Abstract
The Video Surveillance System is an enhanced version of modern CCTV surveillance. The system is trained using Yolo algorithm to detect the weapons and also is trained using Convolutional Neural Network (CNN) to detect Violence in public places. The system not only detects but also it sends notification to the central control of the system like Police Stations and the police will be able to take necessary actions. The users can also send complaints and use the android application in case of emergency to alert the police if the user is in danger situations. The police will be able to take quick actions using the locations available with the complaint or emergency. By combining CCTV surveillance and weapon detection the system can act as a Central Surveillance System. The system will not record the full video instead take the snapshot of the detected weapons or violence and send it to the admin saving the memory.
References
- Acker, Robin, and Michael Massoth. ” Secure ubiquitous house and facility control solution.”
- An Thanh Trung, Bui, and Nguyen Van Cuong, Monitoring and controlling devices system by GPRS on FPGA platform
- Bajorek, Marcin, and Jedrzej Nowak. ”The role of a mobile device in a home monitoring healthcare system
- Bandi Narasimha Rao and Reddy Sudheer, Surveillance Camera using IoT and Raspberry Pi
- David Gabriel Choqueluque Roman, Guillermo Camara Ch’avez, Violence Detection and Localization in Surveillance Video
- Hoshiyar Singh Kanyal , Mukulit Goel , Amit Singh Tomar , Harshit Kumar Yadav and Koshinder Singh, Object Recognition and Security Improvement by Enhancing the Features of CCTV
- Jinsol Ha, Jinho Park, Heegwang Kim, Hasil Park, and Joonki Paik, Violence Detection for Video Surveillance System
- Karia, Deepak, et al. ”Performance analysis of ZigBee based Load Control and power monitoring system.” Advances in Computing, Communications and Informatics
- Luca, Gabriele, et al. ”The use of NFC and Android technologies to enable a KNX-based smart home.
- Prof. S. B. Kothari , Mr. Vishal Ahirrao , Mr. Manoj Pawar , Mr. Umesh Kapale , Mr. Machindra Arjun, Survey on Smart Security Surveillance System
- Rama Moorthy H , Vijeth Upadhya , Vidyesh V Holla, CNN based Smart Surveillance System: A Smart IoT Application Post Covid- 19 Era
- Saurabh Singh Rajawat, Subhranil Som, Ajay Rana, IoT Based Theft Detection Using Raspberry Pi
- Sharma, Rupam Kumar, et al. ”Android interface based GSM home security system
- Tupakula, Udaya, Vijay Varadharajan, and Sunil Kumar Vuppala. ”Security Techniques for Beyond 22G Wireless Mobile Networks
- Robin Singh Sidhu and Mrigank Sharad, Smart Surveillance System for Detecting Interpersonal Crime