Design of air quality meter and pollution detector

Mukhopadhyay, Arunava; Sengupta, Abhirup; Paul, Shuvam; Saha, Debdutta; Shome, Kaustav; Roy, Srinwan; Ghosh, Shreya; A., None Basu; Sen, Kaustavi; Chatterjee, Rajib

doi:10.1109/iemecon.2017.8079626

Cited by 6 publications

(1 citation statement)

References 3 publications

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“…Users can view the real-time graph of parameter and sensor reading through the webpage of IBM Watson IoT platform. Arunava Mukhopadhyay and his research group has conducted a project on air quality meter and air pollution detector in 2017 [20]. They developed an IoT technology via Bluetooth to monitor the environment.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of real-time IoT-based air quality monitoring system

Dahari

2020

IJPEDS

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Air pollution is one of the biggest threat for the environment and the human’s health. The monitoring of air pollution based on several atmospheric pollutants is becoming critical in most countries including Malaysia. This paper presents a development and enhancement features of real-time Internet of Things (IoT)-based environmental monitoring system for air quality. The proposed system will be beneficial to monitor the real-time data for a specific set of air quality parameters such as temperature, humidity and concentration of carbon monoxide, liquified petroleum gas (LPG) and smoke. An alarm system will be triggered if the concentration of carbon monoxide exceeds 50 ppm. Users can use their smartphone to view these data via Wi-Fi by installing an application called “AirProp”. Based on the collected data, this paper also analyses other contributing factors such as time and traffic condition on the temperature, humidity and concentration of pollutant gases at different locations. The advantage of the real-time system is it serves as the data base platform to store data up to certain duration of time. The data can be further analysed and leveraged by governments and researchers to mitigate air pollution.

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Section: Introductionmentioning

confidence: 99%