Lung-Wen Antony Chen (Environmental and Occupational Health) and colleagues have published an article, "From Air Quality Sensors to Sensor Networks: Things We Need to Learn" on the Sensors and Actuators B: Chemical.
As low-cost air quality sensors become a new paradigm for air quality monitoring and exposure assessment, this study leveraged data collected from state and local agencies in metropolitan areas of the United States to evaluate how low-cost sensors could be deployed to form an urban sensor network. It was found that homogeneities of criteria air pollutants varied by city, making it challenging to design a uniform network that was suitable across regions. Data collected during wildfire episodes showed that a real-time (i.e. in situ) machine learning calibration process is promising to address the data quality challenges persisting in sensor applications. This paper concluded by calling for establishing and agreeing upon “good practice” guidelines for sensor network design, deployment, and management.
