Meeting public health guidelines in schools can be made easier with a network of advanced sensors that monitor indoor air quality as part of a smart building system. (Photo credits: All images courtesy of TE Connectivity.)

Smart building sensors provide the foundation for the decade of data

April 5, 2021
JONATHAN CATCHPOLE explains the seven types of measurement data for running lighting, HVAC, and air quality in smart buildings and how the latest sensors are designed for developers to make the most of this data.

With 5G telecommunications networks under development and sensors being embedded all around us as part of the Internet of Things (IoT), the 2020s can be seen as the decade of data. That is definitely the case for the latest generation of office, leisure, and civic buildings where we work, learn, relax, and reside. According to a report by market research firm Fortune Business Insights, the smart building market is expected to grow by 12% annually by 2026. Data from smart building systems is already helping to save energy through control of lighting and HVAC. However, it can also support productivity and staff retention.

Indoor air quality as a competitive advantage

According to the WELL Building Standard, carbon dioxide (CO2) and volatile organic compounds (VOCs) are both indicators of indoor air quality. The WELL standard aims to provide a framework to create environments that help their occupants thrive. Early adopters include financial institutes and technology companies that see their workplaces as being essential to attract and retain talent.

One area where the standard differs from other building regulations and design codes is its focus on air quality. From the CO2 perspective, studies have found that high levels of CO2 can impair cognitive ability. This can impact our ability to make decisions, maintain a high quality of work, or learn and communicate effectively. Therefore, indoor air quality has huge repercussions for productivity at work, life outcomes in education, and clinical outcomes in hospitals.

For now, there are no legal requirements for educational facilities or healthcare, but the UK’s Department for Education has published guidelines that recommend a maximum concentration of less than 1000–1500 parts per million (ppm), depending on the type of ventilation.

The other indicator of indoor air quality is VOCs, which include any substance that produces an odor. Some VOCs are harmful — for example, residues from cleaning fluids, glues, or paints. Other VOCs are not harmful but could be annoying. For example, the lunchtime food habits of colleagues might not be welcomed by everyone in the office. There are yet more VOCs that are not strongly scented — for example, the compounds that people breathe out when they exhale.

The World Health Organization considers VOCs to be an indoor air pollutant and risk to health. It has linked some types of VOCs to lung conditions. However, any scent or smell can interrupt or distract in an office or classroom, particularly in a building where CO2 levels are high and minds are wandering. At the same time, energy-efficiency regulations for buildings have led to a trend for windows to be sealed shut. As a result, CO2 and VOC levels can rise throughout the day — and that is why there is growing interest in their impact and how to measure and control them.

Therefore, adding air quality monitoring to a smart building means that ventilation rates can be adjusted to keep building occupants focused, comfortable, and free of unwelcome distractions. With this in mind, buildings of the future will need to be equipped with seven types of sensors for comfort and energy efficiency.

The four core sensors

A set of four core sensors provides the basic data needed for HVAC control. Two of these are needed to detect occupancy and natural light data for lighting — passive infrared (PIR) and ambient light sensors. The other two are temperature and humidity sensors. All of these are already well established in smart building systems.

A challenge for PIR sensors is that they may be a bit “shortsighted” with a standard off-the-shelf lens. However, they can be upgraded to cover a larger space with a Fresnel lens. This is a type of lens that can be mass produced from molded polymer. It will provide greater field of view, which means a single PIR sensor can cover a larger space or a designer can specify fewer sensors to cover an entire building.

There are also potential stumbling blocks for designers when integrating temperature, humidity, and ambient light sensors.

As a component soldered onto a printed circuit board (PCB), it’s worth remembering that a temperature sensor will typically pick up the temperature of the wall rather than the air in the office. Therefore, it is important that a system should be adjustable to take into account the temperature profile in the room. For example, the device can use an algorithm to offset the measured temperature.

Ambient light is another factor that changes depending on the relative location of a room’s sensor and occupants, or even its position within an enclosure. A sensor unit at roof height will experience a different level of light to a person at a desk, so it is important to measure and adjust the lux levels during set up so that the lights dim or brighten at the associated ambient light levels.

Microphones — Sorting the signal from the noise

Another important sensor for intelligent buildings is the microphone. It has two jobs. The first is that it provides confirmation of occupancy. It could also integrate voice activation through artificial intelligence (AI) agents.

On a technical level, the microphone is probably the most straightforward of all the sensors. Microphone technology has been driven by mobile telecommunications, meaning that today’s microphones are small, cheap, and extremely sensitive, even up to the ultrasonic range.

Microphones can be based on microelectromechanical system (MEMS) technology. This uses etching to create a microscopic structure in a silicon wafer. In the case of a microphone, the structure takes the form of a diaphragm that picks up vibration and translates it into an electrical or electronic signal.

They offer a clear advantage for energy efficiency by acting together with the PIR sensor to detect whether a room is occupied by someone who is stationary behind a desk but creating sound from keystrokes or a phone call. Monitoring noise levels can also help to optimize an open office environment.

This dataset can provide a facilities manager with the information to justify whether to install acoustic baffling; so they can provide data that is essential for designers who want to achieve WELL Building certification.

However, the challenge for microphones is concern for privacy in people’s personal space. While voice activation is possible and very desirable for some markets, not everyone wants it. This is particularly true for organizations where confidentiality is critical.

It is possible to use the data from microphones as a “dumb” measure of noise levels without picking up voices. This can be done by sampling the analog output from a microphone and monitoring the level, not the content. This is like looking at a graphical output of a sound wave on an oscilloscope rather than listening through a speaker. Engineers who want this can make use of a microphone’s analog output and monitor the level of sound.

Air quality sensors for buildings

Facilities that want to optimize air quality can also add sensors for CO2 and VOCs. However, the challenge is that CO2 is tricky to detect, being a colorless, odorless gas, and although it is not quite inert, it is an unreactive gas.

Only two sensor technologies exist that are capable of picking up CO2. The first is the non-dispersive infrared (NDIR) technique. This takes advantage of the fact that CO2 absorbs a particular wavelength of light and calculates the level of the gas in an environment by measuring how much light is absorbed between a light source and a corresponding sensor.

However, NDIR is relatively large, cumbersome, and costly to integrate into a smart building module or a luminaire. The newer designs of NDIR sensors are around the size of a typical person’s thumb from the last knuckle to the tip — much larger than all the other aforementioned sensors combined. In addition, they can have costs around £45 (about $56) per sensor. These are major drawbacks for designers of electronics systems and housings for LEDs, who are under pressure to reduce size and cost. However, they do offer the benefit of measuring true CO2 and have high accuracy, so they are currently the only solution for some applications.

The alternative sensor is an eCO2 sensor, with “e” meaning “equivalent.” This is a metal oxide (MOX) sensor and uses the principle that CO2 and VOCs exist together at a constant ratio inside typical buildings. It works by measuring the resistance across a heated gas-sensitive semiconductor plate in a MEMS device. It then uses the measured level of VOCs to calculate the level of CO2. It is an indirect measurement technique, but is still valid for many applications.

Being a MEMS device, it is small and cheap — therefore ideal for integrating into a smart building module. The drawback is that because MOX sensors do not read CO2 directly, their accuracy is lower than NDIR sensors and would give elevated readings in VOC-rich environments. MOX sensors are well suited for smart buildings thanks to the fact that people exhale VOCs and CO2 during the day, so the two types of gases are strongly related.

It is also worth noting that both types of air quality sensors need to self-calibrate every 24 hours, usually against a baseline of the lowest reading over the past 24 hours.

Data and communication

With all this in mind, there is a lot to consider before integrating sensors into luminaires and other devices.

PIR and ambient light sensors are already well established as components of luminaires — a development that was possible thanks to the low temperature of LED technology. However, there is a thirst for more data and more smart building functionality.

When looking to measure other data, the ideal sensor should be small in size, widely available, and inexpensive. In addition, developers should be able to integrate them easily.

That was the principle we worked to when we developed the AmbiMate smart building sensor. It offers developers common smart building sensors on a single PCB that measures around 30 × 16 mm. It is compatible with Arduino and Raspberry Pi, so it is already being adopted by the maker community.

For example, maker BK Hobby has published his design for the Kube Multisensor on GitHub as a low-cost, open-source smart building sensor that supports multiple communication protocols. He chose the AmbiMate sensor because it was straightforward to get up and running quickly and because it included all the sensors he needed.

Because the module is pre-engineered, it avoids the need to source and integrate multiple sensors individually. Therefore, it helps engineers reduce the time and effort needed for research, development, testing, and configuration. As a result, they can get their products to market faster and focus their time on other aspects of their product — for example, developing a service strategy or a data service for their customers.

Devices like this can be found with just the four core sensors, and also with the options of microphone and/or eCO2 and VOC sensors. A useful feature is that options with alternative sensors should be the same size. That is helpful for designers who want to offer options for their customers as they can create one single design covering mechanical, electrical, and control functions for all options.

Next five years of developments

Looking ahead at the next five years of development, it will be essential to find sensor solutions that provide the right data and can also meet the requirements for small size, accuracy, functionality, and communication protocol. One electronics distributor that has recognized the potential of our sensor module is Arrow.

The company’s engineers have combined the sensor module with the latest wireless radios and a battery to create a wireless sensor unit called Sentimate. The idea behind this is to give electronics developers a product where they can experiment with the technology and find the combination of sensor and radio components they like the best. It’s a product that takes them 60 or 70% of the way to a real-world wireless sensor and helps them write the specification for the prototype product they want to create.

However, for the LED sector, the next big step for smart building sensors will be driven by the Zhaga Book 20 specification. This will help to future proof the industry’s approach to luminaires by standardizing driver communication and aspects of mechanical design of a sensor or communication node such as dimensions, fixations, connection interface, and keep-out zones.

Once this has been published, suppliers will be able to develop the next generation of sensors that integrate all the multiple sensor types into a module designed specifically for luminaires.

Get to know our expert

JONATHAN CATCHPOLE is system architect for TE Connectivity. With 22 years’ experience at TE, Catchpole has held several engineering and management roles utilizing his background in mechanical and electrical engineering. He is a Six Sigma Black Belt and received a 2:1 bachelor’s degree with honors in mechanical and manufacturing engineering from the University of Brighton, East Sussex, UK.

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