Empowering Bluetooth Angle of Arrival Positioning with Ultra-wideband for Industry 4.0

The shift from mass production to mass customization in the era of Industry 4.0 requires production and warehouse management to be more flexible and controllable. The precise location information of the resources (men, machines, materials) is significant to enable the orchestration of processes and operations. However, the massive resources and complicated industrial environment could impede the adoption of high-cost, shelter-sensitive and hard-to-deploy indoor positioning systems. Therefore, this paper proposes a novel solution that amalgamates Bluetooth Low Energy (BLE), featuring low energy consumption, low cost, and high scalability, and Ultra-wideband (UWB) technology that attains high location accuracy. A deep learning method is designed for angle of arrival (AoA) estimation to address the challenges of multipath fading faced by BLE, thus enhancing location accuracy. UWB is innovatively employed to facilitate sampling and labeling job to underpin rapid deployment. The AoA training data can be collected on site during the operations, avoiding the impact on daily production. The experimental results show that the proposed solution achieving a positioning accuracy of 50 cm.