Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Particulate Matter Measurement with Low-Cost Sensors—Investigation of Data Quality and the Benefit of Data Correction Approaches

Version 1 : Received: 16 February 2022 / Approved: 22 February 2022 / Online: 22 February 2022 (20:10:59 CET)

How to cite: von Kuyck-Studzinski, T.; Buller, T.; Conrad, A. Particulate Matter Measurement with Low-Cost Sensors—Investigation of Data Quality and the Benefit of Data Correction Approaches. Preprints 2022, 2022020283 (doi: 10.20944/preprints202202.0283.v1). von Kuyck-Studzinski, T.; Buller, T.; Conrad, A. Particulate Matter Measurement with Low-Cost Sensors—Investigation of Data Quality and the Benefit of Data Correction Approaches. Preprints 2022, 2022020283 (doi: 10.20944/preprints202202.0283.v1).

Abstract

The transmission and analysis of data is one of the challenges of the 21st century. In the field of environmental measurement technology, existing broadband and wireless technologies have not been able to transmit data reliably and cost-effectively over long distances and in hard-to-reach places. LoRaWAN, an IoT technology, could be an energy-efficient, cost-effective and secure alternative as a narrowband technology in combination with battery-powered sensors and thus make an important contribution to the intelligent, largely wireless networking of objects, plants and machines (IoT), for example in the municipal sector. In addition to ecological and economic benefits, the quality of life in modern, intelligently networked cities can be enhanced by real time data acquisition. However, the prerequisite is that the quality of the data acquired via this method is sufficiently good. This paper therefore addresses the question of the quality of particulate matter data collected by low-cost sensors. To determine this, an SDS011 particulate matter sensor from Nova Fitness was ported to LoRaWAN. The sensor was installed next to a governmental measurement station. In a test that lasted five weeks, data from the SDS011 sensor were compared with those from the governmental station. Differences were identified and a correction approach was developed and applied. The efficiency of the approach was verified. Based on the results, it can be seen that the use of the low cost sensors has weaknesses. Problems can only be partially reduced. Nevertheless, the use of the low-cost sensors can be helpful for a flexible and cost effective collection of environmental data.

Keywords

fine dust measurement (PM2.5, PM10); LoRaWAN; internet of things; low-cost sensors; SDS011; level-indication measurements; sustainability

Subject

EARTH SCIENCES, Environmental Sciences

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.