Design and Implementation of an IoT System for Indoor Measurement and Monitoring Fire and Gas Warning

Nguyen Van Tri; Le Hung Manh; Ha Duyen Trung

doi:10.12928/biste.v6i2.11254

Authors

Nguyen Van Tri Hanoi University of Science and Technology
Le Hung Manh Vietnam National Defense Television
Ha Duyen Trung Hanoi University of Sciene and Technology

DOI:

https://doi.org/10.12928/biste.v6i2.11254

Keywords:

IoT, ESP32 Processor, SIM900a, MQ2 Gas Sensor, DHT11 Sensor, Flame Sensor, Fire and Gas Warning

Abstract

Early detection and warning of fires occurring in homes is crucial to prevent loss of life and property. Fires can happen anywhere and at any time, but the presence of fire alarms helps keep homes safe. Therefore, early detection of fires will prove to be crucial as it could mean the difference between life and death. Most recently, the Internet of Things (IoT) technology has been deploying for data collection, transmission, storage and processing of large amounts of data from various sensor devices. Through the Internet, these sensors can be linked and help us manipulate or collect data from them. In this paper, we will use various types of sensors to sense the presence of fire and gas in the design and implementation of a completed IoT system. The designed IoT system aims to alert and assist homeowners, building guards, and firefighters about the presence of fire and gas leaks. Additionally, a common preventive solution is to install a sprinkler to spray water when the smoke sensor detects a fire. The designed system has been successfully implemented and tested in a variety of circumstances in an education bulding of University.

References

V. H. Vu, “Financial Services in Vietnam,” The Economy and Business Environment of Vietnam, pp. 111-132, 2020, https://doi.org/10.1007/978-3-030-49974-7_6.

K. A. Nguyen, Y. A., Liou, and J. P. Terry, “Vulnerability of Vietnam to typhoons: A spatial assessment based on hazards, exposure and adaptive capacity,” Science of the Total Environment, vol. 682, pp. 31-46, 2019, https://doi.org/10.1016/j.scitotenv.2019.04.069.

M. Aram, X. Zhang, D. Qi, and Y. Ko, “A state-of-the-art review of fire safety of photovoltaic systems in buildings,” Journal of Cleaner Production, 308, 127239, 2021, https://doi.org/10.1016/j.jclepro.2021.127239.

M. McNamee et al., “IAFSS agenda 2030 for a fire safe world,” Fire Safety Journal, vol. 110, p. 102889, 2019, https://doi.org/10.1016/j.firesaf.2019.102889.

A. Gaur, A. Singh, A. Kumar, K. S. Kulkarni, S. Lala, K. Kapoor, V. Srivastava, A. Kumar, and S. C. Mukhopadhyay, “Fire sensing technologies: A review,” IEEE Sensors Journal, vol. 19, no. 9, pp. 3191–3202, 2019, https://doi.org/10.1109/JSEN.2019.2894665.

E. Maltezos, K. Petousakis, A. Dadoukis, L. Karagiannidis, E. Ouzounoglou, M. Krommyda, et al., A smart building fire and gas leakage alert system with edge computing and NG112 emergency call capabilities, Information, 13, 164, 2022, https://doi.org/10.3390/info13040164.

J.-.S. Chou, M.-.Y. Cheng, Y.-.M. Hsieh, I.-.T. Yang, H.-.T Hsu, “Optimal path planning in real time for dynamic building fire rescue operations using wireless sensors and visual guidance,” Autom. Constr. 99, pp. 1–17, 2019, https://doi.org/10.1016/j.autcon.2018.11.020.

Intelligent multi-sensor detection system for monitoring indoor building fires, IEEE Sens. J. 21, pp. 27982–27992, 2021, https://doi.org/10.1109/JSEN.2021.3124266.

C. Su, W. Chen, “Design of remote real-time monitoring and control management system for smart home equipment based on wireless multihop sensor network,” J. Sensors 2022, pp. 1–10, 2022, https://doi.org/10.1155/2022/6228440.

A. Mukherjee, S. K. Shome, and P. Bhattacharjee, “Survey on internet of things based intelligent wireless sensor network for fire detection system in building,” in Communication and Control for Robotic Systems.

Springer, pp. 193–200, 2022, https://doi.org/10.1007/978-981-16-1777-5_12.

Aalsalem, M. Y., Khan, W. Z., Gharibi, W., Khan, M. K., & Arshad, Q., “Wireless Sensor Networks

in oil and gas industry: Recent advances, taxonomy, requirements, and open challenges,” Journal of network and

computer applications, vol. 113, pp. 87-97, 2018, https://doi.org/10.1016/j.jnca.2018.04.004.

S. Kamel, A. Janal, K. Omri, and M. Shayyat, “An IoT-based Fire Safety Management System for Education Buildings: A Case Study,” (IJACSA) International Journal of Advanced Computer Science and Applications,

vol. 13, no. 7, pp. 765-771, 2022, https://doi.org/10.14569/IJACSA.2022.0130789.

S. K. Mekni, “Design and implementation of a smart fire detection and monitoring system based on IoT,” in: 4th Int. Conf. Appl. Autom. Ind. Diagnostics, vol. 1, pp. 1–5, 2022, https://doi.org/10.1109/ICAAID51067.2022.9799505.

G. Cavalera, R.C. Rosito, V. Lacasa, M. Mongiello, F. Nocera, L. Patrono, et al., “An innovative smart system based on IoT technologies for fire and danger situations,” in: 2019 4th Int. Conf. Smart Sustain. Technol., IEEE, pp. 1–6, 2019, https://doi.org/10.23919/SpliTech.2019.8783059.

M. Mongiello et al., “A smart IoT-aware system for crisis scenario management,” J. Commun. Softw. Syst. 14, pp. 91–98, 2018, https://doi.org/10.24138/jcomss.v14i1.533.

P. Kanakaraja, P. S. Sundar, N. Vaishnavi, S. G. K. Reddy, and G. S. Manikanta, “IoT enabled advanced forest fire detecting and monitoring on ubidots platform,” Materials Today: Proceedings, vol. 46, pp. 3907–3914, 2021, https://doi.org/10.1016/j.matpr.2021.02.343.

I. H. Sarker, “Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective,” SN Computer Science, vol. 2, no. 5, p. 377, 2021, https://doi.org/10.1007/s42979-021-00765-8.

M. Mahbub, M. M. Hossain, and M. S. A. Gazi, “Cloud-enabled iot based embedded system and software for intelligent indoor lighting, ventilation, early stage fire detection and prevention,” Computer Networks, vol. 184, p. 107673, 2021, https://doi.org/10.1016/j.comnet.2020.107673.

H.D. Trung, “An IoT System Design for Industrial Zone Environmental Monitoring Systems,” in: Hybrid Intelligent Systems (HIS 2022), Lecture Notes in Networks and Systems, vol. 647, 2023, https://doi.org/10.1007/978-3-031-27409-1_4.

A. Rehman, M. A. Qureshi, T. Ali, M. Irfan, S. Abdullah, S. Yasin, U. Draz, A. Glowacz, G. Nowakowski, A. Alghamdi et. al., “Smart fire detection and deterrent system for human savior by using internet of

things (IoT),” Energies, vol. 14, no. 17, p. 5500, 2021, https://doi.org/10.3390/en14175500.

M. Mukhiddinov, A.B. Abdusalomov, J. Cho, “Automatic fire detection and notification system based on improved YOLOv4 for the blind and visually impaired,” Sensors 22, 3307, 2022, https://doi.org/10.3390/s22093307.

V. Barral Vales, O. C. Fernández, T. Domínguez-Bolaño, C. J. Escudero and J. A. García-Naya, "Fine Time Measurement for the Internet of Things: A Practical Approach Using ESP32," in IEEE Internet of Things Journal, vol. 9, no. 19, pp. 18305-18318, 1 Oct.1, 2022, https://doi.org/10.1109/JIOT.2022.3158701.

S. Mukherjee, A. Ghosh and S. K. Sarkar, "Arduino based Wireless Heart-rate Monitoring system with Automatic SOS Message and/or Call facility using SIM900A GSM Module," 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), pp. 1-5, 2019, https://doi.org/10.1109/ViTECoN.2019.8899504.

I. K. N. Trisnawan, A. N. Jati, N. Istiqomah and I. Wasisto, "Detection of Gas Leaks Using The MQ-2 Gas Sensor on the Autonomous Mobile Sensor," 2019 International Conference on Computer, Control, Informatics and its Applications (IC3INA), pp. 177-180, 2019, https://doi.org/10.1109/IC3INA48034.2019.8949597.

G. M. Debele and X. Qian, "Automatic Room Temperature Control System Using Arduino UNO R3 and DHT11 Sensor," 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp. 428-432, 2020, https://doi.org/10.1109/ICCWAMTIP51612.2020.9317307.

D. Hercog, T. Lerher, M. Truntič, and O. Težak, “Design and implementation of ESP32-based IoT devices,” Sensors, vol. 23, no. 15, p. 6739, 2023, https://doi.org/10.3390/s23156739.

M. R. Johnson, D. R. Tyner, and A. J. Szekeres, “Blinded evaluation of airborne methane source detection using Bridger Photonics LiDAR,” Remote Sensing of Environment, vol. 259, p. 112418, 2021, https://doi.org/10.1016/j.rse.2021.112418.