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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
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| Paper Title: | HawkEye - AI-Powered Smart Intruder Detection System: Building NextGen Surveillance with OpenCV |
| Authors Name: | Siddesh S K , Prajwal D , Srujan D J , Shravan M S |
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IJRTI_208088
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| Published Paper Id: | IJRTI2512109 |
| Published In: | Volume 10 Issue 12, December-2025 |
| DOI: | |
| Abstract: | Traditional surveillance systems are having more and more problems because they rely on fixed motion detectors and often give false alarms, which makes them less useful for real security purposes. This study presents an Intelligent Intruder Detection System that integrates motion detection, facial recognition, and automated alerting capabilities within a unified, real-time surveillance framework. The solution uses OpenCV based background subtraction methods to find movement patterns. It also has a facial encoding part that uses an advanced deep-learning recognition engine to create 128-dimensional face representations. A K-Nearest Neighbor algorithm is used to tell the difference between authorized personnel and people who shouldn't be there. If the system sees someone it doesn't know or sees behavior that seems suspicious, it sends out a full alert, including emails and sound based warnings. A thorough evaluation over many test sessions shows that the system consistently detects intruders and recognizes them reliably, all while keeping processing delays to a minimum so that it can be used in real time. This solution offers a flexible, effective way to manage advanced residential and commercial security through its component-based architecture, adjustable parameter settings, and activity recording system. |
| Keywords: | Smart Intruder Detection, Motion Detection, Face Recognition, OpenCV, Background Subtraction, Facial Embeddings, K-Nearest Neighbor (KNN), Real-Time Surveillance, Automated Alerts, Security Systems, Computer Vision, Intruder Classification. |
| Cite Article: | "HawkEye - AI-Powered Smart Intruder Detection System: Building NextGen Surveillance with OpenCV", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.b97-b104, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512109.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 |
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Published Paper ID: IJRTI2512109
Registration ID:208088
Published In: Volume 10 Issue 12, December-2025
DOI (Digital Object Identifier):
Page No: b97-b104 Country: Bangalore, Karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2512109 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2512109 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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