Efficient Clear Air Turbulence Avoidance Algorithms using IoT for Commercial Aviation
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With the growth of commercial aviation over the last few decades there have been many applications designed to improve the efficiency of flight operations as well as safety and security. A number of these applications are based on the gathered data from flights; the data is usually acquired from the various sensors available on the aircraft. There are numerous sensors among the electrical and electronics devices on an aircraft, most of which are essential for the proper functioning of the same. With the sensors being operational throughout the time of movement of the aircraft, a large amount of data is collected during each flight. Normally, most of the gathered data are stored on a storage device on the aircraft, and are analyzed and studied later off-site for research purposes focusing on improving airline operation and efficiently maintaining the same. In certain cases, when there is data transfer during the flight, it is between the aircraft and an air-traffic-control (ATC) tower, which serves as the base station. The aircraft equipped with all these sensors, which can gather and exchange data, form a framework of Internet of things (IoT). Detecting and avoiding any form of turbulence for an aircraft is vital; it adds to the safety of both passengers and aircraft while reducing the operating cost of the airline. Therefore, in this paper, we study techniques to detect and avoid Clear Air Turbulence (CAT), which is a specific type of turbulence, based on the IoT framework of aircraft. We propose algorithms that consider both direct and indirect communication between aircraft within a specific region. Using simulation results, we show that our proposed techniques of direct communication using the IoT framework is faster than conventional techniques involving radio communication via both single ATC tower and multiple ATC towers.
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