the LCA, despite diverse conflicting lines of evidence. Crucial to this hypothesis is the role of the centrale in the hominoid wrist, since the fusion of this bone with the scaphoid is among the clearest morphological synapomorphies of African apes and hominins. However, the exact functional significance of this fusion remains unclear. We address this question by carrying out finite element simulations of the hominoid wrist during knuckle-walking by virtually generating fused and unfused morphologies in a sample of hominoids. Finite element analysis was applied to test the hypothesis that a fused scaphoid-centrale better withstands the loads derived from knuckle-walking. The results show that fused morphologies display lower stress values, hence supporting a biomechanical explanation for the fusion as a functional adaptation for knuckle-walking. This functional interpretation for the fusion contrasts with the current inferred positional behaviour of the earliest hominins, thus suggesting that this morphology was probably retained from an LCA that exhibited knuckle-walking as part of its locomotor repertoire and that was probably later exapted for other functions. This locomotor behaviour greatly contrasts with those observed in other African apes, which mainly exhibit diversified quadrupedal locomotor behaviours2. Using the extant great apes as analogues, several different locomotor modes have been advanced to characterise the ancestral condition prior to the adoption of the strict bipedal locomotion seen in the human lineage4. Among the ancestral proposed locomotor modes, knuckle-walking, a characteristic terrestrial quadrupedal locomotion exhibit by African apes, has played a central role. This is because it represents the most parsimonious of the alternative hypotheses since both Pan and Gorilla exhibit this locomotor behaviour. The knuckle-walking hypothesis states that the last common ancestor (LCA) of gorillas, chimpanzees and humans possessed this locomotor mode, whereas vertical climbing, a common behaviour observed in all of the extant apes, would be considered ancestral to knuckle-walking6. Nevertheless, both phyletic and functional analyses of the fossils of Ardipithecus ramidus suggest that hominin bipedality might have evolved from a locomotor mode that does not have a modern analogue among the great apes 9. In addition, some authors point out that knuckle-walking could have evolved independently in the African great apes, which would imply an homoplasic evolution of this locomotor behaviour in Gorilla and Pan11. Other studies have argued the opposite by pointing out that the observed differences in knuckle-walking between these two genera can be explained by differences in positional behaviour, kinematics, and the biomechanics of weight-bearing13, without implying two independent origins of knuckle-walking. Additionally, a recent re-assessment of the foot morphology of Ardipithecus ramidus suggests that the LCA probably exhibited an African ape-like locomotor repertoire involving terrestrial quadrupedalism and climbing14. Due to the importance of this matter, several studies have focused on the analysis of the hominoid wrist since it represents the key anatomical location that could help to elucidate whether the LCA was a knuckle-walker or not (for a summary see15).As noted by Darwin15. Despite being composed of numerous elements, the carpal bones work together to transfer loads between the hand and forearm, thus enabling the mobility of the hand in multiple planes16. Interestingly, among the scarce osteological synapomorphies of humans and African apes, the fusion of the os centrale to the scaphoid has been long recognised18. The scaphoid-centrale fusion in the African hominoid carpus has been interpreted as a functional adaptation to the stresses exerted on this joint during quadrupedal locomotion, particularly accentuated in knuckle-walking. The functional hypothesis has led to the suggestion that the fusion is evidence for a knuckle-walking common ancestor of the hominine clade6. In modern humans, the persistence of this feature has been interpreted as either a phylogenetic vestige19, or an exaptation to withstand the shear stress during power-grip positions20. Among other anthropoids, Pongo sometimes exhibits this feature, but only African apes and fossil and extant humans show this trait in almost all individuals18.Among mammals, the wrist is arguably one of the most complex joint systems, comprising around 15–17 bones, which are connected by at least 20 articulations, and bound together by several tendons and ligaments16, hence its importance when inferring the locomotor mode of the LCA21. This is especially important in African apes, because they do not have a weight-bearing articulation between the carpals and the ulna, so they have to use a hand posture in which ground reaction forces travel along metacarpals, carpals, and the radius21. This hypothesis has found some support in the convergent evolution of carpal fusion in other knuckle-walking species such as giant anteaters22, as well as chalicotheres17. However, it is also known that some lemurs, including suspensory sub-fossils such as Palaeopropithecus, also show the fusion of the os centrale24. This observation led some researchers to discard the knuckle-walking hypothesis for the os centrale fusion in the African hominoid clade25. Nonetheless, others consider that lemur wrist structure and function are sufficiently dissimilar to have evolved for different reasons5. For this reason, some argue that neither the functional nor the phylogenetic significance of scaphoid-centrale fusion are completely clear18, and that further analyses are required to establish whether this carpal fusion represents a significant functional adaptation. Fortunately, the functional virtual morphology toolkit allows us to generate fused and unfused morphologies to test this using a representative hominoid sample. Consequently, the present work uses finite element analysis (FEA) to assess whether the scaphoid-centrale fusion improves the transmission of forces between the manual rays and radius. If the fusion of the centrale to the scaphoid acts biomechanically to limit stresses as would be expected as an adaptation to knuckle-walking, then higher stresses should be expected in those specimens with an unfused centrale . However, it is important to keep in mind that functional homology does not necessarily imply structural homology . In this sense, if a functional explanation for the fusion that is incompatible with the current inferred positional behaviour of the earliest hominins is found , then this would suggest that the fused morphology was retained from a LCA that exhibited knuckle-walking as part of its locomotor repertoire, and that then was later exapted for other functions.Currently, the predominant functional hypothesis explaining the evolution of the fusion of the os centrale and the scaphoid considers that it decreases mobility and improves the ability to transmit forces between the manual rays and radius during knuckle-walkinghttp://dmm.pri.kyoto-u.ac.jp/dmm/WebGallery/index.html), whilst the human individual was downloaded from Morphosource (https://www.morphosource.org/)  where each specimen was segmented by applying a combination of case-specific thresholding values and manual painting techniques. We virtually generated fused and unfused morphologies of our entire sample depending on the species to compare biomechanical performance (further details about this process are provided in S2). The unfused morphologies comprised three bony elements  connected by the scaphocentralecapitate ligament, whereas the fused morphology involved the scaphoid  and capitate connected by the scaphocapitate ligament. The segmented models were then converted to CAD models and oriented with respect to the same plane to facilitate the comparison between them as shown in Fig. CT-scans of the wrists of adult individuals belonging to different hominoid species were obtained from Digital Morphology Museum, KUPRI . Elastic, linear, and homogeneous material properties were assumed for both capitate and scaphoid in the fused models and, capitate, centrale and scaphoid for the non-fused ones. The following mechanical properties were assumed for cortical bone (Young Modulus E = 10 GPa and Poisson’s ratio v = 0.22), cancellous bone (Young Modulus E = 0.5 GPa and Poisson’s ratio v = 0.3) and the cartilage that surrounds the bones (Young Modulus E = 7 MPa and Poisson’s ratio v = 0.3)28. The mesh of the analysed models ranged approximately between 1.5 and 3 million tetrahedral elements and 30,000–50,000 shell elements depending on the model (See S4 for further details).Shell elements were used to mesh the cartilage and cortical bone, whereas solid three-dimensional tetrahedral elements were used to mesh the cancellous bone. The shell elements defining the cortical bone and the solid elements defining the cancellous bone were connected using a multipoint constraint approach where the degrees of freedom of both types of elements are totally coupled. As shell elements, the thickness of the cartilage and the cortical bone were assumed to be constant Table . The bon16. The origins and the insertion points were distributed over an area by using multiple springs in parallel with each other. Fig. Linear spring elements were used to model the ligaments with their locations being estimated from previous anatomical studies29 for the palmar scaphocapitate carpal ligaments. The values of each spring in the model were set according to the parallel and serial distribution of the springs in the fused and non-fused cases   was defined as a non-separation contact which enables sliding on the plane of the contact and that does not allow a normal separation between bodies in the perpendicular direction.Fixed displacements were placed on the lower portion of the model in the areas of the scaphoid  and capitate where these bones meet the third metacarpal, the trapezoid and the trapezium Fig. . Lateral33. The obtained stress results for the scaphoid and capitate from the fused and non-fused models followed a normal distribution based on a Shapiro-Wilks test . Therefore, they were compared using Welch’s two sample t-tests in R version 3.5.134.We obtained the von Mises stress distribution in the carpal elements under the chosen loading conditions. The von Mises stress distribution was evaluated using their average values and presented using box-plots to display their stress distribution. This required the use of a quasi-ideal mesh (QIM), which is a non-uniform mesh , which in turn needed the use of recently proposed statistics that take into account this non-uniformity Additionally, simulations considering a force applied at 5° were also carried out to test if changing the direction of the applied force could have had an important impact in our results. The obtained results from this additional simulation set do not differ significantly from our main set of simulations . Further details about this additional simulation set can be found in S6, whereas the numerical results are provided in S7.The visual representation of the von Mises stress distributions is provided in Fig. The results presented here support the biomechanical aspect that is required to interpret the fusion of scaphoid and the centrale as a functional adaptation for knuckle-walking. The biomechanical results show that fused morphologies better withstand the simulated loading scenario as compared to the non-fused models. All fused morphologies  exhibited lower stress values when compared to the non-fused ones. Thus, these results show from a mechanical perspective that the fused morphology is better at withstanding the forces derived from knuckle-walking. When we virtually separated the centrale from the scaphoid, it seems that we removed a morphological portion of the bone that was necessary to better distribute the stresses derived from the applied external forces. Another possibility is that the lack of a cartilage layer could improve the force coupling, preventing the stress concentration that might be caused by the thin layer of dissimilar material. In any case, fused scaphoid-centrales show less stress as compared to unfused morphologies.35. We simplified the models by defining constant thickness for the cartilage and the bone. This is probably not the best ideal option, but the lack of available information did not allow us to generate more sophisticated models. We modelled the cartilage as a layer covering the whole body of the bone . This also represents an additional simplification because cartilage does not really cover the totality of the bone. Nonetheless, this simplification does not influence the stress results observed in the bone. In fact, since we are simply comparing the fused and unfused models from the same species with respect to each other, we would expect a minimal impact assuming all these limitations and simplification from a comparative point view.It is important to keep in mind some of the limitations of the present study that could influence our results. For instance, we used the same material properties of cancellous and cortical bone, cartilage and ligaments for all the studied species, and we also assumed homogeneity. These values were obtained from humans and applied to all the models because there is no available information of these values for the other analysed apes. Moreover, the use of homogeneous material properties for the bone is also widely accepted in the community, especially when modelling carpal bones since there is no accurate published information available for all the analysed species36. Our obtained results are consistent with this interpretation, since they show that the scaphoid-centrale fusion plays a role in reducing the experienced loads during knuckle-walking, which suggests that high loads due to quadrupedal locomotion were indeed a problem and a skeletal trait that contributes to better withstand the mechanical loads from knuckle-walking would therefore be adaptive. This result also provides some functional support for the hypothesis that considers the LCA as a knuckle-walker, although, of course, it does not prove it. As mentioned before, it is important to keep in mind that functional homology does not necessarily imply structural homology . However, the fact that the functional explanation for the scaphoid-centrale fusion contrasts with the inferred positional behaviour of the earliest hominins, thus suggests that this morphology was probably retained from an LCA that exhibited knuckle-walking as part of its locomotor repertoire and that was later exapted for other functions.It has been argued that knuckle walking was adopted by the African apes as a way to ameliorate the consequences of repetitive impact loadings on both soft and hard tissues of the forelimb via isometric and/or eccentric contraction of the antebrachial muscles during terrestrial locomotion37 that consider the scaphoid-centrale fusion as a functional adaptation to better resist weight-bearing stresses and increase the stability of the hand in terrestrial quadrupedalism. This interpretation is in agreement with other traits shared between African apes and humans, such as robust metacarpals and phalanges and long middle phalanges relative to proximal phalanges, which might also represent knuckle-walking adaptations. In addition, other studies that focused on ligaments and kinematics have also shown some support to the hypothesis that the scaphoid-centrale fusion contributes to a more rigid mid-carpus in the African apes in a way that may stabilises the wrist during knuckle-walking16. This work is also concordant with previous morphological studies, which have suggested that several radial traits in the African apes are involved in stabilizing the wrist in extension during knuckle-walking6. The obtained results in our study are also consistent with a recently published study that analysed the oldest-known fossil foot (4.4 myr) attributed to Ardipithecus ramidus14. This study of the foot used evolutionary models to assess the relationship between tarsal proportions and the locomotor behaviour of both apes and monkeys and suggests that hominins evolved from an ancestor that had a foot similar to the African apes, thus suggesting an LCA with an African ape-like foot adapted to terrestrial plantigrade quadrupedalism and some climbing14.Consequently, the biomechanical results obtained here are consistent with more classic interpretations11, great ape locomotor biomechanics2, as well as the current functional interpretation of Ardipithecus ramidus anatomy9 do not favour a knuckle-walking LCA, but rather the homoplasic evolution of this behaviour in chimpanzees and gorillas (but see14 for opposite opinions). In addition, another possible interpretation for the retention of scaphoid-centrale fusion in the bipedal hominin lineage might be attributable to exaptation, rather than phylogenetic legacy, as stresses in the wrist from activities such as tool making, or tool use might have been substantial. For example, it seems that in Oldowan knapping the highest forces are reported to be transmitted through the digits 2 and 3, hence likely onto the capitate. Whether stone tool behaviours could have led to the retention of the scaphoid-centrale fusion requires further investigation.Nevertheless, it is important to consider that this conclusion would also require the explanation of diverse conflicting lines of evidence and opposing interpretations of the available data. For instance, it has been strongly argued that some aspects of the hominoid carpus morphology38. Fossil evidence linking the origins of knuckle-walking with the appearance of scaphoid-centrale fusion would be able to clarify the adaptive significance of this trait. In addition, further biomechanical models and experimental data on this issue can also contribute in elucidating the role of the scaphoid-centrale fusion. For example, by analysing unrelated taxa  and exploring the functional interpretations of fused and non-fused wrist bones within different phylogenetic and locomotor contexts, we should be able to further clarify the functional role of this trait. Finally, it is important to keep in mind that extant knuckle-walkers show diverse positional behaviors, and that knuckle-walking does not preclude climbing or exclude the possible importance of arboreality in the evolution of bipedalism in our lineage.Consequently, the functionally adaptive nature of the scaphoid-centrale fusion has to be shown at different levels to be fully corroborated, since the present paper exclusively shows its functional roleSupplementary information.


In order to solve the problem of how to quickly and accurately obtain crop images during crop growth monitoring, this paper proposes a deep compressed sensing image reconstruction method based on a multi-feature residual network. In this method, the initial reconstructed image obtained by linear mapping is input to a multi-feature residual reconstruction network, and multi-scale convolution is used to autonomously learn different features of the crop image to realize deep reconstruction of the image, and complete the inverse solution of compressed sensing. Compared with traditional image reconstruction methods, the deep learning-based method relaxes the assumptions about the sparsity of the original crop image and converts multiple iterations into deep neural network calculations to obtain higher accuracy. The experimental results show that the compressed sensing image reconstruction method based on the multi-feature residual network proposed in this paper can improve the quality of crop image reconstruction. Crops will inevitably be affected by diseases, insects, soil conditions, climate and other factors during the growth process. Realizing the monitoring of crop growth is not only an important means for constructing agricultural information, but it can also improve bad factors in time. The image is a direct means to perceive and analyze the growth situation of crops. In addition to analyzing the growth changes of leaves and rhizomes of crops, it can also determine the maturity of crops. Accurate image acquisition is the prerequisite for image processing and analysis.The image acquisition task needs to be completed by the wireless sensor network node, whose main feature is to rely on battery power supply and limited energy. In the transmission and storage of large data images, it will face problems such as resource constraints, which will easily lead to a short life cycle of the node. Therefore, how to ensure the quality and quantity of image information acquisition in an environment with limited energy and resources has become a problem that needs to be solved urgently. In short, in order to make the data collection of sensor nodes achieve the effects of greatly reducing the amount of data and network energy consumption, effective information compression has become the focus of research.In 2006, Donoho et al. ,2 proposThe reconstruction problem is one of the research focuses in the field of CS. Since CS image reconstruction is the prerequisite for accurate judgment and analysis, our article mainly explores its compressed sensing image reconstruction in depth. Traditional compressed sensing systems usually use convex optimization or iterative algorithms for signal recovery under the premise of sparse signal. For crop images whose background environment are more complicated, however, they do not accurately meet the sparsity in the transform domain, and it takes a long time to solve the optimization problem based on iterative solutions, making it difficult to process image information quickly.In recent years, deep learning has developed rapidly in various fields and has been widely used. It has achieved significant performance improvements in many traditional signal representation and recognition tasks, showing its ability to handle complex recognition tasks. Introducing deep learning technology into CS image reconstruction provides a better solution to the problems of traditional CS reconstruction with high time-consuming and low image reconstruction accuracy when the measurement rate is low. Deep learning uses a large amount of data and data labels, namely compressed images and original images, to learn the structural characteristics of crop image information adaptively; meanwhile, it converts the traditional measurement and reconstruction process into an end-to-end mapping network, reducing network complexity and measurement parameters. With the rapid development of the Internet and the advent of the era of big data, highly parallel graphics processing unit (GPU) and massive amounts of data ensure network computing time and image quality.DeepCodec  learns aBased on the existing algorithms, we proposes a compressed sensing image reconstruction method based on a multi-feature residual network that uses multi-scale convolution to obtain different feature information of crop images. The residual block can solve the problem of deep neural network degradation well, avoiding the gradient dispersion problem caused by the deepening of the network. The multi-feature extraction of the image can capture more different image details, so that the image information is more completely retained, and the image reconstruction ability of the network is improved.In summary, this paper studies the problem of image acquisition in the process of crop growth monitoring, and researches the inverse solution of compressed sensing to achieve higher quality reconstruction of crop images. On the one hand, it provides a reliable basis for the next image analysis and other processing. During the monitoring of the growth process of crops, problems such as withering of branches and leaves, falling of fruits, moth eaten etc. are discovered as soon as possible; thereby permitting timely harvesting of fruits when they are ripe. On the other hand, in the traceability of agricultural products, it provides real and effective image display to realize the visual presentation of its growth process. With a small amount of data, low energy consumption and high speed of transmission, CS sampling extends the life of sensor nodes, allowing them to monitor crop growth for a longer time; the CS reconstruction algorithm based on deep learning uses massive data to learn image features autonomously, which can speed up the reconstruction process. The experimental results show that compressed sensing image reconstruction based on multi-feature residual network (MRNet) proposed in our paper can effectively improve the accuracy of crop image reconstruction, indicating that the multi-feature extraction of images has a good effect on improving the quality of reconstructed images. It can promote the application of wireless sensor networks (WSNs) in crop growth monitoring, accelerate the development of intelligent Internet of Things and improve the construction of agricultural informatization.x is an N × 1 sparse signal that has only k nonzero values, and then we can recover x from a set of under sampled linear measurements y = Φx (y ∈ MR), the Φ denotes the random measurement matrix .The measured value containing the original image information is obtained by the measurement matrix, and then the original image can be obtained by the reconstruction algorithm. We suppose that x does not satisfy sparseness, it needs to be sparsely expressed on the sparse basis; let x = Ψs, Ψ∈ N×NR is the sparse basis matrix, and s is the sparse coefficient. The mathematical expression of compressed sensing is shown in Equation (1), and the schematic diagram is shown in However, since the general natural signal Among them, the sparse signal measurement matrix Φ must meet the restricted isometry property (RIP) ,16 in puε is a constant approaching 0. Since the solution of Equation (2) is a NP-hard problem, it cannot be solved accurately; what we can do is make the estimated value approach the true value indefinitely. The traditional compressed sensing reconstruction algorithm mainly includes the following three categories:Convex optimization algorithm: uses Greedy tracking algorithm: selects the local optimal solution through iterations to approximate the original signal, for example, by using the subspace tracking algorithm (SP) ,18.Nonconvex optimization algorithm: such as the Bayesian compressed sensing algorithm (BCS), based on statistics, the prior probability density distribution function of the signal is obtained from the prior knowledge. Then, the maximum posterior probability is used to estimate the error range of the reconstructed value and finally reconstruct the original signal.The essence of the compressed sensing image reconstruction problem is to solve an non-deterministic polynomial (NP-hard) problem, which can be achieved by:The reconstruction method based on deep learning uses a large amount of data and data labels, namely compressed images and original images, by continuously adjusting network weights adaptively and offsets to learn the structural characteristics of crop image information, and how to use the data structure to accelerate the reconstruction process. The reconstruction steps are as follows:Step 1: Data preparation.Load the dataset and preprocess the image, and then construct a measurement matrix for compressed sensing sampling to obtain a compressed crop image. Correspond this to the initial crop image and the compressed image to obtain data and data labels.Step 2: Input data and labels to reconstruct the network.Input the data and labels to the reconstruct the network and update the network parameters, and dynamically adjust the learning rate through the optimizer, thereby minimizing the loss function.Step 3: Test.When the training end condition is reached, save the network parameters, load the test image into the trained reconstruction network, calculate the peak signal to noise ratio between the reconstruction and the original image to evaluate the image quality, and then end the training.To address the problem of how to quickly and accurately obtain crop images during crop growth monitoring, this paper proposes a compressed sensing image reconstruction algorithm based on a multi-feature residual network. We use this fully connected to form a linear mapping network, and use multi-scale convolution to achieve multi-feature extraction of images, so that the reconstruction network can make full use of the structural features of crop image information, and train network parameters, aiming to improve the quality of reconstructed images by multi-feature fusion.Before the data are transferred to the reconstruction network, data preprocessing is needed. The implementation process is shown in x, x′, xmax, and xmin represent the original pixel value, the normalized pixel value, the maximum pixel value, and minimum pixel value, respectively.First, for the convenience of subsequent data processing and to ensure the convergence speed of the model during operation, the original image is normalized. The mathematical model is shown in Equation (3):x of N = n2 dimension, which can effectively avoid the problem of excessive data in the subsequent initial reconstruction process, reduce the number of network parameters, and speed up the training process. Set the sampling rate MR, get the compressed image dimension M = N × MR, and then we can generate a random Gaussian matrix of  and orthogonalize its vector to get the measurement matrix. Use the measurement matrix to sample x for compressed sensing to obtain the corresponding measurement value y.Secondly, divide all training set images into n × n subimage blocks and vectorize them to obtain the signal x = Ay, where A ∈ RM×N is a linear mapping matrix, although the equation belongs to the overdetermined equation without an exact solution, we can estimate a mapping matrix A’ to approach A infinitely. Therefore, input the compressed image to the linear mapping network to obtain the initial reconstructed image u, w, b, ubH(u), f represent the feature vector of image information, weight vector, biases, output of fully connected layer, and activation function, respectively.Since the mapping from the measurement vector y to the original signal x can be regarded as an approximately linear mapping, The agricultural environment is usually more complex, and the acquired images often have complex backgrounds such as uneven lighting. The extraction and analysis of the texture features of the images can be used as an important basis for evaluating the growth status of crops. Therefore, in this paper, convolution kernels of different scales are used to convolve the image separately to capture more different details of image feature information, so that the image information is more completely retained, and the image reconstruction ability of the network is improved.x to the function F(·), we can obtain an initial reconstructed image x*. The specific mathematical model is shown in Equation (5). The compressed sensing image reconstruction model based on the multi-feature residual network is shown in W1 is the weight matrix in the linear mapping network and W2 represents the weight matrix in the multi-feature residual network.The linear mapping network is recorded as the function F(·). According to the analysis described above, with input the original image In the multi-feature residual network, in order to maintain the dimension of the image feature information, the network does not contain a pooling layer, only the convolution layer and the activation function. The “same” setting is performed during convolution. In this paper, we choose the rectified linear unit (ReLU) as our activation function. The value of ReLU in the negative interval is 0, and the value in the non-negative interval is constant. Therefore, there is no problem of gradient disappearance when the network parameters are back propagated, so it is convenient to use the back propagation algorithm in deep artificial neural network training. At the same time, it can ensure that the convergence speed of the network model is maintained in a relatively stable state.In our paper, the experiment is implemented in Intel(R) Core(TM) i5-6200U CPU @2.30GHz of Lenovo laptop which was made in Beijing, China, Windows 10 operating system, and the simulation software is PyCharm which is developed by JetBrains in Prague, Czech Republic. In order to verify the effectiveness of the proposed multi-feature residual network model in solving crop image reconstruction problems, the same settings were used in the deep learning model training to compare the reconstruction effects of the test images.N represents the total number of samples, iy represents the i-th true value, and i)f as the loss function of learning and training. Its mathematical model is shown in Equation (6):MSE is the expected value of the square of the difference between the estimated value of the image and the true value of the image. It can evaluate the similarity between the reconstructed image and the original image. In a certain sense, the smaller the value of MSE, the higher the quality of the reconstructed image. Therefore, the Adam optimizer is used to update and calculate the network parameters to minimize the loss function.For image reconstruction algorithms, the quality and similarity of the reconstructed image is a key evaluation factor for the pros and cons of the network model. We select peak signal to noise ratio (PSNR) and SSIM to quantitatively analyze the quality of the reconstructed image. A larger PSNR indicates a smaller image distortion. SSIM measures the similarity between the reconstructed image and the original image. If SSIM equals 1, the two images are identical.In summary, the specific implementation steps and parameter settings of the method are shown in In view of the characteristics of crop images, such as complex image environment, the model proposed in this paper uses multi-scale convolution to extract more feature information. In practical applications, crop images obtained by WSNs should be selected for targeted training to make it more suitable for a single field. In order to verify the universality and effectiveness of the model, this paper selects the universal dataset Set91 , which cThe parameter selection in this paper has a certain universality. The four images in the experiment use the same set of parameters, and this set of parameters can also be extended to the reconstruction of other crop images. Through a comparison between PSNR and SSIM, we find that the large PSNR value of the image does not mean that the SSIM is necessarily high, and its value can only represent the image quality to a certain extent. There are two main goals in this study of image reconstruction: one is to analyze using images whether the crops are growing in good condition and the other is to achieve the visual presentation of the crop growth process. Therefore, objective and subjective evaluation criteria are required to jointly evaluate the image quality. During the experiment, it was found that inputting images of different sizes into the network can acquire different PSNR and human visual perception. As shown in This paper proposes a deep compressed sensing image reconstruction method based on a multi-feature residual network. By continuously adaptively adjusting the network parameters, and adaptively learning the structural characteristics of the image, the assumptions of the original signal sparseness of the CS theory are relaxed; converting the traditional measurement and reconstruction process into an end-to-end mapping network greatly reduces the image reconstruction operation time, that is, using a small amount of data to accurately reconstruct crop image information in a short time. Experimental results show that the method proposed in this paper offers a good reconstruction effect on the test image and can obtain high-quality reconstructed images. The future research work is to realize the reconstruction of crop images in the color space, perform image processing analysis while monitoring the growth situation of crops, and predict the development status of crops.Guiling Sun, Ruili Nan, Zhihong Wang, Shijie Wang. Research on Image Reconstruction of Compressed Sensing Based on Multi-feature Residual Network. China. 2020105099841, 8 June 2020.


Technology has influenced every aspect of our living, and education is not anexception. During the current pandemic period of COVID-19, the latent motive ofmaintaining social distancing is leading to be one of the prime reasons for thestudents to get enrolled in online courses. Although the benefits of e-learninghave been discussed in various previous studies, it is important to understandthe quality of e-learning and the satisfaction level of learners during thisforceful shift toward e-learning amid the pandemic of COVID-19. This researchproposes a conceptual model for understanding the variables influencinge-learning quality (ELQ) and learner satisfaction under the moderating effect ofmaintaining social distancing. The model is empirically validated by means ofthe partial least square approach through structural equation modeling based on435 responses of university students in India. The results suggest thatassurance, reliability, responsiveness, and website content are the factors thatinfluence the ELQ of the online courses during the pandemic. ELQ also stronglyinfluences the learner’s satisfaction. Interestingly, perceived benefits ofmaintaining social distancing have a significant negative moderating effect onlybetween empathy and ELQ, which leads to the satisfaction of the learners. E-learning refers to learning via the Internet, providing learners with a flexible andpersonalized platform to learn. It can be referred to be an innovative approach for anexcellent provision of educational services to the learners through electronicinformation, aiming for continuous enhancement of their knowledge, skills, and otheroutcomes . It offeUniversities and higher education institutions, as the providers of the educationalservice, are striving hard to satisfy their customers, that is, the learners, throughvarious students’ centric strategies and offerings . E-learnQuality of an object has been defined as the “fitness for use” , pp. 15,Till now enough studies are undertaken to investigate the quality of e-learning,especially in the context of the developed world. But there are not many studiesfocusing on validating the developed world studies’ outcomes to the learners of theIndian sub-continent. Moreover, in the present COVID-19 times, the influence ofmaintaining social distancing, perceived harm of being on campus, and instead of takingonline classes under lockdown may have altogether different implications on the qualityof learning and learners’ perception of satisfaction thereto. Thus, the aim of thepresent study is to test the proposed hypothesized model using the partial least squarestructural equation modeling (PLS-SEM) technique to assess the impact of variouse-learning factors under the moderating perceived impact of maintaining socialdistancing on the ELQ and its subsequent impact on the student satisfaction.Although the benefits of e-learning have been widely discussed in various previousstudies, it is more critical now to better understand the satisfaction level ofe-learners, especially as maintaining social distancing has become a new norm duringthis pandemic period. E-Learning is the delivery of education or training usingelectronic means or information technology to access the educational curriculumoutside of a traditional classroom . Online The SERVQUAL scale has been used in past to measure the service quality in variousservice industries such as banking , hospitaThe quality of e-learning may be understood better by various underlying theories andprinciples, including cognitive theory of multimedia learning, social cognitivetheory, and information systems continuance model. The cognitive theory ofmultimedia learning  establisBased on the appraisal of previous significant studies and theories as discussedearlier, the researchers propose and empirically test a theoretical model see thatconReliability is the ability to perform the promised servicedependably and accurately  and ELQ is moderated by the perceived benefitsof maintaining social distance.Various studies have found that during outbreaks of the pandemic, human behaviorchanges, such as maintaining social distancing, can have a significant effect onits spread . Koo et The data are collected through a structured questionnaire obtaining responses of435 undergraduate and graduate management students in India. Data collection for this study is conducted using a questionnaire with5-point Likert scales. An online version of the questionnaire was sent to theundergraduate and postgraduate students, accompanied by a cover letter. The datawere collected through snowball sampling within our network and asked ournetwork to forward it further. The questionnaire was shared with students in anonline class in English. A conceptual model framework is proposed forunderstanding the relationship between ELQ and learners’ satisfaction moderatedby perceived benefits of maintaining social distancing (PBMSD). Based on theproposed research framework as shown in Based on the demographic information in The values of composite reliability, the average variance extracted (AVE), andCronbach’s alpha values are as shown in Further, the Fornell–Lacker criterion is used to assess discriminant validity.This method compares the square root of the AVE with the correlation of latentconstructs . The valHeterotrait-Monotrait ratio criterion is also used to check the discriminantvalidity. From the results of the study, the values (in bold) in R2 and standardized rootmean square residual value is considered as the primary way to evaluate theexplanatory power of the model , Reliability , Responsiveness , and Website Content , have a significant positive effect on ELQ, whereasthe empathy and learning content does not have a significant effect on ELQ.Further, ELQ , has a strong positiverelationship with the learner’s satisfaction as shown in R2 value of ELQ and learner’s satisfaction is.53 and .017, respectively. The path coefficient values and outer loadings ofthe item along with R2 values are shown in The standardized beta values (β) of path coefficients are computed by using thePLS algorithm function technique called bootstrapping  in Smartp < .05). This implies that high PBMSD cansignificantly reduce the effect of empathy on ELQ. PBMSD does not moderate theeffect of any other variable on ELQ. Hence, the results confirm the acceptanceof only one moderating hypothesis (H8b) and rejecting all other hypotheses. Theempathy from faculty and staff of the educational institute during this periodof the pandemic will not help students to enhance their learning andsatisfaction rather it will reduce their satisfaction.PLS-SEM bootstrapping procedure empirically measured the moderating effect ofPBMSD on the relationship between various factors and ELQ. The bootstrappingresults in COVID-19 pandemic has disrupted almost all industries around the world, and theeducation sector is not an exception to it. Even continuing education during thepandemic, when social distancing norm is the only solution to slow down the spread,was a serious concern for all the educational institutes and learners. Most of theinstitutes, including schools and higher education, shifted toward online learning.Online learning is the best alternative available for continuing education. However,affordability, that is, inability to purchase electronic gadgets such as laptop,mobile, and pay for data, and so forth, and availability, that is, of internetconnection and requisite infrastructure, is a matter of discussion among educatorsand policy makers. As the shift toward online education was sudden and somewhatforced, the quality of learning must not be compromised.The study was aimed to check the influence of various factors of the SERVQUAL scale,the most common scale to assess the service quality and besides, other factors thatare relevant to online learning particularly. As this online education is necessaryto avoid COVID-19 spread on campuses, it is important to understand how studentsperceive the benefits of maintaining social distancing and its moderating effect onthe various factors of ELQ. The factors such as assurance, reliability,responsiveness, and website content were found to be having a positive significantimpact on ELQ, confirming previous similar investigations  and,in turn, found to be having a strong relationship with learners’ satisfaction. Theassurance factor explains that learners have the belief that their universityadministration and faculty are working hard, and they are assured they will get aquality education. Empathy toward learners during the pandemic in the online setupwill not enhance the quality of learning. The reason may be that students expectuniversities to provide education for which they actually paid for not the empathy.Moreover, the interface is mostly impersonal in nature. Reliability is an importantfactor for students as they rely on their career and job prospects on universityeducation and the same factor is true for online learning. The responsivenessvariable may hold much importance during online education as students andinstructors are placed in remote locations. The responsiveness of instructors andadministration will help to enhance the quality of learning in the onlineenvironment during the time when learners are frustrated and need technical support.The learning content may not hold much importance in the immediate concern of thestudents, as they are struggling to cope up with the new learning setup and mediumof learning and are more concerned about effective and nondisruptive utilization.Learners may feel a sense of frustration because of the lockdown, and sudden shiftstoward this learning and the content of learning may be secondary to the quality oflearning. The website content of educational institutes must be easy to navigate andprovide relevant information during the pandemic as it is the only interface betweenthe learner and institute at the time of the pandemic. The relevant information,learning material, and easiness to navigate will improve the quality of e-learningand enhance student satisfaction. The ELQ strongly influences learner satisfactionwhich means the quality of learning will enhance student satisfaction which isimportant in online learning during this sudden shift.The moderating effect of PBMSD has been concluded to be significant only between“empathy” and ELQ. The learners acknowledge the perceived benefits of maintainingsocial distance and a high perception of maintaining social benefits will highlyinfluence the effect of empathy on the ELQ. The prominence of the “empathy”attributes is justifiable pertaining to the impact of the current pandemic of thepsychological state and behavior of the individuals . COVID-1The present study has noteworthy implications and benefits for the subject areaas it has been able to provide and validate a broad framework for the qualityand satisfaction of e-learning, especially in the context of the new normal dueto the COVID-19 pandemic. This is one of the first research in the area ofstudying the students’ e-learning in the changed new normal of a COVID-19pandemic. Therefore, this study contributed to the literature by developing aframework in response to the COVID-19 pandemic. The study reconfirms the role ofELQ attributes, that is, assurance, reliability, empathy, responsiveness,website content, and learning content toward the satisfaction of e-learners,during the crisis as well. The discovered moderating role of maintaining socialdistancing on the relationship between “empathy” and ELQ posits a great case forfurther study and theory development. Empathy helps us in recognizing, sharing,and reacting to the emotions of others. Empathy is essential in taking theperspective of the other person’s mental life . CognitiAlong with the academic implications, the present research also has noteworthypractical implications. Particularly, the current study is vital for the highereducation institutions to start or review their e-learning offerings during thepresent current COVID-19 pandemic times explicitly triggering a paradigm shiftin the world of learning and education. The positive change is inevitable, andthe study outcomes may be used to establish better systems not only for thepandemic period but also for future times. E-learning or blended learning arethe areas to be explored further by the learning solution providers. Theestablished names in the physical education got to prove their metal in this newplayfield by taking cues from the findings of this and related studies, whereassmaller players have got a level playing chance and a golden opportunity toestablish themselves as the leaders of the learning and education industry.Another critical present-day concern for governments, policy makers, andeducation service providers is to understand the antecedents to the e-learningand their relationship with learning satisfaction and formulate the relevantstrategies in accordance with these findings. The significant moderating effectof PBMSD between 'empathy' and ELQ calls for immediate action toward theprovision of empathetic service solutions for effective delivery of e-learningand larger satisfaction of the e-learners.With the onslaught of COVID-19, it has become difficult to teach students throughtraditional classrooms. The students are compelled to enroll in online courses.During this challenging time period, the present study has given key quality factorsof e-learning that can be improved by the e-learning service providers,institutions, and organizers. The path analysis with a structured equation modelverified that ELQ relates to learner satisfaction. The results of this suggest thatELQ is positively influenced by the e-learning variables viz., assurance,responsiveness, reliability, and website content. The ELQ is the construct thatstrongly influences the learners’ satisfaction. The PBMSD only moderate therelationship between empathy and ELQ. With the progress of online education programsand improvement in quality factors, we believe e-learning will have a very brightfuture among young millennials.