In this paper, our objective is to devise a new defence mechanism using automation, which will seek to provide a viable solution to tighten the security around the border areas and simultaneously reduce the burden on soldiers. With the help of automation, we can increase the efficiency of safeguarding our borders in remote areas to a great extent, and this will also result in a better quality of surveillance due to this technological intervention. The main focus for us will be in the creation of an active and real-time device for the armed forces, which will help safeguard the relatively remote border areas where human mobility is restricted. The devised mechanism will consist of three modules: face detection of a human intruder, wireless communication, and hardware detection of an intruder. The automation system in this defence mechanism majorly consists of face detection of a human intruder, which is supported and complemented by Ultrasonic and IR Sensors. This system is implemented using Arduino microcontroller, which will be complemented with NodeMCU to provide necessary wireless communication for sending intruder detection and location information to the cloud, which will trigger the gun to shoot down the enemy. The use of wireless communication over GSM is preferred solely because the control stations receive Wi-Fi signals directly from the satellite, which is very reliable and fast. The main application of our research work is to ensure safeguarding border region around remote areas where patrolling is difficult for army personnel and will be implemented by the armed forces. Keywords: face detection, human intruder, wireless communication, cloud.


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    Titel :

    Automatic Gun Targeting System using Face Detection, IR and Ultra Sonic Sensor



    Erscheinungsdatum :

    2020-06-30


    Anmerkungen:

    oai:zenodo.org:5547091
    International Journal of Engineering and Advanced Technology (IJEAT) 9(5) 389-393



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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