Status: attic
Investigating the Feasibility of Bluetooth Smart (BLE) GATT Beacons for Road Safety Applications
PA: Research Project (INF-PM-FPA / INF-PM-FPG) or
BA: Bachelor Thesis (or Studienarbeit / Großer Beleg)
A key enabler of future Intelligent Transportation Systems (ITS) is the ability to use wireless communication technologies to detect the presence of other road traffic participants. This is particularly true for pedestrians and cyclists, who are often not detected by current systems. However, it is precisely these road traffic participants who cannot easily be equipped with dedicated hardware running a custom Cellular Vehicle-to-Everything (C-V2X) or Wireless LAN (WLAN) stack. Bluetooth Smart (BLE), on the other hand, is a low power, low cost, low bandwidth wireless technology that is being used in a variety of applications and is available in many embedded systems and mobile devices. Its is designed to enable the periodic transmission of beacons to detect the presence of other devices in the vicinity and many applications such as COVID contact tracing or asset tracking use this feature. BLE is therefore a promising candidate for detecting the presence of pedestrians and cyclists in ITS applications.
Goals of the thesis
This thesis will investigate the feasibility of using Bluetooth Smart (BLE) Generic ATTribute Profile (GATT) beacons for road safety applications. A key part is conducting hardware experiments to determine reliability and range in real world environments. These experiments will require the use of the student’s smartphone(s). Embedded Computers(s) with a Bluetooth 4.1+ receiver (such as a Raspberry Pi) will be provided. The student is expected to write custom software, e.g., on top of the Linux BlueZ stack. A detailed written discussion of fundamentals, related work, system design, and obtained results concludes the thesis.
Collaboration
This thesis kicks off a larger collaboration with teams at TU Braunschweig and TU Ilmenau.
Keywords
Linux, Hardware, Practical
Literature
[1] Guillaume Celosia, Mathieu Cunche. Fingerprinting Bluetooth-Low-Energy Devices Based on the Generic Attribute Profile. IoT S&P 2019 - 2nd International ACM Workshop on Security and Privacy for the Internet-of-Things, Nov 2019, London, United Kingdom. pp.24-31, DOI 10.1145/3338507.3358617ff.
[2] https://github.com/IanHarvey/bluepy
[3] https://github.com/mh-/exposure-notification-ble-python/blob/master/README.md
[4] https://learn.adafruit.com/pibeacon-ibeacon-with-a-raspberry-pi