AI-Enhanced Sensor Fusion Platform Takes the Pain Out of Indoor Air-Quality Detection

Improving indoor air quality is a growing imperative for ensuring a healthy environment, whether at home, work, or school. According to a new report from the U.S. Environmental Protection Agency, we spend up to 90 percent of our days inside where airborne pollutants can be up to five times higher than is typical in outdoor settings.

To advance the trend toward better air-quality measurement, Renesas recently extended our sensing portfolio to include integrated all-in-one modules that combine factory-calibrated environmental sensors with a Renesas microcontroller (MCU), chip-scale packaging, and artificial intelligence (AI) algorithms.

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One of our application engineers, Stefan Schreiber, recently published a blog titled “Addressing Air Pollution with Advanced Sensor Technology: Introducing the RRH62000 for Clean Air Monitoring” that offers an excellent analysis of the rapidly changing air-quality sensor market and how the Renesas RRH62000 module is helping to mitigate air-quality issues.

I would like to expand upon that theme by acknowledging the deeply collaborative nature of this latest breakthrough, which includes input from across our industry-leading sensor, MCU, and AI portfolios to foster the widespread deployment of environmental sensors in everything from smart air purifiers and smoke detectors to remote weather stations.

From a customer perspective, we focused intently on three areas to make it significantly easier to detect, interpret, and share real-time air-quality data.

Comprehensive Sensor Fusion

The trajectory of the Renesas environmental sensor portfolio has seen us evolve from discrete sensors to highly integrated sensor modules that incorporate AI-enhanced smart compensation engines and algorithms developed through our acquisition of Reality AI. Today’s emergence of any AI-enabled sensor fusion platform continues to help make our customers’ lives easier by lowering costs by more than 30 percent, reducing board space by more than 50 percent, and cutting time-to-market in half.

In the latest case, the RRH62000 module allows customers to move from detecting a single event to simultaneously measuring temperature, humidity, particulate matter, and the presence of volatile organic compounds. This combination of multiple sensor parameters, known as sensor fusion, gives customers the ability to address numerous unique applications. This is ideal for multi-faceted use cases such as mold detection or monitoring kitchen exhaust fans where multiple gases and airborne matter may be present. In a more light-hearted proof-of-concept case, our designers recently helped a prospective customer integrate a sensor hub into a commercial oven, using several sensor modalities to determine optimum application conditions like automated cooking processes. As a result, end users can prepare perfectly cooked food in their kitchens.

Using AI Models to Provide Continuous Performance Improvement

Depending on a customer’s specific detection requirements, we enable them to gather data and use it to train the sensor module’s compensation engines.

In the future, this advanced data training will use AI event classification algorithms at the endpoint to continuously evolve, for example, by learning to differentiate whether smoke is coming from a cigarette or vape pen. By building out these data sets, designers then have the ability to identify broader profiles or patterns. This could enable them not just to detect cigarette smoke but distinguish which brand of tobacco is being used.

Air Quality Standards Conformity

Air quality standards are notoriously complex as they change frequently and differ widely by region. This makes it nearly impossible for a typical customer to conduct the due diligence required to conform to every standard across all global markets.

Renesas has a very deep knowledge in these standard bodies and is reflecting them in its solutions. In the execution of these building standards through specific sensor firmware, Renesas supports their customers in their end devices.

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Continuous firmware updates and further operation mode releases address the different customer needs for regional building standards without them having to navigate what is effectively a paperwork jungle.

In the end, the combination of hardware, software, firmware, and AI algorithms enables flexible, scalable, customer-friendly solutions that integrates the latest Renesas MCU nodes, embedded environmental sensors, and machine learning models capable of data analytics. Together, Renesas Sensing Solutions help to ensure the air we breathe is healthy in an age where energy-efficient building construction often restricts ventilation and older populations remain at risk of life-threatening respiratory illnesses.