Orchestrating a Smart Agriculture System with Optimized Sensor Allocations and Heterogeneous Wireless Coverage

Smart agricultural systems are essential in increasing production rates and reducing losses, while poor connectivity hinders their capabilities. Ensuring robust connectivity among its components within a systematic agricultural field remains a significant challenge. Issues related to sensor allocation and wireless coverage further complicate this landscape. A practical solution lies in adopting an orchestrated wireless sensor network (WSN) design that addresses these research gaps in tandem. The orchestrated design provides a novel connectivity solution that improves connectivity development within two approaches. The first approach utilizes a hybrid method for sensor allocation. The second approach concerns maintaining more robust wireless coverage for those allocated sensors. This paper proposes an orchestrated design that employs a hybrid approach to incorporate area clustering using the rapidly exploring random trees method for efficient spatial sampling. Additionally, it introduces an improved allocation method for agricultural sensors based on a mathematical variable length distance technique combined with the Voronoi algorithm. To further enhance wireless coverage, the design targets the interoperability of wireless transmission via the Fuzzy Analytical Hierarchical Process method. This is complemented by the k-nearest neighbors method for planning wireless sensor communication pathways. Overall, the proposed orchestrated design demonstrates significant advancements. It provides economic implementation by allocating only 13 nodes, achieving minimal power consumption rates and optimal coverage. Furthermore, it has 86% WSN coverage and a performance score that surpasses Particle Swarm Optimization by 1.13%.