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With the growth of commercial aviation over the last few decades there havebeen many applications designed to improve the efficiency of flight operationsas well as safety and security. A number of these applications are based on thegathered data from flights; the data is usually acquired from the varioussensors available on the aircraft. There are numerous sensors among theelectrical and electronics devices on an aircraft, most of which are essentialfor the proper functioning of the same. With the sensors being operationalthroughout the time of movement of the aircraft, a large amount of data iscollected during each flight. Normally, most of the gathered data are stored ona storage device on the aircraft, and are analyzed and studied later off-sitefor research purposes focusing on improving airline operation and efficientlymaintaining the same. In certain cases, when there is data transfer during theflight, 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 theoperating cost of the airline. Therefore, in this paper, we study techniques todetect and avoid Clear Air Turbulence (CAT), which is a specific type ofturbulence, based on the IoT framework of aircraft. We propose algorithms thatconsider both direct and indirect communication between aircraft within aspecific region. Using simulation results, we show that our proposed techniquesof direct communication using the IoT framework is faster than conventionaltechniques involving radio communication via both single ATC tower and multipleATC towers.

Efficient Clear Air Turbulence Avoidance Algorithms using IoT for Commercial Aviation