AUTOMATIC COOKER HOOD MONITORING SYSTEM BASED ON INTERNET OF THINGS

Abstract

Acute Respiratory Tract Infection (ARI) poses a significant health risk, particularly for housewives frequently exposed to kitchen smoke, which contains harmful pollutants like carbon monoxide, potentially leading to serious conditions such as cancer and pneumonia. To address this issue, the development of an effective smoke removal system is crucial. This research employs a Research and Development methodology to design and test an automatic cooker hood that utilizes the MQ-7 sensor for smoke detection, controlling a 12V DC fan through a relay to operate at three adjustable speeds: low, medium, and high, based on real-time smoke intensity. The Aims of this study are to create a monitoring tool that efficiently removes kitchen smoke and provides immediate feedback on air quality. Results indicate that the system functions optimally, with the fan speed successfully adjusting according to detected smoke levels and displaying data on a 16x2 I2C LCD as well as through the Blynk application, offering clear visualization of air quality metrics. This research introduces a Novelty in integrating IoT technology for real-time air quality monitoring in kitchens, enhancing user awareness and intervention capabilities. However, fluctuations in smoke readings from the MQ-7 sensor present a Knowledge Gap, highlighting inconsistencies that affect PPM accuracy. The Implications of this study suggest the potential for improved health outcomes through better indoor air quality management, while future research should explore sensor accuracy enhancements and optimal placement strategies to ensure more reliable measurements, thereby further advancing the effectiveness of the automatic cooker hood system.