This project MOBITER (“MOBIlité autonome en milieu tout TERrain”) aims to fully meet the ambitions of the MOBILEX challenge. For this, 2 SMEs (Sherpa Engineering / Logiroad) join their academic partners: TSCF INRAe, and Institut Pascal, confirming recent collaborations (Thesis, common laboratory, geographical proximity). This proximity allows to have already common links in the methodology of development (recourse to numerical models), tools (use of the middleware ROS), techniques of representation of the environment (Lambda-field) ... which will be necessary for the framework of this very applicative project, requiring a demonstration in the first year. The contributions are as follows: - Sherpa Engineering, coordinator of the project, will realize (on the basis of an existing), the hardware realization of a perception platform, totally adapted to the requirements, and to the specificity of the challenge. He will carry out the engineering tasks of the project, and will be in charge of a part of the algorithm. - INRAE will bring its experience in agricultural robotics, and will be responsible for the experimentation thanks to the use of its site of Montoldre (Allier). - The Pascal Institute will provide advice on scientific development (data fusion, traversability, risk management, planning), which will be implemented by an internal resource. - Logiroad will integrate its software module to classify the elements of the scene. The project will be carried out to increase the academics part in the software. Initially designed to manage functions at the state of the art level, via an adaptation of the existing modules, the vehicle will evolve during the 2 following challenges to better perceive the state of the terrain, to manage the passage of complex obstacles, to have redundancies to manage degraded environmental conditions or hardware faults. Thus, the basic technical definition Stereo Camera + Lidar 360° will be completed in the long term by a FMCW 360° radar. This project will allow the 2 SMEs to investigate in the Defense or Space sectors, but are also aimed the sector where the consortium is present: - The agricultural sector, requiring knowledge of a changing natural environment, with impact on the control. - The automotive sector, to allow the passage of autonomous vehicles in unmapped or poorly defined areas (especially rural areas).

Mobile robots are more and more efficient but limited by the problem of variation of motion properties, as is the case for applications in natural environments. Sharp transitions can be estimated reactively, but are difficult to predict, and lack of anticipation can lead to inappropriate or even hazardous behaviors. This project aims to overcome this problem by proposing adaptive mechanisms for robotic behavior by anticipating these variations from scene perception. The project proposes to develop machine learning approaches to predict and map the interaction conditions. It will also develop stable supervision processes to select and modify on-line several control modes. Tested on realistic scenarios using the robotic platforms available from the project members, such developments will strengthen the autonomy of robots to offer efficient and safe solutions to societal issues, particularly for agriculture.

The Internet of Things connects physical devices offering sensing or actuating with their vicinity. The ever-growing capabilities of devices allow to imagine new architectures including them as first class citizens. New added-value applications can then be envisioned in smart agriculture, smart buildings, smart cities, energy and water management, e-health and ageing well... The Web of Things (WoT) allows to describe the devices semantics, bridging the gap between the different domain and service descriptions. In today WoT architectures, physical devices can be located at distance from systems that perform reasoning. A centralised approach does not take advantage of the devices capabilities and induces suboptimal data transfers as well as server overload. Besides, many devices are now smart enough to discover each other, exchange data, and collectively make decisions. CoSWoT objectives are to propose a distributed WoT-enabled software architecture embedded on constrained devices with two main characteristics: (1) it will use ontologies to specify declaratively the application logic of devices and the semantics of the exchanged messages; (2) it will add reasoning functionalities to devices, so as to distribute processing tasks among them. Doing so, the development of applications including devices of the WoT will be highly simplified: our platform will enable the development and execution of intelligent and decentralised smart WoT applications despite the heterogeneity of devices. In CoSWoT, WoT applications will rely on a platform hosting the base services. Besides traditional services, it will host extensions that correspond to two scientific barriers: (1) the use of ontologies as a generalised model for exchanges between heterogeneous devices. A joint statement from AIOTI WG3, IEEE P2413, oneM2M, W3C positions ontologies as key enablers for semantic interoperability on the WoT. However research questions remain concerning (i) the adequation of existing ontologies to the target application domains; (ii) the applicability of theoretical principles developed in a variety of protocols and standards, in the context of data streams; (iii) the discovery of heterogeneous devices, their services and how to solicit them. (2) distributed and embedded incremental reasoning. Devices become powerful enough to offer storage and processing; new architectures appear, based on edge computing including devices such as sensors and actuators. The data streams provided by sensors require to perform incremental reasoning tasks. Research questions remain on (i) how to embed reasoning in devices with various capacities, it requires specific optimisations; (ii) how to efficiently distribute reasoning tasks among devices. Smart agriculture is a typical application domain of such WoT architectures, where the surveillance of cultivated fields requires various sensors that push streaming data, which must be collected and reasoned upon to take decisions executed by actuators. Smart buildings is another such typical application domain where added-value application services involve other verticals such as energy management, e-health, or ageing well. We will define use cases and requirements for smart agriculture and smart buildings, run simulations, and then lead real experiments. The CoSWoT platform will foster the decoupling of the development of software and the development of hardware, so as to ease the emergence of a new economic sector in the digital industry around WoT applications development, disconnected from the development of the smart devices themselves.

The conservation of biodiversity and its link with agriculture currently represents a major challenge. Observation data may be needed at large spatial or temporal scales to encompass a wide range of situations in order to achieve meaningful results. This implies that thousands of observers need to be mobilized, at a cost which would be prohibitive if they had to be paid. Therefore in this project we will define a set of statistical tools and observers’ behaviour modelling to extract and visualize accurate and relevant data from opportunistic data (VGI data), in order to produce meaningful farmland biodiversity indicators. Moreover, since VGI systems do not provide advanced analysis tools, in this project we will use Spatial OLAP to analyse those farmland biodiversity indicators. Since final users are different and numerous, in this project we will define a new group decision-making SOLAP design methodology to implement Spatial OLAP models for farmland biodiversity indicators

The objectives of the FooSIN project are to establish and work within the recently proposed and endorsed GO FAIR Food Systems Implementation Network (IN) to 1) accelerate the implementation of FAIR principles in the agri-food community, and 2) position France as a leader in this evolution and make French actions and productions more visible at an international level. The Food Systems IN, co-led by Inra and Wageningen University and Research, gathers 22 major actors of the agriculture and nutrition domains worldwide, who commit to FAIR principles and collectively work for their wider and quicker adoption. As members of the Food Systems IN, we propose concrete actions towards the French community of people involved in data production and management for agriculture and food. We will organize a Bring-Your-Own-Data workshop (a.k.a datathon), seek for adapted training materials, and recommend tools and methodologies to FAIRify data and semantic resources, with the aim to leverage the FAIR awareness and skills, and the adoption of efficient tooling by our community. We will also propose original tools and services for data FAIRification to be adopted and disseminated by the Food Systems IN at the international level. These services and tools may also be transfered to other fields among the INs of the GO FAIR network.