Enhancing Wireless Sensor Networks with Bluetooth Low-Energy Mesh and Ant Colony Optimization Algorithm

Wireless Sensor Networks (WSNs) face persistent challenges of uneven energy depletion, limited scalability, and reduced network lifetime, all of which hinder their effectiveness in Internet of Things (IoT) applications. This paper introduces a hybrid framework that integrates Bluetooth Low-Energy (BLE) mesh networking with Ant Colony Optimization (ACO) to deliver energy-aware, adaptive routing over a standards-compliant mesh fabric. BLE mesh contributes a resilient many-to-many topology with Friend/Low-Power Node roles that minimize idle listening, while ACO dynamically selects next hops based on residual energy, distance, and link quality to balance load and prevent hot spots. Using large-scale simulations with 1000 nodes over a 1000 × 1000 m field, the proposed BLE-ACO system reduced overall energy consumption by approximately 35%, extended network lifetime by 40%, and improved throughput by 25% compared with conventional BLE forwarding, while also surpassing a LEACH-like clustering baseline. Confidence interval analysis confirmed the statistical robustness of these results. The findings demonstrate that BLE-ACO is a scalable, sustainable, and standards-aligned solution for energy-constrained IoT deployments, particularly in smart cities, industrial automation, and environmental monitoring, where long-term performance and adaptability are critical.