We are happy to announce that Ben-Jasper Kettlitz has won the “Datenlotsen-Preis 2022” of the TU Darmstadt for his Bachelor’s thesis “Updating Heterogeneous LoRaWAN Nodes Using a Modular LoRaWAN-Stack”. Every year, up to four graduates from computer science, mathematics or industrial engineering are honored with the Datenlotsen-Preis for their outstanding Bachelor’s and Master’s thesis. The prices were handed over in a ceremony at the Georg-Christoph-Lichtenberg-Haus in December.
The thesis of Ben-Jasper Kettlitz focuses on LoRaWAN sensor networks, which play a central role in the transition to smart and digital cities. The thesis was supervised by emergenCITY researcher Frank Hessel at the Secure Mobile Networking Lab.
LoRaWAN sensor networks should help creating a detailed overview of the city and thus contribute to the optimization of municipal and business processes. LoRaWAN sensors have a very low energy consumption and operate on low data rates, which allows operation without on-site maintenance for extend amounts of time. Within the network, a variety of sensor types from different vendors and platforms coexists. Updating the sensor’s internal software, for example to address security issues, is a challenging task in such a heterogeneous environment and given the limitations on energy consumption and battery use.
The thesis solves this issue in an innovative way by allowing to target and swap single functions within the device software. In consequence, only functionality which actually changed has to be transmitted, saving energy and transmission time. By using a platform-independent representation of the updated function, all sensor nodes can receive their updates simultaneously.
Particularly interesting for emergenCITY is that the new approach can also help in crises. In addition to the efficient transfer of software updates, it is also possible to adapt the functionality of the sensor nodes quickly and efficiently. That would allow changing network topologies so they are able to provide situational awareness without a central Cloud infrastructure. Furthermore, data acquisition based could be adapted based on demand from a control center.