Pollution sensors.jpg
FA info icon.svgAngle down icon.svgSource data
Type Paper
Cite as Citation reference for the source document. J.S. Botero-Valencia, C. Barrantes-Toro, D. Marquez-Viloria, Joshua M. Pearce, Low-cost air, noise, and light pollution measuring station with wireless communication and tinyML, HardwareX,16, 2023, e00477, ISSN 2468-0672, https://doi.org/10.1016/j.ohx.2023.e00477. Academia OA
FA info icon.svgAngle down icon.svgProject data
Authors J.S. Botero-Valencia
C. Barrantes-Toro
D. Marquez-Viloria
Joshua M. Pearce
Location London, Ontario, Canada
Status Designed
Completed 2023
Made Yes
Replicated No
Uses Arduino
OKH Manifest Download

Different types of environmental pollution cause negative consequences to ecosystems throughout the globe, which humanity is now trying to mitigate. To do this it is necessary to know the level of pollution problems in the immediate environment, to evaluate the impact of human activities, and to ensure habitability. For this reason, in this work, a low-cost pollution measurement station for outdoor or indoor use is proposed and developed that measures air pollution (particulate matter and CO2), noise (level and direction), light pollution (power and multispectral), and also relative humidity and ambient temperature. The system stores the data in an SD memory or transmits them in real-time to the internet via WiFi. The purpose of the system is to be used in environmental studies, to deploy monitoring networks, or to ensure the habitability of a living or working space. The prototype integrates the measurement of the different sources of contamination in a single compact device at USD$ 628.12 without sacrificing measurement accuracy, as corroborated by the validation performed for each variable with reference equipment, obtaining an average error of approximately 2.67% in the measurement of all the variables measured. The system is easy to assemble and has an option for power supply using solar photovoltaic devices and an alternative for connection to 2G/3G mobile networks.

Keywords[edit | edit source]

Air pollution, Arduino, Light pollution, Measuring station, Noise pollution, TinyML, Internet of Things (IoT), Meteorology, Climatic variables, environmental variables, low cost, 3-D printing, open hardware, environmental monitoring, sensing, environmental sensing, additive manufacturing

See also[edit | edit source]

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