Building automation systems (BAS) have become progressively more advanced and increasingly use big data and artificial intelligence (AI). Big data represents the massive amounts of information businesses often have that are too challenging to manage and analyze through conventional means. BAS platforms typically generate big data through use, and AI algorithms help people extract meaningful information. The intersection of two technologies can result in better outcomes for users.
Tighter Security and Surveillance
Many buildings now have security cameras and access control systems that work with data analytics and AI. The combination of big data and well-trained AI algorithms can tell the difference between someone who lives in an apartment building and a visitor.
Some companies also rely on advanced technologies to spot the improper behaviors that often lead to accidents. Protex AI is a company deploying computer vision and artificial intelligence to detect health and safety violations. Dan Hobbs, the CEO and co-founder, said most accidents happen because people repetitively engage in risky behaviors. He also recognizes how data and safety go hand in hand, but manual processing methods are too labor-intensive. His company speeds up big data analysis with AI.
Artificial intelligence can spot hazardous behaviors. Data collection allows people to go deeper and see where problems occur, giving them the specifics to fix them. That approach could enable facility managers and others to see if accidents are more likely on certain extremely slippery sidewalks. It could also reveal how specific areas need more traffic control measures because they get crowded and risks increase.
However, decision-makers using BAS systems to collect data that may identify people must uphold all relevant privacy laws. Rice University researchers discovered how locally sensitive hashing could maintain big data privacy as people use or share information while using machine learning. It also makes the information more manageable by summarizing huge databases of sensitive content. The team reported this method is 100 times less expensive to run than current options.
Improved Energy Management
There are abundant opportunities to combine AI and big data for better energy efficiency. One academic paper examined the possibilities and identified several promising paths. For example, a system using AI and big data could find abnormalities in energy usage patterns, prompting people to take a closer look at the reasons.
Another case study explored in the paper involved applying energy management to a sports facility, using data and algorithms to maintain energy efficiency and predict future needs depending on activities in the building.
Incorporating big data and AI into predictive maintenance strategies is also becoming more common. A BAS could help technicians know when to take specific measures to keep energy usage as low as possible. A dirty condenser coil can cause a 30% increase in energy requirements for compressors, so people must adhere to the correct maintenance schedules.
Researchers also examined how AI and data analysis could keep buildings at the ideal temperature for occupant comfort while prioritizing energy efficiency. One study involved training algorithms with 1,700 datasets to create an intelligent system to meet occupant needs.
Elsewhere, a team explored using AI and big data to improve the energy usage of two five-story residential buildings in a hot, humid climate. They collected indoor air temperature, electricity usage and relative humidity information and asked for comfort-related feedback from approximately 18 households.
One important takeaway was that west-facing units used 20% more energy than north-facing ones. It suggests the amount of sunlight exposure for each property could indicate which would benefit from big data-AI applications most.
The group recommended using AI to dynamically adjust the indoor temperature, plus provide actionable insights to residents with above-average electricity usage. Then, people simultaneously stay comfortable and reduce unnecessary electricity consumption.
Enhanced Occupant Experiences
As decision-makers deploy BAS to curb unnecessary resource usage and gain visibility, they must also explore how AI and big data could collectively bring more satisfaction to a building’s users. Many companies rely on big data to learn about customers and track related trends. Doing so improves consumer perception and makes them feel their favorite brands understand and cater to them. Building automation professionals can also rely on AI and big data to elevate visitors’ perceptions.
Many BAS systems track occupancy levels, and people could leverage that data to determine when garbage cans need emptying. Workers only tend to the bins once people have used them enough to justify it. That approach enhances occupant convenience and workflow management. Alternatively, suppose facilities managers see areas generating exceptionally high amounts of recycling or compost. They could add more bins there for everyone’s convenience.
Plus, applications that work with big data and AI can accelerate waste-sorting tasks. In one example, a team trained deep-learning algorithms on a dataset containing six types of trash. The AI successfully detected the garbage type with more than 89% accuracy after the training and testing stages.
Restrooms are other ideal areas to target. Sensors could collect information that goes into a big data platform. People can then analyze details, such as how often a door opens or closes, to determine how many occupants have used a specific bathroom. Some facility managers also rely on sensors and AI for leak detection. It can cost as little as 10 cents per day to monitor areas with small sensors. Artificial intelligence used on those connected products can reduce false alarms.
AI and Big Data: An Ideal Pairing for BAS
These examples show why examining feasible ways to benefit from big data and AI with a building automation system makes financial and operational sense. A BAS already has so much data, and people can use it with artificial intelligence algorithms and specialized information analysis platforms.
