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Smart environments are environments where digital devices are connected toeach other over the Internet and operate in sync. Security is of paramountimportance in such environments. This paper addresses aspects of authorizedaccess and intruder detection for smart environments. Proposed is PiBase, anInternet of Things (IoT)-based app that aids in detecting intruders andproviding security. The hardware for the application consists of a RaspberryPi, a PIR motion sensor to detect motion from infrared radiation in theenvironment, an Android mobile phone and a camera. The software for theapplication is written in Java, Python and NodeJS. The PIR sensor and Pi cameramodule connected to the Raspberry Pi aid in detecting human intrusion. Machinelearning algorithms, namely Haar-feature based cascade classifiers and LinearBinary Pattern Histograms (LBPH), are used for face detection and facerecognition, respectively. The app lets the user create a list of non-intrudersand anyone that is not on the list is identified as an intruder. The app alertsthe user only in the event of an intrusion by using the Google Firebase CloudMessaging service to trigger a notification to the app. The user may choose toadd the detected intruder to the list of non-intruders through the app to avoidfurther detections as intruder. Face detection by the Haar Cascade algorithmyields a recall of 94.6%. Thus, the system is both highly effective andrelatively low cost.

PiBase: An IoT-based Security System using Raspberry Pi and Google Firebase