Authors - Nivedhitaa Ranganathan, Riya Puri, Stuti Patel, Sudhanva M., Sandesh B J Abstract - Crime has grown to become a preeminent issue in today’s society, creating a problem for the common man and governments. There are instances where the felon cannot be convicted due to insufficient evidence and sometimes the incident is not even reported. The current law enforcement agencies lack the manpower and technology to combat this. Here lies the incentive to create a system which once automated, can survey a crime-ridden area to capture footage and on the occurrence of a crime, notify the concerned authorities. The proposed model in this paper contains a drone or UAV which is programmed to monitor a locality or town. The camera on the drone captures the frames in which a crime has occurred and sends selected frames to the server (backend) or the CNN. Post training and testing the CNN model, its core competency is to detect whether a crime has occurred in the frames or images received in near real-time. The images from the UAV are also processed within the drone via the facial recognition module using OpenCV. This framework introduces the integration of a Tello Py DJI drone with a facial recognition module and a Dense-Net 121 convolutional neural network.
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