Development of indoor air quality monitoring system using raspberry Pi

Mohamad Ali, Mohamad Nazhim (2024) Development of indoor air quality monitoring system using raspberry Pi. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Indoor air quality (IAQ) is a key aspect of environmental health as it affects comfort, productivity, and general well-being. It involves variables like humidity, temperature, ventilation, and contaminants like chemicals, mold, and bacteria. Inadequate indoor air quality (IAQ) can cause everything from allergies and respiratory troubles to more serious illnesses like asthma and lung cancer. The COVID-19 pandemic and growing public awareness about indoor pollution and sick building syndrome have brought attention to the significance of indoor air quality (IAQ). Engineering controls, administrative procedures, and building space reconfiguration are all part of the IAQ improvement efforts. As a result, maintaining a high IAQ is essential for comfort, productivity, and health in interior environments. Therefore, the objective of this project is to develop an indoor air quality monitoring system using Raspberry Pi along with ESP32 to monitor the air quality of indoor environment using web-based user interface and record the levels of quality of air. Besides, this indoor air quality monitoring system uses a Raspberry Pi as a microprocessor to record, evaluate and monitor the system and uses Raspberry Pi 's onboard Wi-Fi to send the data to the web-based interface wirelessly. The SDSO 11 sensor is used for detecting and measuring particulate matter, especially PM2.5 and PMlO which can be up to 2.5 μm and 10.0 μmis size that can have detrimental effect on health. The BME680 and SGP30 sensors, connected to an ESP32, are used for detecting various air quality parameters. The ESP32 reads the data from these sensors and sends it to the Raspberry Pi using MQTT with its onboard Wi-Fi. In addition, it is anticipated that this monitoring system will provide a worthy cost estimate with consistent accuracy and user-friendliness

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