You are currently viewing 7 Ways of ARTIFICIAL INTELLIGENCE is that the way forward for FACILITY MANAGEMENT


The breadth of the technology occasionally creates confusion about what AI actually can do. 7 ways of AI is that the way forward for FM.

  1. Energy monitoring and measurement and verification (M&V)

M&V could also be an excellent example of AI, because it takes what are often a very complex set of calculations (creating a building’s performance model) and automates them. Then, new variables, like weather and occupancy, are often used to provide energy consumption estimates using the same model. With enough data to observe the correlation between energy, weather, and occupancy, an accurate model is often used to calculate one of these variables if the others are available. Within the case of M&V, actual weather and occupancy are often used to estimate energy use under a pre-retrofit scenario, which can be compared to the actual energy consumption after the retrofit. The difference between actual and predicted energy could also be a more accurate because of track energy savings.

2. Demand management

 Before or behind the meter. Understanding current energy demand is extremely important for grid reliability. Utilities got the skills of much power they’ll need to supply and wish to avoid generating an excessive amount of high demand charges for using an excessive amount of energy at the wrong times. More data on energy consumption and thus the characteristics that drive that use (such as weather and occupancy) can translate into better predictions about how the grid will behave. With this data, it’s possible to reduce energy demand, economize, and increase grid reliability.

3. HVAC (Heating, ventilation, and air conditioning) optimization.

In terms of demand management, understanding the performance of subsystems, like HVAC, is vital. within the summer, cooling demands in an office are often the difference between setting a replacement, costly demand peak, or avoiding a hefty charge. AI can provide cost savings by pre-cooling a building within the first mornings supported calendar/meeting and historic occupancy data. The building’s HVAC system would start early in the morning, when energy may be a smaller amount expensive, and begin cooling space for the day ahead, all without human intervention. Moreover, if a building has used a pre-cooling strategy within the past, AI may help improve future pre-cooling efforts. because the Google data center example suggests, there are significant opportunities for savings by employing AI.

4. Equipment predictive analysis.

Data pulled from complex machines found in buildings, like chillers and boilers, are often overwhelming to facility managers. But, when these data streams are analyzed by a software solution, trends may appear. This analysis may indicate a high likelihood of failure within the near term, supported the condition of the equipment and reasonable estimates about how it’s used (such needless to say operating times). The extra insight, which can help a facility team plan upcoming maintenance, can reduce unexpected equipment outages, add predictability to the budget, and keep occupants comfortable.

5. Space planning.

As more offices move to open plan designs and more flexible arrangements, there’s some risk of a shortage of space, especially at peak times. Reducing the amount of space an excessive amount of or increasing occupancy, may increase these costs, but also may cause a poor working environment. With an increase in indoor space sensors, it’s possible to predict demand at different times — both when planning a replacement open office and only for day-to-day management AI helps by pulling within the data from these space sensors and providing estimates of occupancy, plus information which may help to resolve potential issues.

6. Predict facility cleaning needs.

Custodial(guardian) staff typically clean all occupied spaces regularly. This schedule-based approach is suitable for busy spaces that are consistently used. But, with more flexibility in how occupants interact with spaces, it’s likely that some spaces are getting to be used by others. There is a chance for spaces to be cleaned only they need it, supported actual use. Today, this cleaning schedule could even be supported sensors that track occupancy, but AI can help to predict cleaning demands and even generate a schedule for service providers. Moreover, AI can optimize supply by automatically ordering various materials and products for the office space, supported actual and predicted occupancy trends.

7. Safety and security.

Many commercial buildings spend an enormous amount of money on the indoor safety of their offices. There is a spread of AI applications related to safety and security, though many are growing. As an example, instead of employing a key card for access control, one startup is using face recognition. Safety and security use cases may raise some questions on privacy, which is one reason that they will not be as common as other applications, a minimum of not yet.

Regardless, AI applications in buildings also can drive younger employees to enter the industry. Facility management is facing a talent shortage: the standard employee is 51 years old. Younger employees typically look for positions that provide modern technology, and AI solutions could provide this for buildings. The facility management industry has not been effective at attracting young talent as lately. But AI technologies may remove variety of the chief tasks and make the industry more attractive to a replacement generation.

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