Dataset Released! Air Pollution Monitoring Sensor Nodes

Dataset collected for "Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors

Written by Rajashekar Reddy Chinthalapani on September 18, 2021

You can find the air pollution dataset that we collected as part of our IEEE PIMRC paper titled Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors on this blog post on this blog post.

Abstract

Current air pollution monitoring systems are bulky and expensive resulting in a very sparse deployment. In addition, the data from these monitoring stations may not be easily accessible. This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes. For this, total nine low-cost IoT nodes monitoring particulate matter (PM), which is one of the most dominant pollutants, are deployed in a small educational campus in Indian city of Hyderabad. Out of these, eight IoT nodes were developed at IIIT-H while one was bought off the shelf. A web based dashboard website is developed to easily monitor the real-time PM values. The data is collected from these nodes for more than five months. Different analyses such as correlation and spatial interpolation are done on the data to understand efficacy of dense deployment in better understanding the spatial variability and time-dependent changes to the local pollution indicators.

Sensor Deployment

Air Pollution Sensor Nodes

File Information

Download Link Paper Link

The Folder has 9 Files named using the Nodes numbering. Each File has:

data.csv – Actual Raw data

ndata.csv – Cleaned data

outliers.csv – Outliers

adata.csv – Averged data

Each csv file has 4 fields other than timestamps.

temp – temperature(Celsius)

hum – Relative Humidity (%) (Consider Data only >75%)

p25 – PM2.5 (ug/m^3)

p10 – PM10 (ug/m^3)

Acknowledgements

Research reported in this paper was partially supported by Department of Science & Technology, Government of India and Pernod Ricard India Foundation (PRIF) through the CIE-IIITH PRIF Social Incubator Program 2019, with no conflict of interest.

Reference

C. R. Reddy et al., "Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors," 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, 2020, pp. 1-7, doi: 10.1109/PIMRC48278.2020.9217109.