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Eagle Eye: An AI Based Indoor Surveillance and Security System

Dr. H. Jayasree1, A. Sanjana2, K. Nandini3, E. Nishanth4, P. Saivignesh5
1Professor, Department of CSE(AI&ML), Jyothishmathi Institute of Technology and Science, Telangana, India,
jayasaree@gmail.com
2Student, Department of CSE(AI&ML), Jyothishmathi Institute of Technology and Science, Telangana, India,
sanjanaaddagunta@gmail.com
3Student, Department of CSE(AI&ML), Jyothishmathi Institute of Technology and Science, Telangana, India,
22271a6622nandinikatta@gmail.com
4Student, Department of CSE(AI&ML), Jyothishmathi Institute of Technology and Science, Telangana, India,
nishanthedla@gmail.com
5Student, Department of CSE(AI&ML), Jyothishmathi Institute of Technology and Science, Telangana, India,
saivigneshpoloju009@gmail.com

Abstract— It is becoming more difficult to ensure the safety of indoor spaces like commercial, office, and residential settings with the constraints of traditional methods of surveillance. Most currently available systems act as passive monitoring systems, relying immensely on human operators to analyze the recorded video, which causes delayed reactions to critical events in many cases. Eagle Eye, an indoor security system that is smart and active in assessing indoor potential threats through live visual and acoustic data, is presented in this research. The system is designed to monitor real-time inputs from cameras and microphones in order to identify suspicious behavioural patterns such as hidden faces,stationary location, as well as thre*atening or distress speech.The system uses a fuzzy logic decision-making mechanism to identify a cumulative Robbery Probability Score in order to determine risk levels. As soon as a risk threshold is surpassed,an alert message is sent to authorized users. The system is computationally efficient and cost-effective in that it does not necessarily require high-performance processing hardware.
Index Terms— Indoor surveillance, Threat Prediction, Fuzzylogic, Robbery Potential Score, Alert Generation