Machine-to-Machine
(M2M) collaboration opens new opportunities where systems can collaborate
without any human intervention and solve engineering problems efficiently and
effectively. M2M is widely used for various application areas. Through this reported project
authors developed a M2M system where a drone and two ground vehicles
collaborate through a base station to implement a system that can be utilized
for an indoor search and rescue operation. The model training for drone flight
paths achieves almost 100% accuracy. It was also observed that the accuracy of the
model increased with more training samples. Both the drone flight path and
ground vehicle navigation are controlled from the base station. Machine
learning is utilized for modelling of drone’s flight path as well as for ground
vehicle navigation through obstacles. The developed system was implemented on a
field trial within a corridor of a building, and it was demonstrated successfully.
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