Intelligent Node Deployment in Smart Spaces to Optimize Sensor Signal and Data Acquisition

The rapid growth of the Internet of Things (IoT) has led to the proliferation of interconnected devices and the generation of vast amounts of data. One of the critical factors in optimizing IoT data acquisition networks is the intelligent deployment of nodes to ensure adequate coverage. Therefore, throughout this paper, we propose an innovative approach to deploy sensor nodes as the primary data source of IoT in Smart Spaces. The proposed framework combines Poisson point processing, spatial partitioning by Voronoi diagrams and the modified Artificial Bee Colony (ABC) algorithm for position optimization. Voronoi’s tessellation of Euclidean space is constructed using the radical lines of the circular planes created by the intersections of the spheres. Initially, sensor nodes, which represent the centre of each sphere, are positioned erratically using the Poisson point process (PPP). Then ABC algorithm is utilized to intelligently explore the environment, detect, and cover the grey areas considering the overlapped coverage with other sensors. Comparison with the Voronoi-based algorithm for sensor network architecture optimization proves the effectiveness of the proposed ABC algorithm.