A Fully Automated System for Detecting and Monitoring Indoor Airborne Pollutants

Lead Author Major

Computer Engineering

Lead Author Status

Senior

Second Author Major

Computer Engineering

Second Author Status

Senior

Third Author Major

Electrical Engineering

Third Author Status

Senior

Fourth Author Major

Electrical Engineering

Fourth Author Status

Senior

Format

SOECS Senior Project Demonstration

Faculty Mentor Name

Professor Rahim Khoie

Faculty Mentor Department

School of Engineering and Computer Science

Abstract/Artist Statement

Indoor air pollution is a growing concern around the world, especially in densely populated areas where ventilation is limited. The air inside buildings can become polluted by a range of sources, including cooking, heating, and cleaning chemicals. This is particularly concerning as people spend a significant amount of time indoors, especially during extreme weather conditions, making it essential to monitor air quality.

The goal of this project was to design an indoor air pollution monitor that detects specific pollutants, as well as non-pollutants and displays this information in an easy-to-understand manner. The project team decided that having multiple sensor units strategically placed would give the most accurate representation of real-world pollutant levels, so they determined the number of sensor units and the best locations to place them. They selected five pollutants to monitor, as well as one non-pollutants.

One of the main challenges of the project was to develop a self-powered sensor unit. The initial design included a solar panel to supply the sensor unit with power, but after testing, it was found that the power output from the panels from indoor conditions would not be sufficient to power the sensor unit. The project team had to rework the original design to use a battery instead. The sensor unit design included a sleep mode to save power.

To make it easier for users to access the data collected by the sensor units, the system features a hub microcontroller that interprets the data, then uploads it to a website where the user can view the information as a histogram. The data can be displayed by type and time range. The website also provides a warning if the pollutants reach dangerous levels.

Location

Chambers Technology Center, 3601 Pacific Ave, Stockton, CA 95211, USA

Start Date

6-5-2023 2:30 PM

End Date

6-5-2023 4:30 PM

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May 6th, 2:30 PM May 6th, 4:30 PM

A Fully Automated System for Detecting and Monitoring Indoor Airborne Pollutants

Chambers Technology Center, 3601 Pacific Ave, Stockton, CA 95211, USA

Indoor air pollution is a growing concern around the world, especially in densely populated areas where ventilation is limited. The air inside buildings can become polluted by a range of sources, including cooking, heating, and cleaning chemicals. This is particularly concerning as people spend a significant amount of time indoors, especially during extreme weather conditions, making it essential to monitor air quality.

The goal of this project was to design an indoor air pollution monitor that detects specific pollutants, as well as non-pollutants and displays this information in an easy-to-understand manner. The project team decided that having multiple sensor units strategically placed would give the most accurate representation of real-world pollutant levels, so they determined the number of sensor units and the best locations to place them. They selected five pollutants to monitor, as well as one non-pollutants.

One of the main challenges of the project was to develop a self-powered sensor unit. The initial design included a solar panel to supply the sensor unit with power, but after testing, it was found that the power output from the panels from indoor conditions would not be sufficient to power the sensor unit. The project team had to rework the original design to use a battery instead. The sensor unit design included a sleep mode to save power.

To make it easier for users to access the data collected by the sensor units, the system features a hub microcontroller that interprets the data, then uploads it to a website where the user can view the information as a histogram. The data can be displayed by type and time range. The website also provides a warning if the pollutants reach dangerous levels.