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Measuring Thermal Comfort, Air Quality Using the Autonomous Robotic Environmental Sensor

Measuring Thermal Comfort, Air Quality Using the Autonomous Robotic Environmental Sensor

From ASHRAE Journal Newsletter, February 22, 2022

Measuring thermal comfort and air quality in the indoor environment allows engineers to adjust building design and operations to improve building performance and occupant health. But those methods of measurement tend to be tedious and expensive, requiring several expensive sensors to be mounted in the building.

Researchers from the University of Guelph recently published a paper in Science and Technology for the Built Environment proposing the Autonomous Robotic Environmental Sensor (ARES)—a custom-designed omniwheel mobile robot retrofitted with several sensors capable of autonomously taking measurements of the indoor environment at multiple positions. ARES can reduce the number of sensors needed, the amount of labor required and cost.

Researchers Amir Aliabadi, Ph.D., P.Eng., and Mohammad Biglarbegian, Ph.D., P.Eng., discussed ARES and explained to ASHRAE Journal how it could help HVAC&R engineers:

Why is this research significant?

Building science is important for two reasons: climate change and human health. From the point of view of climate change, buildings consume about 40% of the world’s energy, so any effort in understanding of their energy consumption and ways to reduce it will have a large impact in mitigating climate change. This is possible because an energy-efficient building would consume less fossil fuels, electricity or embodied carbon.

From the point of view of human health, people spend 90% of their time indoors—at least in the developed world. This makes them susceptible to negative psychological or physiological health effects if buildings are not designed or operated properly. For instance, lack of light, noise, poor ventilation, inadequate air quality and/or improper thermal comfort could result in loss of productivity and/or the possible spreading of airborne disease in buildings.

There is a famous saying by Peter Drucker: “You can’t manage what you can’t measure.” It is extremely important to assess building performance using quantification methods and measurement metrics before solutions can be found to improve their performance. This signifies the importance of building monitoring research.

A lot of people are talking about using sensors to measure building conditions. What makes this research different?

Climate and air quality variables exhibit a wide range of spatial and temporal variations throughout the footprint of a building. For instance, temperature, relative humidity, air speed, light or concentration of pollutants can vary substantially from one location in a building to another location and also from one moment in time to the next. This renders the control of buildings’ environmental variables a real challenge. Most people in an office environment have experienced a situation in which some occupants of the space find their thermal comfort satisfactory while others complain about the environment being too cold/hot, dry/wet or stuffy/drafty.

The most basic way to measure building performance variables is via the installation of a few sensors in fixed locations. This method may resolve the temporal resolution of variables being measured, but it does not show spatial variability. The next level is to install a greater number of fixed sensors in a building, but this is costly and cannot cover all spatial locations.

Mobile sensing platforms are the alternative that rely on humans (e.g., wearable sensors, moving carts, etc.) or robots to relocate measurements for achieving greater spatial resolution. Most available robotics solutions are not autonomous. Our philosophy is to achieve autonomous robotic measurements of the indoor environmental variables by minimizing the human intervention and cost effectively.

How do the Autonomous Robotic Environmental Sensors work?

The ARES automatically measures temperature, air speed and relative humidity in a complex flat environment (e.g., with obstacles) by navigating itself using a pre-determined (but optimized) path that minimizes energy use.

A novel feature of ARES is that it relies on omniwheels allowing holonomic motion, instead of a differential drive, which makes it easy to navigate. Omniwheels—or poly wheels—are wheels with small discs (called rollers) around the circumference which are perpendicular to the turning direction. The effect is that the wheel can be driven with full force, but it will also slide laterally with great ease. Differential drive robots may have to move in order to rotate, while the omniwheel robots can rotate in place without the need to move.

Before a measurement campaign, ARES takes the geometry of space (possibly with obstacles), the number of points to measure and the measurement interval. It then generates a navigation path to avoid the obstacles and to minimize energy consumption while achieving the measurement program.

It relies on a sophisticated non-linear control program and a feedback signal from the robot’s wheels to sense its position. ARES can repeat a cycle of measurements many times without human intervention by locating itself in the same measurement points again and again. This helps mapping the environmental variables with the desired spatial and temporal resolution cost effectively.

Currently, an ultrasonic anemometer is fitted on ARES for the environmental measurements, but any sensor type can be fitted to ARES for the desired type of measurements. For example, gas or particulate sensors could also be fitted to ARES for mapping air quality.

Just like detecting a polluting car with an emissions monitoring probe inserted in the exhaust pipe, the ARES can be viewed as a diagnostic tool to spot inefficient and unsafe areas of a building.

How can this tool help HVAC&R engineers?

HVAC&R engineers can map the real performance of a building by deploying ARES. They can measure the real response of the building variables as a result of implementing a design/operation approach.

For instance, imagine an engineer wishes to find a thermal comfort index (e.g., Predicted Mean Vote and Predicted Percent Dissatisfied (PMV-PPD)) throughout a building with multiple zones, each having its own air exchange rate, temperature and humidity settings. The engineer can deploy ARES to map the environment over many days and locations. The engineer can then identify the required air exchange rate, humidity and temperature settings for each zone of the building to achieve the desired PMV-PPD.

As another example, suppose an engineer is tasked to find areas of poor ventilation in a hospital space. The engineer can fit ARES with a carbon dioxide sensor and map the space at multiple locations and times for the variations of carbon dioxide concentration. In both cases, ARES will perform autonomous measurements cost effectively, reducing the labor effort to relocate the measurement platform each time.

What do you want ASHRAE Journal readers to know about this research?

ASHRAE Journal readers can realize the potential of this technology toward building/operating more energy efficient and healthy buildings.

An old saying by the celebrated architect Le Corbusier reads as “The house is a machine for living.” In an age when other engineered devices, such as cars, airplanes, trains, etc., are made so efficient and safe, we still struggle to create building stock with the same level of efficiency and safeness. Just like detecting a polluting car with an emissions monitoring probe inserted in the exhaust pipe, the ARES can be viewed as a diagnostic tool to spot inefficient and unsafe areas of a building. This tool can go a long way for achieving energy efficiency and healthy indoor environment for buildings.

What are the next steps for this research?

ARES can be further developed to perform localization and real-time path planning. It can learn from the environment as it performs the measurements using Bayesian techniques. For instance, Lidar technology can be fitted to the platform to detect obstacles in real-time.

It can also sense areas of the environment where the monitored variables exhibit large spatial and temporal gradients, as opposed to areas with more or less uniform variation of the monitored variables. It can then plan to probe the areas with large gradients more actively.

Finally, the “sky is the limit” for this technology, both literally and metaphorically. Currently, ARES can only move in 2D space, i.e., in a flat environment. However, it can be advanced with technology to climb stairs, extend vertically and/or fly to cover 3D mapping of a space.