Collaborative WSN-UAV Data Collection in Smart Agriculture: A Bi-objective Optimization Scheme

Smart agriculture which integrates the with Internet of Things (IoT) has attracted attention since it contributes to increase productivity and quality crops, reduce energy consumption facilitate farmers. Wireless sensor networks (WSNs) unmanned aerial vehicles (UAVs) are two most commonly deployed devices that used for enabling smart agriculture. In this paper, we design a collaborative WSN-UAV system, wherein different clusters nodes form sensor-based virtual antenna arrays (SVAAs) transmit collected data towards receiver UAVs via adopting beamforming (CB), then will take back ground control station (GCS). We formulate transmission rate battery bi-objective optimization problem (TRBEBOP) simultaneously maximize total CB remaining selected nodes, by selecting appropriate in each cluster can predominant SVAA, determining suitable optimizing excitation current weights nodes. To handle formulated TRBEBOP is demonstrated be non-convex NP-hard, an enhanced non-dominated sorting genetic algorithm II (ENSGA-II) several specific designs presented. Simulation results validate effectiveness proposed ENSGA-II solving TRBEBOP. Moreover, compared other benchmark algorithms, superiority demonstrated. addition, impacts fortuitous circumstances on system estimated, illustrate robustness scheme. Finally, discussion about mechanisms deal interference induced sidelobe levels impact UAV movement receiving provided.