New multi-sensor module integrates AI for next-level air quality monitoring

The RRH62000 all-in-one sensor module from Renesas presents a compact, intelligent solution for fast development of air quality monitors in a wide variety of applications in which accuracy and robustness are important. The small footprint and streamlined bill-of-materials make the RRH62000 extremely competitive, saving space and development time when compared to discrete solutions or competing modules.

The RRH62000 offers simultaneous measurement of all important air quality parameters, including particulate matter (PM) detection with output mass concentration binning for PM1, PM2.5 and PM10, total volatile organic compounds (TVOCs), indoor air quality index (IAQ), equivalent carbon dioxide (eCO2), temperature and relative humidity (RH). Each of the sensors is fully calibrated at the factory. The required air-flow channel for sampling has a self-cleaning high-speed fan mechanism to protect against malfunctions due to dust accumulation.

The insights provided by the RRH62000 sensor module are output via an I2C or UART interface on a six-pin connector, with on-device correction algorithms for improved measurement accuracy. Processing and control of the sensors are performed using the in-built microcontroller to free resources on the host system. This in-built processing also makes for easy plug-and-play evaluation of the RRH62000 sensor module using the evaluation kit and accompanying PC software.

The standard firmware of the RRH62000 sensor module can also be modified so that the RRH62000 reports in a way that conforms to the requirements and air quality standards of a particular application. The in-built MCU is also powerful enough to implement machine learning algorithms. Using an HVAC system as an example, the RRH62000 can be used to predict when a filter requires replacing. This sensor-fusion AI capability makes the RRH62000 sensor module a useful solution for applications in which machine uptime is of critical importance.