Bio Algorithms for Resource Optimisation and Analysis of Data

Wireless sensor nodes are an important part of many modern systems, such as environmental monitoring networks, smart homes, and industrial automation. These nodes are typically small, low-power devices that are deployed in large numbers to collect data and perform various tasks. However, the limited energy resources of these nodes can be a major limitation to their performance and lifetime. Optimal sensor placement not only minimizes the consumption of limited energy of battery-driven sensors but also reduces the sensing of redundant information. Hence it is of utmost importance to optimize the energy consumed by a wireless sensor network for better sustainability. In this project, we focus on bio-inspired optimization algorithms concerning the optimal sensor node placement in WSNs for a smart agriculture setup namely the Particle Swarm Optimization Algorithm and LEACH Algorithm and prove that the latter is the better algorithm suited for energy conservation by soil moisture wireless sensor nodes placed in a WSN and the same can be extended to any real-life application. A comparative analysis is performed between the stochastic heuristic algorithm in PSO and the hierarchical protocol of the LEACH algorithm for energy consumed by the wireless sensor nodes.