![]() The work carried out explored the technological and methodological choices for designing and deploying on a large scale a mobile application promoting the gathering of georeferenced farmsourcing observations. They demonstrated how an approach like this could be used to promote participation in farmsourcing projects. ![]() This case study is the monitoring of the vine water status at regional scale using i) an indicator (iG-Apex) based on observations of vine shoot growth and ii) the development of a dedicated farmsourcing application (ApeX-Vigne).įirstly, the work demonstrated the value of a simple but noisy approach, such as the one based iG-Apex, for characterising an agronomic variable of interest (in this case, the vine water status) at the field and intra-field levels in a decision support context. The objective of this thesis is to propose tools and methods to develop a farmsourcing approach in both the design and the evaluation of the project (How to foster the contribution of participants? How to evaluate the success of a project?) and then in the characterisation of the quality of the resulting observations (How to identify outliers and surprising observations? How can these approaches be automated?) The thesis is based on a systemic approach with the implementation of a case study. To date, there is no existing approach taking into account the specificities of farmsourcing projects. Finally, they influence the methods for identifying outliers and surprising observations in corresponding datasets. They also influence the criteria and indicators for evaluating the success of such projects. These specificities of farmsourcing projects influence the design of the projects and the involvement of the different stakeholders. These crowdsourcing projects in agriculture have specificities in terms of participants (professional contributors, importance of the role of advisors), studied phenomena (with strong spatial and temporal covariances) and datasets collected (asynchronous and heterotopic) that have led some authors to coin the concept of farmsourcing to describe them. diseases, pests or abiotic stresses monitoring). To date, crowdsourcing is not widely spread in agriculture, but it has great potential for collecting georeferenced observations to monitor phenomena at regional scale (e.g. Based on the findings as well as derived knowledge, we also suggest some new open opportunities and challenges that can be explored by the research community, including app development, deployment, delivery, revenue, etc.Ĭrowdsourcing is an approach consisting in answering a question defined by an organisation (research laboratory, company, etc.) by relying on the collective intelligence of a community of contributors. We explore multiple aspects of such behavioral data and present patterns of app usage. ![]() The dataset of Wandoujia service profiles consists of two kinds of user behavioral data from using 0.28 million free Android apps, including (1) app management activities (i.e., downloading, updating, and uninstalling apps) from over 17 million unique users and (2) app network usage from over 6 million unique users. This article presents an empirical study of behavioral service profiles collected from millions of users whose devices are deployed with Wandoujia, a leading Android app store service in China. Supporting mobility has become a promising trend in software engineering research. The prevalence of smart mobile devices has promoted the popularity of mobile applications (a.k.a.
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