If we’ve learned one thing over the course of the pandemic, it’s that understanding how building occupants utilize spaces is important to the health and safety of everyone who walks through your doors. But space utilization isn’t just a component of building wellness, it’s also part of the larger push toward data-driven building operations. The purpose of this article is to provide a primer on occupancy measurement solutions (OMS), sometimes referred to as “people counting systems.” We’ll define what they are, and discuss data privacy, hardware and software, smart integrations, planning considerations, infrastructure, and procurement options to consider.
An important distinction here is that people counting is not people tracking. These solutions aren’t tracking individuals, rather, they are counting how many people have entered or exited a particular area. We’ve found that solution providers are keenly aware about concerns around data privacy and promote the fact that their sensors do not collect and store PII (personally identifiable information) and are GDPR (General Data Protection Regulation) compliant. To minimize the “big brother” stigma, deploying OMS requires up-front transparency with occupants about the intended uses, the benefits, and what data is being collected. Institutions that make occupancy data available for student research projects will find that transparency bolsters adoption and reduces concerns.
The hardware end of the solution consists of Internet of Things (IoT) sensors distributed within the space, typically mounted in the ceiling or directly over a doorway. There are various sensor technologies to choose from: passive infrared, motion sensing, light detection and ranging (LiDAR), optical sensors, Wi-Fi localization, Bluetooth beacons, and so on. Many sensors are powered and communicate via Power over Ethernet (PoE) data cabling, while some are simple beacons that plug into a standard AC wall outlet. Different sensors come with their own considerations, including—but not limited to—coverage area (how much area will one sensor cover?); accuracy (what level of detail can these sensors measure occupancy?); infrastructure (how do these sensors communicate and receive power?); privacy (are these sensors collecting PII data?); and security (how might the students steal or vandalize the sensors?).
The software side of OMS leverages a cloud-based database that collects, aggregates, visualizes, and reports occupancy data using a web dashboard. The software is where campus facilities staff can access dashboards showing real-time and historical occupancy data overlaid on 2D floor plans. Staff can query occupancy in classrooms, collaborative spaces, student commons, fitness centers, or larger areas such as libraries. Predictive analytics embedded in the software can aggregate occupancy data over a defined period of time to predict how busy a space will be in advance.
Through the use of application programming interfaces (APIs), an OMS may exchange data and functions with other building systems, services, and applications. For example, an OMS can connect to the building automation system (BAS) to control demand-response ventilation. Campuses can integrate the OMS software to a room booking application to help reduce overbooking of popular spaces. The most common integration is displaying real-time OMS data on building digital signage displays, showing the population of specific areas. These integrations make OMS a key component of your intelligent buildings toolbox.
It’s critical to identify your drivers and applications for deploying OMS. Is the goal to understand trends in space usage for future capital planning? Is the goal simply to make sure a particular space does not exceed capacity limits during flu season? This all leads to objectively the most important question when considering OMS: What do you plan to do with the occupancy data you collect?
This all leads to objectively the most important question when considering OMS: What do you plan to do with the occupancy data you collect?
Once you understand your why, you’ll need to determine how accurate your counting solution must be (i.e., does it have to be down to an individual level, or is there an acceptable margin of error?). The more granular the data, the more opportunities for analysis. However, increased granularity comes with increased costs due to the larger quantity of sensors and infrastructure needed to support a greater level of detail.
Infrastructure will depend largely on the technology solution you select. Here are some common questions to ask during discovery:
- How many sensors are needed to cover my space? This will depend on factors such as acceptable accuracy tolerances, sensor mounting height, and specifications of the sensor selected.
- How are the sensors mounted? In the ceiling, on the wall, or over a doorway? Make sure these can be mounted in a secure location where students and occupants cannot tamper with them.
- How are the sensors powered? PoE is the most common method of power. This requires the IT department to understand any increases in port capacity and power draw on their network switch architecture, plus any right sizing of the telecom rooms required to accommodate additional structured cabling systems. Battery powered options exist, though these may be more expensive, and require battery maintenance.
- How do the sensors communicate with the software? If each sensor requires a wired data drop, there could be additional pathways, backboxes, and raceways required. Of course, Wi-Fi-connected sensors eliminate these requirements. Either way, given that many solutions have Internet-exposed sensors, the IT department will need to be sure this aligns with internal network security policies.
Procurement and Deployment
Many OMS solutions are available through platform as a service (PaaS) consumption models. The PaaS model packages the sensor and subscription license into a single monthly cost, simplifying scaling your solution up or down depending on your evolving needs. Other procurement models include a capital expenditure (CapEx) model (sensors and licensing are purchased up front) or hybrid models (sensors purchased up front with licensing on a recurring monthly basis).
We’ve found that PaaS is desirable, as it provides clear pricing, firmware and software upgrades, and extended warranties. It’s important to read the fine print and see if services such as installation, commissioning, and training are included, as these may require additional costs or vendor engagement.
The OMS market is in its infancy but is experiencing explosive growth and outside investment. The power to collect space occupancy data has never been more relevant as students and faculty return to in-person learning. With that in mind, it’s crucial to understand how occupancy data can help enhance your facilities management efforts and capital planning, and to look for solutions that best align with those objectives.
Ernie Beck, CTS-D, WELL AP, is a senior consultant at NV5 Engineering & Technology’s Washington, DC, office. He can be reached at firstname.lastname@example.org.