A cloud-based iot and web application for indoor air quality monitoring using arduino

Adhitthana, James (2020) A cloud-based iot and web application for indoor air quality monitoring using arduino. Bachelor thesis, Universitas Pelita Harapan.

	Text (Title) Title.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (524kB)
Preview	Text (Abstract) Abstract.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (110kB) | Preview
Preview	Text (ToC) ToC.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (261kB) | Preview
Preview	Text (Chapter1) Chapter1.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (52kB) | Preview
	Text (Chapter2) Chapter2.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (968kB)
	Text (Chapter3) Chapter3.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (1MB)
	Text (Chapter4) Chapter4.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (4MB)
	Text (Chapter5) Chapter5.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (41kB)
Preview	Text (Bibliography) Bibliography.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (121kB) | Preview
	Text (Appendices) Appendices.pdf Restricted to Repository staff only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (2MB)

Abstract

Air quality indoors matters as much and sometimes matters more than the quality of air outdoors. This research aims to enlighten people of the existence and dangers of indoor air pollution by creating IoT hardware that can monitor indoor air quality as well as creating a user-friendly, cloud-based web application able to monitor, illustrate, and visualize the indoor air quality of the room. The system relies on the US-Air Quality Index as the standard of measurement while also providing an air quality scoring system created to fill the current gap of an internationally recognized indoor air quality standard. The web app created is a cross-platform interactive dashboard developed in JavaScript, HTML, and CSS. The hardware consists of Arduino microcontrollers and modules programmed using the C language connected to eight sensors sensitive to the specific pollutant monitored. The sensors employed include MQ-8 (hydrogen), MQ-2 (smoke), MQ-6 (LPG), MQ-135 (CO2), MQ-7 (CO), MQ-3 (alcohol), SHARP GP2Y1010AU (PM2.5/dust), and DHT-11 (temperature and humidity) sensors. Using the four-layer IoT architecture, the Arduino microcontrollers send sensor readings to the Wi-Fi module, uploading them into the cloud database located on the Firebase Realtime Database. The web app uses the uploaded data to calculate the Air Quality Index, air quality score, humidex, and average historical data. As well as generate interactive cards, tables, graphs, tips on increasing air quality, track daily pollutant averages, and act as an alarm if a pollutant passes a dangerous threshold. Three separate randomized trials have shown that the system consistently passes 37/37 unit test specifications, 57/57 integration test specifications, and 3/3 monkey test specifications, indicating that the system's functionalities are proven to be working correctly. The system has also produced the expected Air Quality Index, air quality scores, and Humidex calculations with 100% accuracy, while the truncated mean calculation has a 95% accuracy. Black-box usability testing involving five testers with no prior knowledge of indoor air quality has verified the user-friendly web app and approved the indoor air quality score system created to fill the vacant spot for the internationally recognized indoor air quality standard. Hence, the goal of enlightening laypeople is accomplished. Consequently, the integrity of the data and the system's reliability is guaranteed because the system is found to have a low data transfer error rate of up to 10%. The low error rate would still represent the real-time indoor air quality. The system configuration was successfully tested and deployed in two 3m2 indoor rooms inside a polluted industrial city and non-polluted residential suburbs and has successfully monitored the change in the indoor air quality and pollutants detected. Therefore, the system is ready to be deployed in any indoor room of 3m2 size.

Actions (login required)

View Item