HIRO-NET Demonstration for Step 2 @ Mozilla Challenge

This video has been shot at The George J. Kostas Research Institute for Homeland Security at Burlington, MA.
It demonstrates mesh networking features of the HIRO-NET system by using smartphones, drones and ground robots.

Drone Field Test

Early in November 2017, a field experiment was conducted to test integration of users’ smartphones and robotic drones into the HIRO-NET system. We used the standard Bridgefy app and a DJI Matrice 100 Quadcopter. The following video shows that drones can be effectively used as bridges to connect two or more disconnected users.

Testing HIRO-NET algorithms in MATLAB

In this video we show HIRO-NET performs clustering of the area affected by a natural disaster and computes the efficient flight plans for aerial drones. To optimize search and rescue operations, HIRO-­NET partitions the city map into a Voronoi diagram each associated with a generating point. Generating points of Voronoi regions are rescue headquarter locations such as police stations, fire department, where HIRO-­NET robotic platforms are initially stored. Upon activation, HIRO­-NET drones take off from a rescue headquarter and fly within their Voronoi region to search for existing local mesh networks. HIRO-­NET air drones are first directed to Points of Interest (PoI), which are pre­determined areas such as schools, hospitals and stadiums. PoIs are assigned to each drone by using clustering algorithms (i.e., k­-means). Graph theory optimization is applied to compute the optimal trajectory considering battery constraints. Each drone runs an online beaconing routine that discovers HIRO­-NET mesh networks and  dynamically updates its trajectory. The video also shows how aerial drones discover survivor-generated mesh networks and adapt their trajectory accordingly.