The sensor fusion technology is alive and well, and it’s apparent in a sensor module that combines data from seven sensing signal sources in an indoor air quality monitoring solution and passes it onto an onboard microcontroller (MCU) to detect surrounding air quality data in real-time. All components in this sensor module are pre-integrated and fully calibrated at the factory, which enables developers to start their sensor system designs right out of the box.
The RRH62000 sensor module unveiled by Renesas packs an MCU with seven sensor signals: the laser-based PM1/ 2.5/ 10 sensor, ZMOD4410 gas sensor, and the HS4003 humidity and temperature sensor. These sensors detect particulate matter, total volatile organic compounds (TVOC), estimated CO2, temperature, and humidity all in one system.
The sensors inside the module can detect particulate matter, TVOCs, estimated CO2, temperature, and humidity in a single unified monitoring system. Source: Renesas
At a time when heat, ventilation and air conditioning (HVAC) systems are moving toward autonomous monitoring of our air quality, such combo sensing solutions could be critical in monitoring and detecting harmful gasses in indoor spaces. Such solutions can also support demand-controlled ventilation, which in turn, will allow HVAC systems to adjust air flow based on carbon dioxide levels and occupancy information to maintain optimal air quality and energy efficiency.
The RRH62000 sensor module also employs artificial intelligence (AI) algorithms to predict when HVAC filters must be replaced or detect an anomaly before system failure occurs. That significantly reduces system maintenance cost and time.
Alongside embedded AI algorithms, the sensor module comes with firmware that enables engineers to configure the sensors to support various green air quality standards in public buildings, including The Well Building Standard (WELL), Home Ventilating Institute (HVI) and RESET. As a result, design engineers can use the same hardware for multiple locations and geographies by simply updating the AI-enabled firmware.
While people are now more aware of how air pollutants can affect respiratory health and overall well-being, what’s less known is that pollutants are typically six to 10 times more concentrated indoors than outdoors. That includes dust, paint fumes, smoke from cooking, pollen, and particulates from HVAC filters.
RRH62000—available in a compact footprint measuring 46.6 x 34.8 x 12 mm—provides an integrated design solution encompassing sensors, RA family MCU, AI algorithms, and firmware to turn sensing data into actionable insight for indoor environment monitoring. That makes it a plug-and-play solution for indoor air quality monitoring, claims Renesas.
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