Renesas RRH62000 Compact Sensor Module for Air Quality Monitoring

Renesas Electronics Corporation has unveiled its latest innovation in indoor air quality monitoring: the RRH62000 all-in-one sensor module. This marks Renesas’ first multi-sensor module designed to track various air quality parameters within a compact form factor. The module is capable of accurately detecting multiple particle sizes, volatile organic compounds (VOCs), and gases that pose health risks. Integrated with a Renesas microcontroller (MCU), this module offers an intelligent sensor management solution for the expanding market of air monitoring applications, such as air purifiers, smoke detectors, HVAC systems, weather stations, and smart home technologies. Additionally, its robust firmware supports compliance with international air quality standards.

RRH46410 module inlet and outlet on one side and connector on another side. — RRH62000 Module

The RRH62000 stands out with its exceptionally compact size, measuring only 46.6 x 34.8 x 12 mm, making it one of the smallest in its class. It incorporates Renesas’ RA Family MCU and seven different sensor signals, including a laser-based PM1/2.5/10 sensor, the ZMOD4410 gas sensor, and the HS4003 humidity and temperature sensor. Together, these sensors enable the module to monitor particulate matter, total VOCs, estimated CO2 levels, temperature, and humidity. All components are pre-integrated and calibrated at the factory, allowing developers to begin their designs immediately.

RRH46410 module size somparison with standard pen. — RRH62000 Module size comparison

The COVID-19 pandemic has heightened public awareness of air quality and its impact on health. People are increasingly concerned about how indoor air pollutants affect respiratory health and overall well-being. Indoor pollutants, such as dust, paint fumes, cooking smoke, pollen, and particles from HVAC filters, can be six to ten times more concentrated than outdoor air, posing significant health risks, including lung damage and cancer.

Renesas new sensor module is equipped to tackle these challenges by monitoring a wide range of air quality conditions. Utilizing laser-based technology, which offers greater precision than traditional LED methods, the module can track concentrations of PM1, PM2.5, and PM10 particulates – particles ranging from 0.3 to 10µm in diameter – as well as absolute or relative TVOC levels across different power modes. This ensures the highest accuracy in detecting pollutants. The RRH62000 can deliver seven sensor outputs simultaneously, with the onboard MCU enabling real-time air quality monitoring.

Renesas IAQ Rating	Air Information	TVOC (mg/m³)	Air Quality
≤ 1.9	Clean Hygienic Air (target value)	< 0.3	Very Good
2.0 to 2.9	Good Air Quality (if no threshold value is exceeded)	0.3 to 1.0	Good
3.0 to 3.9	Noticeable Comfort Concerns (not recommended for exposure > 12 months)	1.0 to 3.0	Medium
4.0 to 4.9	Significant Comfort Issues (not recommended for exposure > 1 month)	3.0 to 10.0	Poor
≥ 5.0	Unacceptable Conditions (not recommended)	> 10.0	Bad

Level of Indoor Air Quality Based on TVOC Levels Described by UBA

The RRH62000 module is equipped with standard firmware and AI algorithms that allow engineers to configure the sensors to meet the requirements of various green air quality standards in public buildings, such as The Well Building Standard (WELL), Home Ventilating Institute (HVI), and RESET. For example, a school in China can use the same hardware as one in the United States or another location, with the ability to simply update the AI-enabled firmware to suit specific needs.

Intelligent sensor modules like the RRH62000, along with the recently announced RRH46410 gas sensor module, support demand-controlled ventilation, allowing HVAC systems to adjust airflow based on carbon dioxide levels and occupancy data, maintaining optimal air quality and energy efficiency. Additionally, these modules use AI algorithms to predict when HVAC filters need replacement or to detect anomalies before system failures occur, thus reducing maintenance costs and time.