AI-Enabled Robotic Surveillance System for Critical Infrastructure

Traditional monitoring approaches often experience blind spots and high resource utilization at such a crucial time of security. In our study, we design a small-scaled autonomous vehicle model with smart sensors that is to be equipped with an AI model in a Raspberry Pi for effective and reliable sel...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2025 Emerging Technologies for Intelligent Systems (ETIS) s. 1 - 7
Hlavní autori: Thankappan, Manesh, Nataraj, Neetha K, K S, Divya, Jayaraj, Akshaya, Joby, Alen, Asokan, Abhilash
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 07.02.2025
Predmet:
Accuracy
Anomaly detection
CNN
Critical infrastructure
Explosions
Intelligent sensors
Mask R-CNN
One class detection
R-CNN
Real-time systems
Robots
Security
Spatio Temporal autoencoders
Surveillance
Surveillance system
Videos
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Traditional monitoring approaches often experience blind spots and high resource utilization at such a crucial time of security. In our study, we design a small-scaled autonomous vehicle model with smart sensors that is to be equipped with an AI model in a Raspberry Pi for effective and reliable self-sustained monitoring of critical infrastructure to overcome the problems. The core AI model was specifically designed to detect in real-time anomalies such as a fire, a fight, vandalism, explosion, etc. The AI model is a modified version of an open source repository available on github named "Real-world Anomaly Detection in Surveillance Videos (pytorch) [11]". This technology ensures speedy response time by stopping the vehicle, starting video recording, and forwarding the real-time footage to security personnel upon detecting an anomaly. This innovative solution allows for mobilization and cost-effectiveness, improving surveillance coverage, and diminished dependence on constant human oversight. Exploiting advances in artificial intelligence and robotics, the project delivers a scalable real-time monitoring system deployable into a wide range of critical infrastructure environments. This initiative represents practical application of AI towards improving public safety and building a stronger security posture in facilities that house critical infrastructure.
DOI:10.1109/ETIS64005.2025.10960891