A Collaborative UAV-WSN Network for Monitoring Large Areas

Abstract

Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better overall performance. This paper presents a hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas. A prime objective and novelty of the heterogeneous multi-agent scheme proposed here is the optimal generation of reference trajectories, parameterized after inter- and intra-line distances. The main contribution is the trajectory design, optimized to avoid interdicted regions, to pass near predefined way-points, with guaranteed communication time, and to minimize total path length. Mixed-integer description is employed into the associated constrained optimization problem. The second novelty is the sensor localization and clustering method for optimal ground coverage taking into account the communication information between UAV and a subset of ground sensors (i.e., the cluster heads). Results show improvements in both network and data collection efficiency metrics by implementing the proposed algorithms. These are initially evaluated by means of simulation and then validated on a realistic WSN-UAV test-bed, thus bringing significant practical value.

IoT-Enabled Distributed Data Processing for Precision Agriculture

“…The Lagrange form in (10) can be written out in power form of an interpolating polynomial as, P n (x) = a 1 x n−1 + a 2 x n−2 + ... + a n−1 x + a n (11) where the coefficients a k are computed through a system of linear equations:…”

IoT System Integrating Unmanned Aerial Vehicles and LoRa Technology: A Performance Evaluation Study

“…Other authors [26][27][28][29] evaluated the use of WSN to acquire raw data from the environment and employed LoRa/LoRaWAN to transmit the data to the server, assuming that LoRa covers a range up to 30 km. In [30,31], the authors integrated WSN with UAVs and proposed an optimal trajectory design, minimizing the total path length, passing close to the main interesting points, and ensuring a minimal delay in the communication. Sharma et al [32] tested a LoRaWAN network using UAVs for urban surveillance focusing on stress areas, being able to preserve 40% of the network energy consumption.…”

Advanced UAV–WSN System for Intelligent Monitoring in Precision Agriculture

“…In Reference [32], the authors discuss the information system design supporting agriculture data management. Enabling advanced data processing in the form of sensor fusion and clustering mechanisms for improved network topologies in generic applications has been discussed [30]. Effective data gathering mechanisms [33] and higher level IoT architectures [34] are key and current topics of interest.…”

“…-Group the sensors in clusters and determine the cluster heads, the methodology proposed by the authors in Reference [30]; -Path planning based on specific conditions for efficient data collection; and -Intelligent data collection and processing.…”