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Advanced IoT-AI Security System with Drone Surveillance: Campus Smart Security Prototype


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DOI: https://doi.org/10.15866/irea.v11i5.24007

Abstract


People counting and tracking systems are increasingly in demand for surveillance applications. However, current systems suffer from several limitations. They are often centralized, which makes them vulnerable to disruption and difficult to mobilize. This paper presents a cutting-edge smart security system prototype that addresses these limitations. The system is decentralized, by using lightweight algorithms to process images locally on smart cameras. This makes it more reliable and scalable, and it also enables new features such as crowd recognition, noise detection, intruder identification, and people counting. The system is also integrated with the Internet of Things (IoT), Artificial Intelligence (AI), and Unmanned Aerial Vehicle (UAV) technologies to improve further its performance and user experience. For example, the system can use drones to deploy cameras to remote or difficult-to-access locations, and it can use AI to analyze camera data in real time to identify potential threats. The proposed system has been tested on the Hashemite University campus, with cameras placed throughout the campus and a drone station located at the faculty of engineering. The test results have been encouraging, indicating that the system has great potential for improving security in a variety of settings. The paper also investigates and analyzes critical observations made throughout the implementation and testing phases. These observations can be used to guide the development of future security systems.
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Keywords


Smart Security Systems; IoT and AI Integration; Crowd Recognition; Intruder Identification; Smart Camera UAV Technologies; Flight Path Optimization

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References


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