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Drone UTTERANCE Cast Analysis using Machine Learning


S.R.Sridhar , Muthayammal Engineering College; V.Kathiravan, Muthayammal Engineering College; R.Mylesh, Muthayammal Engineering College; M.Naveen Kumar, Muthayammal Engineering College


Unmanned Aerial Vehicle (UAV), Drone Communication, Machine Learning


Unmanned aerial vehicles (UAVs) networks square measure still untouched and much from analysis field. Security problems square measure the main issues as a result of these networks square measure susceptible to varied attacks which can cause data leak. Cyber Physical Systems (CPS) play a very important role in providing vital services in industries like autonomous vehicle systems, energy, health, producing, etc., by integration computation, physical management, and networking. Most of those systems are not solely cyber-physical, however additionally operate in an exceedingly safety-critical application wherever a failure or malfunction may lead to injury or perhaps loss of life. AN pilotless Aerial System (UAS) meets the wants of a cycle per second and safety-critical system with its dependence on wireless communication, sensors, and algorithms that job synergistically to perform its practicality. Innovation technology has followed the paradigm of enhancing performance as a main priority, with security as either AN afterthought or not thought of in the least, inflicting an absence of security against cyber-attacks in most UAVs. within the past UAVs have costly, heavy, and most typically utilized by the military, however, cost, size, and weight have cut drastically, whereas their capabilities, attributed to technology, have accumulated well.

Other Details

Paper ID: IJSRDV8I10288
Published in: Volume : 8, Issue : 1
Publication Date: 01/04/2020
Page(s): 1151-1155

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