A network architecture for high volume data collection in agricultural applications

An important requirement for Internet of Things applications is the ability to provide fast and energy efficient data collection from wireless sensors. When sensor nodes are located far from the data collection point, currently available long range protocols present challenges associated with a very low data rate and often unreliable connections resulting in excessive energy consumption related to data transmission. To address this problem, we propose a simple and energy-efficient data collection architecture for smart agricultural purposes which require wireless sensing. The architecture involves data collection from nodes located in remote fields or on animals leveraging off the use of drones as a data collection mechanism. In particular, drones can fly over the desired areas (points) and collect high volumes of data that would be otherwise difficult to transfer directly to the sink in a reasonable amount of time and using reasonable amounts of energy. We describe the different components and stages that constitute the proposed architecture emphasizing the networking component. We propose the use of different communication technologies, such as LoRa and WiFi, depending on the data collection requirements. We present an in-lab development of this architecture as a proof-of-concept as well as preliminary results for the architecture. The results reveal that the proposed solution is potentially capable of achieving data collection at high volume, however, the performance does not consider the highest spreading factors of LoRa

Optimizing the trajectory of drones: trade-off between distance and energy

International audienceThe use of autonomous unmanned aerial vehicles (UAVs) or drones has emerged to efficiently collect data from mobile sensors when there is no infrastructure available. The drones can form a flying ad-hoc network through which the sensors can send their data to a base station at any time. In this paper, we present a mixed integer linear program to find the drones' optimal trajectories to form and maintain this network through time while minimizing their movements and energy consumption. Furthermore we analyze the trade-off between distance and energy, where increasing the drones' mobility can reduce their energy consumption, and derive a fair trade-off optimal solution to balance the two opposite objectives