Girdhar Maheshwari, Rohit Kumar

DOI: https://doi.org/10.5281/zenodo.22007072

Gas leakages in household kitchens pose a consistent threat, especially among elderly people and people with anosmia, a disease that adversely affects their sense of smell. Traditional monitoring mechanisms are limited to basic trigger-based actions and local alerts using buzzers. They lack in intelligent capabilities such as connectivity that would enable them timely and reliable responses. This study focuses on artificial intelligence-enhanced IoT-enabled Smart Air Safety System that continually detects the concentration of gas , temperature and humidity levels using a MQ135 gas sensor and DHT11 sensor is connected to NodeMCU (ESP8266). The detection-based filter algorithm differentiates the status of the environment into three categories: safe, moderate, and danger while it minimizes false alarms that result in sudden bursts of the sensors’ outputs. During emergencies, the smart system automatically controls the activation of the exhaust fan using a servo motor, activates buzzer and LED alarms, and pushes notifications through the Blynk IoT platform. A web dashboard integrated within the ESP8266 web server shows live data from the sensors and generates analytics. Results show correct categorization of multiple environmental states, successful false alarm prevention, and less than one-second delay in response time.

IoT, gas detection, anosmia, NodeMCU, ESP8266, smart home safety, false alarm filtering, Blynk.

The paper presents an AI-driven smart air safety system with the Internet of Things (IoT) technology, which is targeted at the elderly and people with anosmia to keep them safe from household gas leaks. This system is novel as it integrates constant monitoring of the environment with multiple sensors, implementation of a consecutive detection algorithm for false alarm filtering, automated actuation via mechanical means, mobile notifications (powered by Blynk app), and a web dashboard interface on the device. The testing revealed that the system described in this paper does a good three-state classification, is able to filter transient peaks (false alarms) from the sensors and is able to do real-time actuation after status confirmation. By comparing its features with other systems, it was evident that, unlike others, the system proposed in the paper offers all five key features: false alarm filtering, automatic actuation, an analytics web dashboard, mobile notifications, and vulnerable user protection – all for a low-cost microcontroller (only $3).

[1] World Health Organization, "Deafblindness and Anosmia: Sensory Impairments in the Elderly," WHO Technical Report, Geneva, Switzerland, 2019.
[2] A. Sharma, R. Gupta, and P. Singh, "IoT-Based Smart Gas Leakage Detection System for Domestic Safety," Int. J. Eng. Research & Technology (IJERT), vol. 12, no. 4, pp. 210–218, 2023.
[3] S. Patel and M. Mehta, "Smart Gas Monitoring System Using IoT and Mobile Applications," Procedia Comput. Sci., vol. 220, pp. 350–357, 2023.
[4] Z. Khan, A. Rauf, and S. Hassan, "Deep Learning-Based Gas Leakage Detection Using IoT Sensor Networks," IEEE Access, vol. 11, pp. 44210–44221, 2023.
[5] R. Yadav, S. Mishra, and P. Tiwari, "IoT-Based Gas Leakage Detection with SMS and Cloud Integration," Int. J. Innovative Research in Sci., Eng. and Technology, vol. 12, no. 6, pp. 7815–7823, 2023.
[6] N. Verma, K. Sharma, and A. Jain, "IoT-Based Smart Home Safety System with Gas and Fire Detection," J. Network and Comput. Appl., vol. 225, pp. 102–115, 2024.
[7] R. Reddy and P. Kumar, "Intelligent Gas Leakage Detection and Alert System Using NodeMCU," in Proc. Int. Conf. on Smart Systems and Inventive Technology (ICSSIT), pp. 45–52, 2024.
[8] M. Gupta and S. Singh, "Smart Kitchen Safety System Using IoT and Automation," Int. J. Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 13, no. 2, pp. 890–897, 2024.
[9] P. Singh, A. Yadav, and R. Mishra, "AI-Based Environmental Monitoring System Using IoT Sensors," Engineering, Technology & Applied Science Research (ETASR), vol. 15, no. 1, pp. 5500–5508, 2025.
[10] M. Gupta, S. Arora, and D. Malhotra, "Real-Time Gas Monitoring System with Web-Based Data Analytics," Expert Systems with Applications, vol. 245, pp. 119–130, 2025.
[11] K. Shah and M. Patel, "Smart Air Quality Monitoring and Alert System Using IoT," Int. J. Advanced Comput. Sci. and Applications, vol. 16, no. 2, pp. 120–128, 2025.

Girdhar Maheshwari, Rohit Kumar (2026). AI-Enabled IoT Smart Air Safety System for Kitchens and Elderly People with Anosmia. International Journal of Computer Techniques, 13(4), 230–235. ISSN: 2394-2231. DOI: https://doi.org/10.5281/zenodo.22007072