Abstract
With the advent of unmanned aerial vehicles (UAVs) several sector of life has been improved. Currently, numerous researches are carried out to enhance UAV capabilities. UAVs are frequently utilized in several life-threatening operations such as rescue, surveillance and transportation. Apart from this, drones-based experiments are conducted in geology, wildlife, safety and ecological protection. Additionally, 5th generation approach which is consists of huge networks, high consistency and transmission rates assist in UAVs. However, to attain such goals is business challenge for rapidly evolving Internet of Things (IoT), particularly in most dynamic and mobile environments. Therefore, utilized in emergency where UAVs ensures rapid recovery and tackling heavy traffic situations. These characteristics have attracted the attention of organizations and academia. Moreover, machine learning (ML) and artificial intelligence (AI) approaches are integrated into network where information is used to solve problems. Thus, combination of ML with AI operates applications. Furthermore, entire operation performance is enhanced. In this chapter, UAVs with machine learning approaches are discussed. Study covers gaps in previous research which influenced existing technique. In different context, machine learning (ML) has recently become a subdomain of artificial intelligence.
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Baig, B., Shahzad, A.Q. (2022). Machine Learning and AI Approach to Improve UAV Communication and Networking. In: Ouaissa, M., Khan, I.U., Ouaissa, M., Boulouard, Z., Hussain Shah, S.B. (eds) Computational Intelligence for Unmanned Aerial Vehicles Communication Networks. Studies in Computational Intelligence, vol 1033. Springer, Cham. https://doi.org/10.1007/978-3-030-97113-7_1
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DOI: https://doi.org/10.1007/978-3-030-97113-7_1
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