Abstract
In this ever-growing world of automation and digitization, where data is a pivotal element for the growth of every individual, institution, and organization, whether digital or physical, data could also be the reason for destruction, if acquired by an antagonist through unconventional access. Data is a very sensitive point in all the domains ranging from an individual’s personal space to tactical military centers such as defense institutions, military matters, financial institutions, hospitals, and educational institutions. Thus, it is necessary to protect the data from intruders. Physical Intruder Detection is equally important as the detection of intrusion in computer networks. Though the later is always digital and without manual intervention. Physical Intruder Detection can be either digital or done manually. The paper presents a system for an enclosed area, based on IoT and supported by Digital Image Processing, to capture any Physical Intruder who breaches the security system and alert the rightful person regarding the intrusion. The approach uses the PIR motion sensor to detect any suspicious activity, turn on the webcam and with the help of Face Recognition System using Digital Image Processing, recognizes whether it is the rightful person or not. If it is an Intruder, then the webcam will start recording the activity of the Intruder and send a text message as well as an email to the system owner alerting him/her/them about the intrusion. A link to this live feed to the system owner is also attached to the alert message and mail. This Intruder Detection System is energy efficient as well because the webcam will be turned on only when the motion sensor detects any suspicious activity.
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Kasar, S., Kshirsagar, V., Bokan, S., Rathod, N. (2020). Smart Physical Intruder Detection System for Highly Sensitive Area. In: Zhang, YD., Mandal, J., So-In, C., Thakur, N. (eds) Smart Trends in Computing and Communications. Smart Innovation, Systems and Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-15-0077-0_23
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DOI: https://doi.org/10.1007/978-981-15-0077-0_23
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