Consider the job of a building administrator. Every day, that administrator makes sure that the complex systems which underlie any modern building (ie. HVAC, Security Access, Lighting, Water, and Electricity) are operating correctly and efficiently. If, for example, there is a major leak in a water pipe or the electricity goes out, then it’s up to the building administrator to assess the damage, dispatch fix crews, and get the system back online.
Additionally, that administrator may also be responsible for maintaining records detailing the efficiency of each system in order to provide answers when the building owner (or, more likely, a building operations team) asks, “Where are we spending the most money, and where can we save?”
To top it all off, they may be in charge of several different buildings each with different requirements (just think about the differences between a hospital and a power plant).
Due to the sheer complexity and scope of the job, building administrators rely on Building Management Solutions (BMSs) to help them quickly solve infrastructure problems and offer system level reporting to interested parties. Twenty to thirty years ago, these BMSs were in very early stage development, offering (at best) a way to gather building-wide metrics. These days, however, the advent of the BACnet/IP protocol, IoT, and AI have the potential to offer even more exciting benefits to building administrators.
First and foremost, a Building Management Solution must provide information to its users on which parts of the building’s systems are costing the most money to maintain. With insight on how the building’s systems affect the bottom line, business intelligence teams can take next steps to cut costs and energy expenditures.
For example, the data gathered from electricity meters over the course of a month can help a business analyst discover the optimal time to shut off the lights in a particular department of a museum. So at a minimum, BMSs provide value to business by describing the relationship between a building’s systems and its expenses.
But the promise of recent developments in machine learning and AI offer an even greater benefit - automated system optimization. If enough data is collected from each sensor in the building, then a computational model can be trained to provide answers to questions like, “When is the optimal time of day to dial down power consumption for department X?”, or “Under what circumstances should we divert more resources to department Y?”. In an intelligent BMS such as this, the system can learn from trends in historical data, and automatically optimize building functions to reduce costs.
So, IoT-powered BMSs provide a big win to building owners looking to reduce their energy use and expenses. By gathering, aggregating, and interpreting the raw data from the building’s systems, BMSs are uniquely able to provide the customer with insights that can help them save energy and cut costs. And as AI gets more and more sophisticated, these systems get even better at automating away the difficulties in maintaining a building complex.