The Internet of Things (IoT) has gained widespread adoption, prompting the addition of new connected devices to the network, such as Unmanned Aerial Vehicles (UAVs). UAVs provide a host of social benefits, including improved personal safety, security, and productivity. These help first responders save lives during natural catastrophes, find missing children, and combat wildfires. They assist the Coast Guard in rescue missions and the Border Patrol in maintaining national security. UAVs provide a practical solution to the limitations of existing terrestrial IoT infrastructure, as well as new ways to deliver IoT services through a wide range of applications. UAVs are well‐suited to collecting aerial data for constant use in large industrial facilities, allowing for speedy and seamless data collection to support informed business decisions. By eliminating the requirement for a drone operator, an automated UAV system improves efficiency while also providing continual, frequent, and real‐time data access. A UAV system collects data from the air and is a useful tool for organizations automating large‐scale activities. With these benefits, it is expected that the number of UAVs flying in low‐altitude airspace above congested cities will rise. As a result, a system for monitoring and managing UAV traffic must be put in place. This adds to the difficulty of doing research, such as guaranteeing the safe operation of UAVs in high‐traffic regions. This research looks into UAV Traffic Management (UTM), with a focus on big data approaches in UTM. The benefits, limitations, and implementation of big data approaches in UTM systems are also discussed in this chapter. This chapter also looks at the results of recent study in the same domain. Finally, the chapter concludes with a consideration of the traffic control system for UAVs in the future.


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    Titel :

    Big Data Technologies in UAV's Traffic Management System


    Untertitel :

    Importance, Benefits, Challenges and Applications


    Beteiligte:
    Rawat, Romil (Herausgeber:in) / Sowjanya, A. Mary (Herausgeber:in) / Patel, Syed Imran (Herausgeber:in) / Jaiswal, Varshali (Herausgeber:in) / Khan, Imran (Herausgeber:in) / Balaram, Allam (Herausgeber:in) / Agarwal, Piyush (Autor:in) / Sharma, Sachin (Autor:in) / Matta, Priya (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-12-19


    Format / Umfang :

    21 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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