Optimizing Energy Efficiency in Wireless Sensor Networks: Integrating Bluetooth M-LPN System with ABC Algorithm

In the evolving landscape of sustainable technology, optimizing energy efficiency is increasingly critical. Bluetooth Low Energy (BLE) has emerged as a pivotal technology for energy-efficient communication, particularly in the Internet of Things (IoT) and healthcare sectors. This study explores the integration of BLE with the Artificial Bee Colony (ABC) algorithm to enhance the efficiency of Bluetooth M-Low Power Node Wireless Sensor Networks (M-LPNWSNs). The ABC algorithm, inspired by the foraging behavior of honeybees, excels in optimizing energy consumption in Wireless Sensor Networks (WSNs) through a mesh topology, which ensures robust and efficient data transmission. This paper examines the synergy between BLE and the ABC algorithm, focusing on the advantages of mesh networks and low-power nodes in reducing power consumption. Through detailed simulations and comparative analyses, the effectiveness of the ABC algorithm in improving energy efficiency in Bluetooth M-LPNWSNs is demonstrated. Key results highlight the algorithm's superiority over traditional methods, such as Genetic Algorithms (GA), in minimizing power usage. This research provides valuable insights into developing more sustainable and efficient WSNs, offering a practical framework for integrating BLE with advanced optimization techniques.