For many facility managers, employing IoT devices allows them access to a realm of data concerning their energy management that was not visible before. However, it is important to be able to both find the right mix of data and have the ability to interpret it to optimize energy efficiency.
In the energy management and smart building space, the data that businesses gather most often are:
- Energy consumption
- Equipment run times and cycle times
- Cooling and heating equipment status (mode of operation, fan status)
- Occupancy sensing and people counters
- Indoor space temperatures
- Cooler, freezer, and food preparation temperatures
- Leak detection
- Thermostat settings (cooling and heating set points)
- Outdoor temperature
- Local operator overrides (deviations from corporate standards–schedules, lighting, and thermostat settings)
- Light levels
- Humidity (indoor and outdoor)
- Indoor CO2 level
- Security status
Collecting data from IoT devices gives businesses remote, continuous visibility into key metrics that affect performance and efficiency. The information is used to identify poorly performing equipment and properties in order to schedule equipment repairs and allocate resources for efficiency upgrades. This is particularly important when there are multiple locations so maintenance and upgrade budgets can be allocated to optimize returns.
In addition, the data can also be used to monitor environmental conditions, such as lighting and HVAC, and make adjustments to maintain employee and customer comfort. These insights also allow the ability to monitor for conditions that may adversely affect health and safety, like indoor CO2 levels and security systems.
These connected systems allow businesses to create and maintain environments that are adaptive to environmental conditions and responsive to employees and customer needs. For example, connected systems can analyze data to adjust the temperature based on the number of people present or dim the inside lights if it is a bright day outside. Over time, the data collected from connected systems can be used to identify patterns and detect when equipment is beginning to fail – which allows for repairs and maintenance to be scheduled before employees and customers are affected.