Student working on a research project.

*POSITION CURRENTLY FILLED* Cloud Control: Cloud-Based Air Traffic Control For Small Unmanned Aerial Systems Using A Low Power Wide Area Network

*POSITION CURRENTLY FILLED*

We envision a cloud-based air traffic control system that leverages emerging Low Power Wide Area Network (LPWAN) technology to monitor and control small unmanned aerial systems (SUAS) over large areas of low-altitude airspace. Large-scale low-cost monitoring of SUAS is not possible with predominant wireless technologies. Short-range technologies like IEEE 802.15.4 (the foundation of ZigBee) and IEEE 802.11 (Wi-Fi) can be implemented with low-power, low-cost chips; however, they need to be configured in mesh networks to cover wide areas, which creates challenges in terms of connectivity, reliability, and latency. On the other hand, long-range cellular technologies can provide coverage of several kilometers; however, they have expensive transceivers due to the complexity of the underlying protocols, and have a high cost of usage because they operate over licensed bands. In light of these limitations, we propose to leverage LPWANs - an emerging connectivity solution for the Internet of Things (IoT) - because they combine the advantages of low-cost low-energy short-range technologies with the coverage of cellular networks. Our concept of air traffic control differs from existing approaches because it is not just about providing remote pilots information to maintain separation between aircraft, but also involves remote actuation of SUAS based on global information about the airspace and environment. In particular, the proposed system will provide a mechanism to define and enforce permanent and temporary airspace restrictions (e.g., no-fly zones), and to prevent SUAS-to-aircraft, SUAS-to-SUAS, and SUAS-to-environment collisions without using sophisticated on-board sensors and processing like conventional sense-and-avoid technologies.

Research Project Information

Disciplines: Electrical Engineering, Computer Science, Mechanical and Aerospace Engineering, Industrial Engineering
Student Skill-Set Needed: *POSITION CURRENTLY FILLED* Working knowledge of C/C++ and Python, ability to work with embedded systems
Compensation: Volunteer
Available: Fall
Website: http://www.eng.buffalo.edu/~nmastron/

Contact

For further information on this opportunity, or to apply, contact:

Faculty Member: Nicholas Mastronarde
Title: Associate Professor
Department: Electrical Engineering
Office: 226 Davis Hall
Email: nmastron@buffalo.edu