Smartphone-based air quality measurement gets personal: Page 5 of 7

June 16, 2020 //By Alexander Herrmann, Project Director Optical Sensing Business, and Dr. Richard Fix, Product Portfolio Manager, Bosch Sensortec
 Smartphone-based air quality measurement gets personal
This article provides insights into new PM2.5 and VOC sensing technologies that enable personal air quality monitoring to improve people’s health and well-being.

To measure VOCs, Bosch has developed a compact, high performance gas sensor. The BME680 is the world's smallest solution that provides 4-in-1 air quality monitoring. It can measure ambient temperature, barometric pressure, relative humidity and gases and is housed in a 3 x 3 x 0.93 mm3 package. It works in the ultra-low power range down to less than 0.1 mA.

The sensor is able to distinguish between fresh air (i.e. clean air, mainly nitrogen, oxygen and humidity) and used air with additional pollutants. Typically, when people are present in rooms, the exhaled breath is one of the most important reasons for poor air quality. Knowing the amount of exhaled air contained in ambient air helps to optimize ventilation, and thereby helps to prevent airborne transmission of infections like SARS-CoV-25. Although VOC sensors cannot directly detect viruses, they indirectly contribute to people’s health and wellbeing.

Intelligent software turns the collected sensor data into useful outputs for the users. By combing modern gas sensing techniques with artificial intelligence (AI), different ambient conditions can now be recognized and classified, which enables many new applications.

Let’s consider an advanced example of risk evaluation for forest climate mapping and early wildfire detection. Firstly, a sensor network maps out the entire area with a real-time view of all environmental activities. Secondly, machine learning is used to create a mathematical model based on raw data for classifying and predicting different situations and assessing risk. And lastly, edge AI is used to adapt the final product to the area-specific conditions of the individual user and to lower power consumption.


Figure 3: An image illustrating the forest climate example.

 

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