Volatile organic compounds (VOCs) are one of the major reasons of indoor air contamination. A few of the VOCs sources are materials used for cleaning, furnishings, cooking and gas leaks. The VOCs may gather in poorly ventilated domestic buildings. Available monitors for the indoor air quality are accurate but have certain limitations, such as being costlier, needing routine maintenance and others. In this case, low‑power wide‑area networks (LPWANs) such as LoRaWAN provide a valuable alternative when used with low-cost metal oxide semiconductor (MOS) sensors. Though MOS sensors are sensitive to temperature and humidity, they have long‑term drift and a higher power cost when tested normally. To overcome these issues, the current research designed an innovative technique that utilized an AI- integrated low-powered wireless area networks (LPWANs/LoRaWAN) for better air monitoring. Hence, there is a need to design and install a complete IoT system for live-time monitoring of VOCs in residences. The designed technique couples a low-energy sensing node with LoRaWAN connectivity, which is an edge‑AI calibration pipeline that can measure humidity, temperature, drift mitigation and provides an adaptive sampling approach to maximize battery performance. The proposed system is tested in a residential having multiple rooms using pilot data and compared with available systems. The obtained results from this prototype revealed that this technique gains reliable VOC identification and leakage notifications and improved battery life for six months.