Review Article | ![]()
Intelligent Security Surveillance System for Communities in Areas Adjacent to Abandoned or Vacant Lots with Image Processing Technology
Author(s): Keeradit Saipattalung1, Phatarapon Vorapracha1, Thongchai Thongyoo1*, Sarawut Puttaraksa1, Anantakul Intarapadung1
Published In : International Journal of Electrical and Electronics Research (IJEER) Volume 14, Issue 1
Publisher : FOREX Publication
Published : 10 March 2026
e-ISSN : 2347-470X
Page(s) : 123-135
Abstract
This work presents the development and testing of an intelligent security surveillance system capable of automatically detecting people and flames, with an alert system sending notifications via Telegram Bot. The objective is to increase the efficiency of security in the communities by testing under various environmental conditions at detection ranges from 5 to 30 meters during daylight, low light, and night times, including testing gaits such as slow walking and running. Next, the system was tested in the Rung Sawang Village 1 community, Bang Khen District, Bangkok, which has an area adjacent to a large abandoned or vacant lot. The test results showed that the system was able to detect people in daylight with a maximum similarity percentage of 98.45% at a distance of 5 meters and could detect at a distance of as far as 30 meters in cases involving slow walking. Running was detectable at a distance of 20 meters. During low light hours, the system's efficiency was reduced to 72.31% similarity at a distance of 5 meters with the closest slow walking detectability at 20 meters, while running was detectable within 15 meters. As for flame detection, the system was found to only work at night due to sunlight interference during the day. Candle flames were detectable at distances of 10 meters, and piles of paper were detectable at distances of 25 meters with a similarity percentage of 78.95% at a distance of 5 meters. Next, the notification system via Telegram Bot was tested, yielding average notification speeds ranging from 6.53 to 7.19 seconds. When the system was tested in actual use by measuring user satisfaction among 30 people, it was found that the image resolution from the camera was 4.27 points, followed by the motion detection system at 4.27 points and the suitability of the installation site at 4.13 out of 5 points.
Keywords: Automatic Detection, Surveillance System, Community Safety, Image Processing.
Keeradit Saipattalung, Phatarapon Vorapracha, Thongchai Thongyoo, Sarawut Puttaraksa and Anantakul Intarapadung, Faculty of Industrial Technology, Phranakhon Rajabhat University, Bangkok, Thailand;
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[1] Assessment Report. (2024). Bangkok City Statistics 2023. City Action Plans and Technology Adoption Strategies in Bangkok, Thailand.
-
[2] Chayovan, N. (2022). Spatial Distribution of Bangkok City Government’s Expenditures on Infrastructure Investment. Sarasatr Journal, Vol. 38, No. 2, pp 15–34.
-
[3] Chokchaimadoln, V. (2024). Greater Bangkok: A Solution Proposal for its Urban Governance Effectiveness. International Journal of Development Administration Research, Vol. 7, No. 1, pp 59–72.
-
[4] Korskul, V., Sornmanee, C., Srihong, C., & Buddhahun, S. (2019). New Public Service: A Case Study of Bangkok Metropolitan Administration. Rajapark Journal, Vol. 13, No. 31, pp 55–68.
-
[5] Kim, J., & Park, S. (2023, December 28). Safe City Seoul: AI-powered surveillance using thermal imaging reduces crime by 37%. The Korea Herald. https://www.koreaherald.com/view.php?ud=20231228000551
-
[6] Pan, W., Wang, X., & Huan, W. (2024). EFA-YOLO: An Efficient Feature Attention Model for Fire and Flame Detection. arXiv preprint arXiv:2409.12635. DOI: 10.48550/arXiv.2409.12635
-
[7] Xavier, K. L. B. L., & Nanayakkara, V. K. (2022). Development of an Early Fire Detection Technique Using a Passive Infrared Sensor and Deep Neural Networks. Fire Technology, Vol. 58, pp 3529–3552. DOI: 10.1142/S0218001424500228
-
[8] Bokolo, A. J. (2023). The Role of Community Engagement in Urban Innovation Towards the Co-Creation of Smart Sustainable Cities. Journal of the Knowledge Economy, Vol. 15, No. 1, 1592–1624. DOI: 10.1007/S13132-023-01176-1
-
[9] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788. DOI: 10.48550/arXiv.1506.02640
-
[10] Zhao, Z. Q., Zheng, P., Xu, S. T., & Wu, X. (2019). Object detection with deep learning: A review. IEEE Transactions on Neural Networks and Learning Systems, 30(11), 3212–3232. DOI: 10.1109/TNNLS.2018.2876865
-
[11] Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010). The Pascal Visual Object Classes (VOC) Challenge. International Journal of Computer Vision, Vol. 88, No. 2, pp 303–338. DOI: 10.1007/s11263-009-0275-4
-
[12] Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 580–587. DOI: 10.48550/arXiv.1311.2524
-
[13] Husain, M. A., Tariq, A., Hameed, S., Arif, M. S. B., & Jain, A. (2017). Comparative Assessment of Maximum Power Point Tracking Procedures for Photovoltaic Systems. Green Energy & Environment, Vol. 2, No. 1, pp 5–17. DOI: 10.1016/j.gee.2016.11.001
-
[14] Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., & Berg, A. C. (2016). SSD: Single Shot Multibox Detector. In Proceedings of the European Conference on Computer Vision, pp 21–37. DOI: 10.48550/arXiv.1512.02325
-
[15] Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020). End-To-End Object Detection with Transformers. European Conference on Computer Vision, pp 213–229. DOI: 10.1007/978-3-030-58452-8_13
-
[16] Razykov, T. M., Ferekides, C. S., Morel, D., Stefanakos, E., Ullal, H. S., & Upadhyaya, H. M. (2011). Solar Photovoltaic Electricity: Current Status and Future Prospects. Solar Energy, Vol. 85, No. 8, pp 1580–1608. DOI: 10.1016/j.solener.2010.12.002
-
[17] Deline, C., Meydbray, J., Donovan, M., & Forrest, J. (2012). Partial Shade Evaluation of Distributed Power Electronics for Photovoltaic Systems. National Renewable Energy Laboratory (NREL). DOI: 10.1109/PVSC.2012.6317908
-
[18] Gur, I., & Firat, C. (2025). Assessment of Off-Grid Photovoltaic System Feasibility: A Dual Simulation Approach for Economic Viability and Performance in the Mediterranean Region. Deu Muhendislik Fakultesi Fen ve Muhendislik, Vol. 27, No. 81, pp 499–506. DOI: 10.21205/deufmd.2025278118
-
[19] Srivastava, P., Bajaj, M., & Rana, A. S. (2018). Iot Based Controlling of Hybrid Energy System Using ESP8266. 2018 IEEMA Engineer Infinite Conference (eTechNxT), pp 1–5. DOI: 10.1109/ETECHNXT.2018.8385294
-
[20] Pavithra, D., & Balakrishnan, R. (2015). Iot Based Monitoring and Control System for Home Automation. 2015 Global Conference on Communication Technologies (GCCT), pp 169–173. DOI: 10.1109/GCCT.2015.7342646
-
[21] Al-Masri, E., Diabate, I., Jain, R., Lam, M. H. L., & Nathala, S. R. (2018). A Serverless Iot Architecture for Smart Waste Management Systems. In Proceedings of the IEEE International Conference on Industrial Internet (ICII), pp 179–180. DOI: 10.1109/ICII.2018.00034
-
[22] Vanitha, V., Pasupathi, S., Vadivel, R., & Mohan. K. (2024). Home Automation System Using Telegram Application. International Advanced Research Journal in Science, Engineering and Technology, Vol. 11, No. 9, pp 2394–1588. DOI: 10.17148/IARJSET.2024.11914
-
[23] Akmaludien, R. (2023). Air Quality Prediction System Using Telegram Bot Based on Real-Time Data. Journal of Computation Physics and Earth Science (JoCPES), Vol. 3, No.1, pp 8–15. DOI: 10.63581/JoCPES.v3i1.04
-
[24] Thabassum, S., & Tharannum, N. (2019). Enhancing Communication Reliability in IoT Networks with Machine Learning. Neuroquantology, Vol. 17, No.3, pp 236–248. DOI: 10.48047/nq.2019.17.03.2021
-
[25] Antono, D. R. R., & Suryo. Y. A. (2025). Security System in A Private Room Using Esp32 Microcontroller with Telegram Bot. Journal of Energy and Electrical Engineering, Vol. 6, No.2, pp 151–157. DOI: 10.37058/jeee.v6i2.14951
-
[26] Lalitha, K. V., Chandrika, S. S. R. L. N., Niranjan, M. S., Chowdary, P. K., & Vinay, B. (2025). Smart healthcare monitoring and tracking system using GPS and Telegram technologies with ThingSpeak. International Journal of Creative Research Thoughts (IJCRT), Vol. 13, No.2, pp e91–e96.
-
[27] Mounika, S., Anitha, A., Jayalakshmi, B., & Prabhavathamma, Y. (2019). IoT based plant monitoring system using Telegram bot. Turkish Journal of Computer and Mathematics Education, Vol. 10, No.3, pp 1272–1278. DOI: 10.61841/turcomat.v10i3.14514
-
[28] Garcia-Luna, J., Vargas-Rosales, A., & Lopez-Villaseñor, M. (2020). AI-Enhanced Iot Notification Systems: Current Status and Future Directions. In Proceedings of the IEEE World Forum on Internet of Things (WF-IoT), pp 295–300.
-
[29] Putra, F. P., Sabirin, S., & Soetanto, H. (2025). Prototype of Internet of Things-based control system using Telegram with Bot API method. Syntax Transformation: Journal of Computer Science, Vol. 6, No.2, pp 1–21. DOI: 10.46799/jst.v6i2.1055

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