Method for orthorectification of terrestrial radar maps

International audienceThe vehicle-based PELICAN radar system is used in the context of mobile mapping. The R-SLAM algorithm allows simultaneous retrieval of the vehicle trajectory and of the map of the environment. As the purpose of PELICAN is to provide a means for gathering spatial information, the impact of distortion caused by the topography is not negligible. This article proposes an orthorectification process to correct panoramic radar images and the consequent R-SLAM trajectory and radar map. The a priori knowledge of the area topography is provided by a digital elevation model. By applying the method to the data obtained from a path with large variations in altitude it is shown that the corrected panoramic radar images are contracted by the orthorectification process. The efficiency of the orthorectification process is assessed firstly by comparing R-SLAM trajectories to a GPS trajectory and secondly by comparing the position of Ground Control Points on the radar map with their GPS position. The RMS positioning error moves from 5.56 m for the raw radar map to 0.75 m for the orthorectified radar map

Evaluation of LoRa technology in 433-MHz and 868-MHz for underground to aboveground data transmission

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Optimal route planning of an unmanned aerial vehicle for data collection of agricultural sensors

International audienceThe development of the Internet of Things is essential in agriculture to meet the challenges of the agro-ecological transition. In fact, by installing communicating sensors directly in the fields, the health of ecosystems can be accurately monitored (e.g. soil conditions, crop growth, loss of biodiversity), the processes optimally controlled (e.g. irrigation systems), and the crop production better managed (e.g. optimal decision making). However, forwarding the measurements from a massive number of IoT-based sensors distributed in the fields to the internet can be a challenging task, all the more in case of energy, cost, latency, data rate or connectivity constraints. The conventional technologies, as the connection to a cellular network, a gateway or a nano-satellite at low earth orbit, may in fact not met these constraints. This paper investigates a new paradigm based on a data collector embedded on an Unmanned Aerial Vehicle (UAV). This approach has numerous advantages (e.g. no need of infrastructures, no subscription fees, operate in white areas, reduce the transmitter power of the communicating sensors). However, as the operating time of an UAV is limited, the length of the flight trajectories to visit all the sensors and collect the data must be minimized. To address this issue, the communication ranges of the sensors are first modeled as hemispheres. The Close Enough Traveling Salesman Problem (CE-TSP) is then investigated at different flying heights. To solve this problem, an algorithm based on three successive parts, a graph reduction, a partheno-genetic algorithm and heuristic rules, is developed. This algorithm is tested on data sets involving a massive number of communicating sensors with various communication ranges, as well as on a real agricultural case study. The results highlight the performances of the method proposed and open the way to future perspectives for data collection of IoT-based sensors by means of UAVs

Evolutionary Algorithm with Geometrical Heuristics for Solving the Close Enough Traveling Salesman Problem: Application to the Trajectory Planning of an Unmanned Aerial Vehicle

Evolutionary algorithms have been widely studied in the literature to find sub-optimal solutions to complex problems as the Traveling Salesman Problem (TSP). In such a problem, the target positions are usually static and punctually defined. The objective is to minimize a cost function as the minimal distance, time or energy. However, in some applications, as the one addressed in this paper—namely the data collection of buried sensor nodes by means of an Unmanned Aerial Vehicle— the targets are areas with varying sizes: they are defined with respect to the radio communication range of each node, ranging from a few meters to several hundred meters according to various parameters (e.g., soil moisture, burial depth, transmit power). The Unmanned Aerial Vehicle has to enter successively in these dynamic areas to collect the data, without the need to pass at the vertical of each node. Some areas can obviously intersect. That leads to solve the Close Enough TSP. To determine a sub-optimal trajectory for the Unmanned Aerial Vehicle, this paper presents an original and efficient strategy based on an evolutionary algorithm completed with geometrical heuristics. The performances of the algorithm are highlighted through scenarios with respectively 15 and 50 target locations. The results are analyzed with respect to the total route length. Finally, conclusions and future research directions are discussed

Adaptive Robot Control Based on Wireless Underground Sensor Network in Agriculture 4.0

International audienceFrom sensor nodes fully buried at a few dozens of centimeters deep in Wireless Underground Sensor Networks (WUSN), the soil moisture information can be measured anywhere, including in the passage of vehicles. This opens new opportunities, in particular in Agriculture 4.0, to adapt the speed and work of agricultural mobile robots to the ground conditions. By integrating a collector node in a robot, connected to its CAN bus, this paper experimentally demonstrates the possibility to adapt in real time the speed of the robot with respect to the soil moisture information transmitted in LoRa by a buried sensor node. The hardware and software developements are presented, and the first experimental results discussed. Future research directions are given to extend the capabilities of the system proposed. The innovative approach presented in thispaper enables to envision new possibilities in the combination of WUSN and robotics technologies

Internet of Underground Things in Agriculture 4.0: Challenges, Applications and Perspectives

Internet of underground things (IoUTs) and wireless underground sensor networks (WUSNs) are new technologies particularly relevant in agriculture to measure and transmit environmental data, enabling us to optimize both crop growth and water resource management. The sensor nodes can be buried anywhere, including in the passage of vehicles, without interfering with aboveground farming activities. However, to obtain fully operational systems, several scientific and technological challenges remain to be addressed. The objective of this paper is to identify these challenges and provide an overview of the latest advances in IoUTs and WUSNs. The challenges related to the development of buried sensor nodes are first presented. The recent approaches proposed in the literature to autonomously and optimally collect the data of several buried sensor nodes, ranging from the use of ground relays, mobile robots and unmanned aerial vehicles, are next described. Finally, potential agricultural applications and future research directions are identified and discussed

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

International audienceThe development of Wireless Underground Sensor Networks (WUSNs) is a recent research axis based on sensor nodes buried a few dozen centimeters deep. The communication ranges are, however, highly reduced due to the high attenuation of electromagnetic waves in soil, leading to issues of data collection. This paper proposes to embed a data collector on an Unmanned Aerial Vehicle (UAV) coming close to each buried sensor node. The whole system was developed (sensor nodes, data collector, gateway) and experimentations were carried out in real conditions. In hovering mode, the measurements on the RSSI levels with respect to the position of the UAV highlight the interest in maintaining a high altitude when the UAV is far from the node. In dynamic mode, the experimental results demonstrate the feasibility of carrying out the data collection task while the UAV is moving. The speed of the UAV has, however, to be adapted to the required time to collect the data. In the case of numerous buried sensor nodes, evolutionary algorithms are implemented to plan the trajectory of the UAV optimally. To the best of our knowledge, this paper is the first one that reports experiment results combining WUSN and UAV technologies

Towards a UML Profile for Designing Smart IoT Data-Centric Applications

The implementation of IoT (Internet of Things) systems is difficult since the data sent from the devices is complex, especially in agriculture and agroecology, where it is generated from heterogeneous hardware and software, and its applications involve different actors. In this scenario, conceptual design is mandatory to provide a formal and unambiguous representation allowing the different actors to set their requirements. The problem with the current representations is that they do not take into account neither the internal parameters nor the dynamic aspect of smart devices. To fill this gap we propose SmartSTS4IoT, an extension of the STS4IoT UML profile that models the different representations of internal/external data expressed from the same sensor and the logic used to adapt the sending/sensing policies to sudden environmental changes. The profile is illustrated with reference to a case study in the context of smart agriculture and validated theoretically

ConnecSenS, a Versatile IoT Platform for Environment Monitoring: Bring Water to Cloud

International audienceClimate change is having an increasingly rapid impact on ecosystems and particularly on the issue of water resources. The Internet of Things and communication technologies have now reached a level of maturity that allows sensors to be deployed more easily on sites to monitor them. The communicating node based on LoRaWAN technology presented in this article is open and allows the interfacing of numerous sensors for designing long-term environmental monitoring systems of isolated sites. The data integration in the cloud is ensured by a workflow driving the storage and indexing of data, allowing a simple and efficient use of the data for different users (scientists, administration, citizens) through specific dashboards and extractions. This article presents this infrastructure through environmental monitoring use cases related to water resources