Researchers have designed a cloud-based framework that uses an internet-of-things messaging protocol for communications among drones, autonomous ground vehicles and responders.
In disaster zones caused by earthquakes, floods, fires, chemical leaks or explosions, first responders may be unable to identify hazards or locate victims amid damaged buildings and a vastly altered environment.
Unmanned aerial and ground vehicles (UAVs and UGVs) have helped responders gain situational awareness, but their inability to quickly and efficiently communicate with each other in power- and network-constrained environments limits their ability to work together with responders.
To address these challenges, researchers have developed a collaborative wireless autonomous systems network framework for disaster area management.
"Most of the existing frameworks cannot extend network service to the autonomous systems, such as UAVs working in network-denied disaster environment, and they do not also have a nearby UAVs' charging point," said Abenezer Girma, a PhD student at North Carolina A&T State University.
Girma and a team of researchers with the university’s Department of Electrical and Computer Engineering have designed a cloud-based framework that uses an internet-of-things messaging protocol to enable communications among drones, autonomous ground vehicles and responders.
The team equipped UAVs and UGVs with multiple sensors that collect and share information with first responders. The UGVs assess the situation on the ground, and the UAVs help with coordinating their activities by providing communications support and giving responders an aerial view of the environment. A clustering algorithm in the framework maximizes the network coverage provided by the UAVs to the UGVs, according to their paper.
A cloud-based remote control station enables first responders to use the internet to remotely monitor operations from anywhere. With an antenna tracker, responders can extend networking capabilities from a nearby functioning network to track the autonomous vehicles and extend their communications range.
To keep the autonomous vehicles powered, the researchers developed a control mechanism that allows a drone to land on a moving UGV where it can be recharged or transported to a more distant location.
Finally, the team used an architectural analysis and design language tool to analyze and evaluate the end-to-end delay of the framework.
The researchers tested the hardware implementation of the proposed framework under different scenarios and verified that the IoT-based communication protocol is more efficient than conventional protocols for communication in widespread disaster areas.
In the future, the researchers said they plan to build on their design by adding even more sophisticated monitoring capabilities such as computer vision and machine learning.
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