Proximity-Based Access Control With BLE Communication Using Path Loss Model and MLP Prediction
2023 · IEEE · Best Paper — VITeCoN 2023 · Abhishek Sebastian, Pragna R, Madhan Kumar S, Jesher Joshua M, Sarath Prathap, Brintha Therese A
BLE proximity access control that adapts path-loss prediction to changing environments.
Bluetooth Low Energy is cheap and everywhere — and noisy when humidity and temperature shift. This work uses a path-loss model plus an MLP to predict exponent changes dynamically for proximity sensing and access control.
The experimental setup uses an Arduino Nano 33 BLE Sense and iPhone 13 Pro, with measurements in an anechoic chamber and a classroom. Comparing these environments addresses a practical weakness of proximity sensing: a fixed signal-strength rule may not transfer between spaces.
The work received Best Paper at VITeCoN 2023. Its focus is adapting the proximity estimate; a complete access-control system still needs identity verification and an appropriate decision policy.
How close is close enough?
An Arduino Nano 33 BLE Sense and iPhone 13 Pro provide the experimental sensing setup.
Conceptual explanation of the IEEE study; this page does not scan nearby devices.
- BLE
- Access control
- MLP