IoT Based Smart Alert Network Security System Using Machine Learning

Anas Habib Zuberi , Shish Ahmad

doi:10.55524/ijircst.2023.11.4.4

Abstract

The increasing security threats in public places such as airports, train stations, and shopping malls require the development of smart security systems that can detect potential threats and provide timely alerts to security personnel. This research paper proposes an IoT-based smart alert network security system using machine learning to enhance public safety. The system integrates various sensors and devices that collect data such as motion, which is analyzed using machine learning algorithms to detect anomalies and trigger alerts if any suspicious activity is detected. The proposed system achieves an accuracy rate of 91.12% in detecting suspicious activities, which is significantly higher than the existing security systems used in public places. The system can provide real-time alerts, which can reduce the response time of security personnel and prevent potential security threats. The proposed system can be implemented in various public places to enhance public safety and prevent security breaches. The results of this research paper provide a useful reference for future studies on the development of smart security systems using IoT and machine learning technologies.

Keywords

Cloud, Face Recognition, KNN, IOT, Network

References

Elazig, TURKEY (2018): A face recognition method in the Internet of Things for security applications in smart homes and cities, https://ieeexplore.ieee.org/abstract/document/8408934
Mr. Jay R. Bhagat, Miss. Santoshi G. Tondare, Miss. Pallavi M. Atram, Mr. Nitin R. Upadhyay, Mr. Rushikesh D. Nachane, Prof. Kiran L. Chavhan (2019): A Survey on Surveillance using Facial Recognition https://www.ijert.org/research/a-survey-on-surveillance-using-facial-recognition-IJERTV8IS100093.pdf
Simone Diniz Junqueira Barbosa, Phoebe Chen, Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Krishna M. Sivalingam, Dominik ?l?zak, Takashi Washio, Xiaokang Yang, and Junsong Yuan (2020): Real-Time Biometric System for Security and Surveillance Using Face Recognition https://link.springer.com/chapter/10.1007/978-981-15-6634-9_27
Medapati, Prema Kumar; Tejo Murthy, P.H.S.; Sridhar, K.P. (2019). Lamstar: For IoT?Based Face Recognition System To Manage The Safety Factor In Smart Cities https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.3843
Tanweer Alam (2021): Cloud-Based IoT Applications and Their Roles in Smart Cities https://www.mdpi.com/2624-6511/4/3/64
Pandimurugan; Anmol Jain;Yash Sinha; (2020). IoT based Face Recognition for Smart Applications using Machine Learning https://ieeexplore.ieee.org/abstract/document/9316089
Masud, M., Muhammad, G., Alhumyani, H., Alshamrani, S. S., Cheikhrouhou, O., Ibrahim, S., & Hossain, M. S. (2020). Deep learning-based intelligent face recognition in IoT-cloud environment https://www.sciencedirect.com/science/article/abs/pii/S0140366419312988
Mallikharjuna Raoa, Haseena Palleb, Pragna Dasaric , Shivani Jannaikode (2021) : Implementation of Low Cost IoT Based Intruder Detection Systemby Face Recognition using Machine Learning https://turcomat.org/index.php/turkbilmat/article/view/8295
Ilhan aydin, Nashwan Adnan Othman (2017) : A New Iot Combined Face Detection Of People By Using Computer Vision For Security Application https://ieeexplore.ieee.org/abstract/document/8090171
Neda Fatima;Salman Ahmad Siddiqui;Anwar Ahmad; (2021). IoT based Border Security System using Machine Learning https://ieeexplore.ieee.org/abstract/document/9484934
Kumar, V., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Intelligent cyber-physical security framework for IoT-based smart cities. Journal of Ambient Intelligence and Humanized Computing, 11(10), 4259-4282. https://link.springer.com/article/10.1007/s12652-020-02485-3
Park, S., Kim, Y. S., & Jeong, H. (2019). A deep learning-based indoor security system for public places using IoT. Journal of Ambient Intelligence and Humanized Computing, 10(6), 2315-2324. https://link.springer.com/article/10.1007/s12652-018-1083-6
Shih, T. Y., Lin, W. H., Wu, C. H., & Chen, C. H. (2019). A Smart Surveillance System Based on Deep Learning for Public Safety Monitoring. IEEE Transactions on Consumer Electronics, 65(4), 430-438. https://ieeexplore.ieee.org/abstract/document/8715574
Jha, M. K., & Singh, M. K. (2018). Internet of Things (IoT)-Based Smart Security and Monitoring Systems for Critical Infrastructure: A Review. IEEE Sensors Journal, 18(23), 9603-9620. https://ieeexplore.ieee.org/abstract/document/8465745
Ayyagari, M., & Rana, N. P. (2020). A systematic review of the Internet of Things (IoT) in the context of smart cities: challenges and opportunities. Journal of Ambient Intelligence and Humanized Computing, 11(6), 2485-2515. https://link.springer.com/article/10.1007/s12652-019-01371-w

Cites this article as

[Anas Habib Zuberi , Shish Ahmad (2023), IoT Based Smart Alert Network Security System Using Machine Learning , International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-11, Issue-4, Page No-15-22], (ISSN 2347 - 5552). www.ijircst.org

Corresponding Author

Anas Habib Zuberi

Research Scholar, Department of Computer Science and Engineering, Integral University, Lucknow, India

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