Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm

  • Ni Gusti Ayu Dasriani Universitas Bumigora, Mataram, Indonesia
  • Sirojul Hadi Universitas Bumigora, Mataram, Indonesia
  • Moch Syahrir Universitas Bumigora,Mataram, Indonesiao
Keywords: Building fire safety, Intelligent system, Internet of things, Na¨ıve Bayes, Telegram


Population growth is increasing every year. Population growth causes an increase in population density in a country. The largest population density is in urban areas. Fires in a city with a high population density will potentially cause greater damage. Material and non-material losses due to fire can be caused by not functioning maximally early warning systems, especially fire detection. In addition, other factors, such as system errors in detecting fires, can potentially cause fires. This research aims to build an intelligent system that can minimize building fire detection errors to reduce user material losses. The intelligent system can classify fire potential into four classifications, namely ”very dangerous,” ”dangerous,” ”alert,” and ”safe.” The method used in this research is Research and Development (R&D) with artificial intelligence using the Na¨ıve Bayes method, which has been integrated with the Internet of Things (IoT). This research shows that the Na¨ıve Bayes algorithm can be used to classify fire potential, proven by the overall system testing accuracy of 93.33% with an error of 6.77%.


Download data is not yet available.


[1], “Population in The World,” 2020.
[2] N. Brushlinsky, M. Ahrens, S. Sokolov, and P. Wagner, “World Fire Statistics,” in International Association of Fire and Rescue
Service, 2020, pp. 1–67.
[3] BNPB, “Geo Portal data bencana di Indonesia.”
[4] Y. C. Nam and Y. Nam, “A low-cost fire detection system using a thermal camera,” KSII Transactions on Internet and Information
Systems, vol. 12, no. 3, pp. 1301–1314, 2018.
[5] F. Saeed, A. Paul, A. Rehman, W. H. Hong, and H. Seo, “IoT-Based intelligent modeling of smart home environment for fire
prevention and safety,” Journal of Sensor and Actuator Networks, vol. 7, no. 1, pp. 1–16, 2018.
[6] D. H. Kang, M. S. Park, H. S. Kim, D. Y. Kim, S. H. Kim, H. J. Son, and S. G. Lee, “Room Temperature Control and
Fire Alarm/Suppression IoT Service Using MQTT on AWS,” International Conference on Platform Technology and Service,
PlatCon 2017 - Proceedings, 2017.
[7] R. A. Sowah, K. Apeadu, F. Gatsi, K. O. Ampadu, and B. S. Mensah, “Hardware Module Design and Software Implementation
of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs),”
Journal of Engineering (United Kingdom), vol. 2020, 2020.
[8] A. Sol´orzano, J. Eichmann, L. Fern´andez, B. Ziems, J. M. Jim´enez-Soto, S. Marco, and J. Fonollosa, “Early fire detection based
on gas sensor arrays: Multivariate calibration and validation,” Sensors and Actuators B: Chemical, vol. 352, pp. 1–16, 2022.
[9] E. Lule, C. Mikeka, A. Ngenzi, and D. Mukanyiligira, “Design of an IoT-based fuzzy approximation prediction model for early
fire detection to aid public safety and control in the local urban markets,” Symmetry, vol. 12, no. 9, pp. 1–29, 2020.
[10] X. Shi and L. Songlin, “Design and Implementation of a Smart Wireless Fire-Fighting System Based on NB-IoT Technology,”
in Journal of Physics: Conference Series, vol. 1606, no. 1, 2020.
[11] Y. Ma, X. Feng, J. Jiao, and Z. Peng, Smart Fire Alarm System with Person Detection and Thermal Camera. Springer
International Publishing, vol. 1.
[12] M. J. Sousa, A. Mountinho, and M. Almeida, “Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and
Monitoring Systems,” pp. 1–29, 2020.
[13] M. A. Hossain, H. S. Roy, M. F. K. Khondakar, M. H. Sarowar, and A. Hossainline, “Design and Implementation of an IoT Based
Firefighting and Affected Area Monitoring Robot,” in International Conference on Robotics, Electrical and Signal Processing
Techniques, no. January, 2021, pp. 552–556.
[14] M. Devi, S. Parthasarathy, B. Mahalakshmi, and E. Sathyamoorthy, “IoT Based Fire Fighting Robot,” vol. 07, no. 11, pp.
7722–7729, 2020.
[15] M. B. Vyshnavi, A. Satheesh, S. S. S, and L. C. Manikandan, “IoT Technology Based Fire-Fighter Robot,” vol. 6, no. 3, pp.
934–941, 2020.
[16] A. Anggrawan, S. Hadi, and C. Satria, “IoT-Based Garbage Container System Using NodeMCU ESP32 Microcontroller,”
Journal of Advances in Information Technology, vol. 13, no. 6, pp. 569–577, 2022.
How to Cite
Dasriani, N. G., Hadi, S., & Syahrir, M. (2023). Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 23(1), 229-242.