Yarlagadda, Syamala and Nalluru, Niharika and Tirumalasetti, Santhi Swaroop and Uppuluri, Mounika and Akhil Perumprath, AnilKumar (2025) NoIR Camera Based Security Surveillance System. International Journal of Innovative Science and Research Technology, 10 (4): 25apr589. pp. 178-184. ISSN 2456-2165
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Abstract
The NoIR Camera-Based Raspberry Pi Security system is an adaptive, intelligent security system that provides efficient, low-light monitoring. It reduces false alarms by using infrared sensitivity to provide day-and-night monitoring with advanced motion detection that can differentiate between objects, including people and animals. This technology is ideal for home security, animal tracking, and restricted access surveillance because it uses local, on-device processing to ensure data privacy, real-time responsiveness, and IoT integration for remote moni- toring. TensorFlow, which is adapted to run on the Raspberry Pi with TensorFlow Lite, is used in this system for object detection and identification. Effective edge processing is made possible by TensorFlow’slightweight models, which are essential for reducing latency and optimizing data privacy. Effective surveillance in low light and at night is made possible by the combination of NoIR imaging with AI-driven object detection. Future developments involve building a scalable network for wider industrial use, extending classification categories and using advanced facial recognition. Adaptability and security characteristics could be further enhanced with more cloud analytics and a deeper IoT integration.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 16 Apr 2025 12:07 |
Last Modified: | 16 Apr 2025 12:07 |
URI: | https://eprint.ijisrt.org/id/eprint/423 |