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

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

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S. D. T. Kelly, N. K. Suryadevara, and S. C. Mukhopadhyay, Towards the implementation of IoT for environmental condition monitoring in homes, IEEE Sens J, vol. 13, no. 10, pp. 3846-3853, 2013.

P. Chakraborty and S. Sultana, IoT-based smart home security and automation system, in Micro-Electronics and Telecommunication Engineering: Proceedings of 5th ICMETE 2021, Springer, 2022, pp. 497-505.

N. Surantha and W. R. Wicaksono, Design of smart home security system using object recognition and PIR sensor, Procedia Comput Sci, vol. 135, pp. 465-472, 2018.

P. Jiang, D. Ergu, F. Liu, Y. Cai, and B. Ma, A Review of Yolo algorithm developments, Procedia Comput Sci, vol. 199, pp. 1066-1073, 2022.

R. Huang, J. Pedoeem, and C. Chen, YOLO-LITE: a real-time object detection algorithm optimized for non-GPU computers, in 2018 IEEE international conference on big data (big data), 2018, pp. 2503-2510.

Espressi Systems, ESP 32. 2023. [Online]. Available:

M. Hayajneh and A. Al Mahasneh, Guidance, Navigation and Control System for Multi-Robot Network in Monitoring and Inspection Operations, Drones, vol. 6, no. 11, p. 332, 2022.

M. Hayajneh, M. Momani, and A. Al-ghazo, UAV coverage path optimization for collecting fine-grained distribution of air samples, in 2023 International Conference on Control, Automation and Diagnosis (ICCAD), 2023, pp. 1-6.

P. R. Nehete, J. P. Chaudhari, S. R. Pachpande, and K. P. Rane, Literature survey on door lock security systems, Int J Comput Appl, vol. 153, no. 2, pp. 13-18, 2016.

C. Yadav, Iot based surveillance system and home automation, Int Res J Eng Technol, vol. 5, no. 5, pp. 2031-2036, 2018.

A. Sarker, P. Chakraborty, S. M. S. Sha, M. Khatun, M. R. Hasan, and K. Banerjee, Improvised technique for analyzing data and detecting terrorist attack using machine learning approach based on twitter data, Journal of Computer and Communications, vol. 8, no. 7, pp. 50-62, 2020.

S. Pawar, V. Kithani, S. Ahuja, and S. Sahu, Smart home security using IoT and face recognition, in 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), 2018, pp. 1-6.

J. Wang, J. Zheng, S. Zhang, J. He, X. Liang, and S. Feng, A face recognition system based on local binary patterns and support vector machine for home security service robot, in 2016 9th international symposium on computational intelligence and design (ISCID), 2016, pp. 303-307.

I. Yugashini, S. Vidhyasri, and K. G. Devi, Design and implementation of automated door accessing system with face recognition, International Journal of Science and Modern Engineering (IJISME), vol. 1, no. 12, 2013.

O. Taiwo, A. E. Ezugwu, O. N. Oyelade, and M. S. Almutairi, Enhanced intelligent smart home control and security system based on deep learning model, Wirel Commun Mob Comput, vol. 2022, pp. 1-22, 2022.

P. B. Balla and K. T. Jadhao, IoT based facial recognition security system, in 2018 International Conference on smart city and emerging technology (ICSCET), 2018, pp. 1-4.

M. V. D. Prasad, N. S. Kiran, and others, Video surveillance-based security system using OpenCV and Arduino uno, NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal| NVEO, pp. 1522-1528, 2021.

A. Pawar and A. Lahane, Design and Implementation of IoT based Smart Surveillance, International Journal of Engineering Research and, vol. 9, 2020.

B. N. Rao and R. Sudheer, Surveillance camera using IOT and Raspberry Pi, in 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA), 2020, pp. 1172-1176.

Noersasongko, E., Shidik, G., Nugraha, A., Andono, P., Kusuma, E., Automatic Integration of Ubiquitous Access Address in Camera Surveillance System Using Natural Language Processing, (2021) International Review on Modelling and Simulations (IREMOS), 14 (1), pp. 70-78.

C. Stolojescu-Crisan, C. Crisan, and B.-P. Butunoi, Access control and surveillance in a smart home, High-Confidence Computing, vol. 2, no. 1, p. 100036, Mar. 2022.

P. Y. Ingle and Y.-G. Kim, Real-Time Abnormal Object Detection for Video Surveillance in Smart Cities, Sensors, vol. 22, no. 10, p. 3862, May 2022.

S. Nikkath Bushra, G. Shobana, K. Uma Maheswari, and N. Subramanian, Smart Video Survillance Based Weapon Identification Using Yolov5, in 2022 International Conference on Electronic Systems and Intelligent Computing (ICESIC), IEEE, Apr. 2022, pp. 351-357.

Uc Ríos, C., Teruel, P., Use of Unmanned Aerial Vehicles for Calibration of the Precision Approach Path Indicator System, (2021) International Review of Aerospace Engineering (IREASE), 14 (4), pp. 192-200.

Szabo, S., Železník, V., Mako, S., Rabatin, R., Kinematics of Exploration Using Unmanned Aerial Vehicles, (2022) International Review of Aerospace Engineering (IREASE), 15 (5), pp. 244-253.


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