In this paper, we present the recent research in the development of AL drones by using an algorithm of deep learning (A subset of machine learning algorithms) and computer vision (CV) based on a drone camera, the study explores the potential use of drones not only in searching the victim person, animals, important properties during natural calamities like flood, volcanoes eruption, forest fire, cyclones, and earthquake, etc. but also it insights into much useful information to collect to ensure the future safety by using a machine learning algorithm. Preparing for and responding to disasters is a major logistical challenge. "Actionable Data" is the next powerful approach and reliable to the Al drones. As we know that drones often generate a huge amount of data – sometimes it produces a large amount of data that we can’t handle at a time. Unmanned Aerial Vehicles (UAVs) are the only possible approach that can add value to our AI-based drone without putting any additional efforts to make UAVs more frequent automation. During search and rescue operations, UAVs played a crucial role over humans. As we know that UAVs can be sent to any desired location without any prior knowledge about the exact conditions in the target area. In this paper, we worked to reduce the number of factors that cause hindrance to the effective deployment of UAVs and increasing the duration of flight duration for the rescue operation. We also use the first Indian microprocessor Shakti class c which is installed in the board Artix-7.


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    Titel :

    RF Controlled Solar Based Robotic Drone


    Beteiligte:
    Chaudhary, Sunil Kumar (Autor:in) / Yadav, Archana (Autor:in) / Sharma, Bipul (Autor:in) / Rouf, Muntaha (Autor:in) / Gupta, Vishal (Autor:in)


    Erscheinungsdatum :

    04.03.2021


    Format / Umfang :

    951570 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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