Raspberry Pi-based intelligent video surveillance system using deep learning.

The Intelligent Surveillance System is a concept that is used to provide support and alert measures to individuals in their homes and businesses. Closed Circuit Television (CCTV) surveillance is employed in business sectors such as jewelry stores and banks all of the time; when theft occurs, the CCTV recordings will be used only for future investigations and will not alert anybody about the theft. When a theft occurs in specific locations such as malls, jewelry stores, vacations, and so on, the suggested work can notify people via SMS and Gmail. The Raspberry Pi will be connected to a standard CCTV camera that will be installed at the selected location. As a result, if a person is discovered at a specific location at a specific time, the user receives an alert message. The real-time object recognition system with the Linux operating system is used to recognize items with a two-dimensional input (Video), where it will detect and show real-time objects based on the environment and surroundings. Mobile Nets creates a real-time project to detect the object for which a frame was created and the object's accuracy was shown. The frame shifts in response to the actions of the objects. It has proven a more accurate real-time alerting tool for the user. Our findings show that in the actual world, the proposed method may be used to build a tracking system with intelligent security and minimal cost. [ABSTRACT FROM AUTHOR]