Tag: sensors

Key Insights from ASIC 2025 in Thailand: Bridging the Indoor-Outdoor Divide

Sotirios Papathanasiou1 Comment

The recent Air Sensors International Conference (ASIC) 2025, held in the vibrant backdrop of Thailand, offered a profound opportunity to delve into the evolving landscape of air quality monitoring. As an attendee, several key themes emerged that highlight both the progress made and the remaining challenges in our quest to understand the air we breathe.

The Indoor-Outdoor Air Quality Discrepancy

One striking observation from the conference was the apparent disparity in research emphasis between indoor and outdoor air quality monitoring. While outdoor environments have benefited immensely from the widespread adoption and scrutiny of low-cost air quality monitors, indoor spaces appear to lag in comparison. The primary reason for this imbalance lies in the availability of robust reference instrumentation. Governments worldwide have invested in publicly air quality stations equipped with reference-grade instruments, providing invaluable benchmarks for normalization and validating low-cost sensors in a variety of outdoor conditions. This has not only accelerated the development of accurate low-cost monitors but also fostered the creation of sophisticated correction algorithms.

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Are Low-Cost Sensors Random Number Generators?

Sotirios Papathanasiou5 Comments

Low-cost sensors aka LCS are commonly used in an effort to measure air pollutants like particulate matter all around the world, indoors and outdoors. Their low price has driven a lot of interest from many communities. Academics, experts, and consumers have embraced them because they are cheap to get and easy to embed in an IoT solution.

Countless air quality monitors use low-cost sensors (mostly from China) and although they are great as educational tools, their low accuracy leads to wrong conclusions most of the time.

Wrong conclusions are as bad as misinformation or fake news. Air pollution doesn’t kill instantly (most of the time) and it doesn’t create severe health issues in the short-term, but after an extended period or at least when we notice the consequences. One exception is carbon monoxide (CO) as it can kill people instantly and this is the reason we don’t see many low-cost CO sensors. There are some regulations that protect the consumers. Moreover, companies don’t want to take responsibility by using a low-cost CO sensor because they can get sued easily by the family of a victim when the air quality monitor won’t notice the increase of the gas indoors. Liability!

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MasterClass: Air Quality Data Visualization with R Studio & Packages

Sotirios Papathanasiou6 Comments

R Studio and its packages are used by hundreds of thousands of people to make millions of plots. I use it to compare air sensor data from different air quality monitors/sensors or to visualize air pollution levels.

In this article we will explore both how we can visualize air quality data from publicly available sources and how you can create statistical correlations between different pollutants or different sensors to find the correlation coefficient or correlation of determination.

First: Get the Right Packages

Packages are collections of functions, data, and compiled code in a well-defined format, created to add specific functionality. Here are some of the packages that we will install inside RStudio and use.

#You can either get ggplot2 by installing the whole tidyverse library
install.packages(tidyverse)

#Alternatively, install just ggplot2
install.packages(ggplot2)

#saqgetr is a package to import European air quality monitoring data in a fast and easy way
install.packages(saqgetr)

#worldmet provides an easy way to access data from the NOAA Integrated Surface Database
install.packages(worldmet)

#Date-time data can be frustrating to work with in R and lubridate can help us fix possible issues
install.packages(lubridate)

#Openair is a package developed for the purpose of analysing air quality data
linstall.packages(openair)
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