Energy Management: Finding Data That Matters

For many facility managers, the utilization of IoT devices is providing access to a realm of energy management data that was previously not available to them. But to optimize energy efficiency, determining the appropriate mix of data specific to their facility, along with the ability to interpret it, is essential.

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

By providing continuous remote access to key metrics affecting performance and efficiency, the data collected via IoT devices can identify poorly performing equipment and properties so that equipment repairs can be scheduled promptly, or resources allocated for efficiency upgrades. This information is particularly important when there are multiple locations as maintenance and upgrade budgets must be allotted to optimize returns.

In addition, this data can be used to monitor environmental conditions, such as lighting and HVAC, and make adjustments to maintain employee and customer comfort as necessary. These insights also offer the ability to monitor for conditions that may adversely affect health and safety, like indoor CO2 levels or security systems.

By integrating these systems, businesses can create and maintain workplace ecosystems that are both adaptive to environmental conditions and responsive to employee 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, allowing for repairs and maintenance to be scheduled before employees and customers are affected.


Curtis Sammer

FSG Energy Software Manager

Joining FSG in 2011, Curtis has a diverse educational background in electrical engineering and computer science. His work experience spans several industries--aviation training, heavy machinery, computer manufacturing, product development, and most recently, building controls. In each of these fields, Curtis was directly involved on a hardware, software, and technology level. If Curtis had one superpower, it would be taking what innovators do and automating it at scale. Currently, Curtis devotes his time to working with open source technologies, cloud environments, and agile development techniques to generate robust, scalable, affordable enterprise capabilities in the energy industry.

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