Travel Path Planning for UAV as a Data Collector for a Sparse WSN

Recent advances in Unmanned Aerial Vehicle (UAV) technologies make their use as data collection sinks feasible for practical applications of Wireless Sensor Networks (WSN). Using UAVs as mobile data collection agents can improve network performance by reducing the horizontal radio pollution in animal sanctuaries or conservations, for example. This may also positively improve energy consumption of both UAV and sensor nodes (SN) on the ground. Designing an efficient UAV trajectory which has the capability of data gathering from randomly distributed large number of SNs has been one of the challenges for the UAV-aided WSN data gathering solutions. This paper aims at conceptualizing a solution for UAV path planning in gathering data of distributed wireless sensors over a large space. Both efficient flight path and dynamic orchestration of sensor grouping are considered as two key factors for improving the flight performance in data collection. Herein, a classical Travel Salesman Problem (TSP) solution supported by the ground group offerings are used for manipulating a simplified centroid-based trajectory and turning it into a more relaxed fuzzy route. This in turn would offer a ground for smoother and more efficient flight paths. While preliminary modelling of the approach offers encouraging results, the demand for fluidity in dynamically re-orchestrating the ground sensor networks must be carefully considered. Successful implementation of this concept would support a wide range of applications such as the farming and conservation used cases.