Locating Objects in Warehouses Using BLE Beacons & Machine Learning

Abstract

Warehouse management plays a pivotal role to boost the entire supply chain. To increase productivity, enterprises are focusing on different object localization approaches to achieve better accuracy amid high interferences. This helps to reduce the overall time for order taking & perform effective stock management. For this purpose, we propose a cost-effective system to achieve better accuracy for locating objects in indoor spaces with the help of BLE beacons. BLE is the term used for the Bluetooth wireless standard for low power consumption. BLE beacons are used as technology enablers because BLE supports all the major mobile smart devices and tablets. The measurement is performed using Received Signal Strength Indication (RSSI). Also, improved the location accuracy with the help of machine learning algorithms & utilizing neighborhood beacons for real-world use cases of warehouse management. The target object & neighborhood beacons provide the raw data to the system & the mobile device acts as a receiver. Our results show that the proposed work provides high accuracy for finding resources, taking orders & improving the overall stock process in warehouse management.

Keywords

• Indoor environments
• bluetooth
• radio communication
• machine learning
• warehousing