Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
There has been a big rise in the need for smart surveillance systems in the last few years because people are worried about security in both public and private places. Conventional surveillance systems depend significantly on ongoing human oversight, which is ineffective, labor-intensive, and susceptible to mistakes. This project offers an AI-based embedded vision system for smart intelligent surveillance, utilizing a Raspberry Pi 4 and OpenCV, to address these constraints. The proposed system will use a webcam to automatically find people and spot suspicious activities in real time. The system processes live video streams, takes frames out of them, and uses computer vision techniques to find people. Further, machine learning models are utilized to classify activities such as fighting, robbery, and normal behavior. The datasets used for training the model are obtained from Kaggle, ensuring improved accuracy and performance.
"AI Based Embedded Vision System for Real-Time Intelligent Surveillance (IoT Enabled)", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b613-b619, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604220.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator