BLE-based indoor asset-tracking system

Abstract

Indoor asset tracking plays a vital role in industries such as healthcare and logistics, where real-time location monitoring enhances operational efficiency and asset management. This project focuses on developing a Bluetooth Low Energy (BLE)-based asset tracking system, integrating BLE-enabled asset tags and anchors with a web application for asset visualization and device management. The system is designed for indoor localization using the fingerprinting technique on Received Signal Strength Indicator (RSSI) data, coupled with a web-based interface which allows users to monitor and configure devices easily. Due to the absence of a trained Convolutional Neural Network (CNN) model, localization was simulated within a grid-based environment to assess feasibility. Results show that the system successfully utilizes BLE communication for real-time tracking, with a localization precision of up to 1m-by-1m grid cells. Nevertheless, further enhancements to scalability, security, and tracking scope can be made to improve the system’s overall performance and applicability.