Saturday 01 February 2025
Scientists have been working tirelessly to develop a reliable and accurate indoor location system using Bluetooth Low Energy (BLE) technology. Recently, researchers from the University of Ghent and others published a paper detailing their efforts to create such a system.
The BLE system uses angle-of-arrival (AoA) estimation, which measures the direction of a signal’s arrival at an antenna array. The team created a dataset of 1000 BLE packets with AoA measurements taken at various angles and distances. They used this data to train a Gaussian Process Regression (GPR) algorithm, which can estimate distances between devices using RSS measurements.
The researchers tested their system in a controlled environment with multiple antennas and found that it was able to accurately estimate distances within a range of 5 meters. This is a significant improvement over previous systems, which often struggled with accuracy at shorter ranges.
One of the key challenges facing indoor location systems is the variability of wireless signals, which can be affected by many factors such as walls, furniture, and other devices. To overcome this challenge, the team used a combination of AoA and RSS measurements to improve the system’s robustness.
Another innovation in their research was the development of a new dataset specifically designed for BLE-based indoor location systems. This dataset includes a wide range of angles, distances, and channel conditions, which will help other researchers to test and develop their own systems.
The potential applications of this technology are vast, from smart homes to industrial settings. Imagine being able to navigate through a large warehouse or factory with ease, knowing exactly where you are at all times.
While there is still much work to be done to perfect the system, this research marks an important step forward in the development of reliable and accurate indoor location systems using BLE technology.
Cite this article: “BLE-Based Indoor Location System Achieves Accurate Distance Estimation”, The Science Archive, 2025.
Bluetooth Low Energy, Indoor Location System, Angle-Of-Arrival Estimation, Gaussian Process Regression, Radio Signal Strength, Wireless Signals, Antenna Array, Dataset, Smart Homes, Industrial Settings
