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4 Revolutionary Applications of AI in Facilities Management

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You may have observed the term appearing frequently in headlines, blogs, and media coverage in recent years, but Artificial Intelligence (AI) extends beyond self-cleaning vacuums and coffee-brewing robots. It is increasingly integrated into technologies and structures within the built environment, subtly shaping and improving routine processes. For instance, ‘Smart’ buildings incorporate AI technologies from inception, facilitating intelligent automation for climate control, security, cleaning, maintenance, lighting, and parking.

According to experts, the potential benefits of integrating AI into business operations are significant, with projections indicating trillions of dollars injected into global economies. This is primarily attributed to productivity gains achieved through automation—where machines handle tasks previously done by humans—or through augmentation, where machines assist the existing workforce in extraordinary ways.

 AI in Facilities Management

 

These advantages are in line with objectives such as resource conservation, time efficiency, and operational cost reduction—objectives familiar to anyone in facilities management. This rings particularly true for those overseeing extensive, multi-building operations where the implications of inefficiency and wastage can escalate significantly.

The promising news for facility managers (FMs) is that AI functions by empowering machines and networks to learn from experience, analyzing extensive datasets and adapting to new inputs by identifying patterns within this information. Rather than manually executing repetitive and time-consuming tasks like approving work orders, scheduling preventative maintenance, and analyzing labor expenses, facility management (FM) software equipped with AI capabilities can automate these processes, executing tasks with minimal human involvement. Consequently, managers stand to gain from expedited processes, conserved resources and energy, reduced expenses, and a streamlined workflow that adopts a proactive rather than reactive approach.

what is facility management

Facility management (FM) is a multidisciplinary field that involves the management and maintenance of buildings, facilities, and infrastructure to ensure they operate efficiently, effectively, and safely. The primary goal of facility management is to create and maintain a productive work environment that supports the organization’s objectives and meets the needs of its occupants.

Let’s delve deeper into four pioneering applications of AI currently shaping the FM industry.

Revolutionary Applications of AI in Facilities Management

1. Predict Faults & Schedule Preventative Maintenance

According to the International Society of Automation, machine downtime globally results in a staggering loss of $647 billion annually. Regardless of the cause—be it seasonal changes, heightened usage, or equipment aging—appliances and machinery are susceptible to eventual faults, which can lead to significant financial losses for businesses.

AI-driven FM software has the capability to anticipate and prevent breakdowns by analyzing historical data on past asset failures, services, and labor requirements. This information is utilized to automatically generate work orders and route them to the appropriate vendors.

AI technology seamlessly integrates with IoT networks, which monitor the health and functionality of devices and appliances by establishing benchmarks for ‘normal’ and ‘abnormal’ input and output. Whenever an anomaly is detected, AI algorithms can pinpoint the issue, estimate the time and cost required for resolution, and schedule qualified labor accordingly. Moreover, invoicing processes become more efficient as scheduled work orders are automatically initiated, closed, approved, and remunerated based on analysis of past orders with similar scopes.

An exemplar of AI-powered FM software aiding in these tasks is ServiceChannel’s Decision Engine. This solution employs prescriptive analytics to assist FMs in making informed, data-driven decisions regarding contractor selection, proposal reviews, and maintenance scheduling. With AI-driven automated maintenance and breakdown detection, even small facilities management teams can effectively oversee hundreds, if not thousands, of buildings and assets with significantly reduced machine downtime. Consequently, this diminishes expenditure and affords FMs more time to concentrate on higher-priority tasks.

2. Reduce Energy Expenditure

In terms of expenditure allocation, businesses typically allocate a higher percentage of their budget to energy resources—such as heating, cooling, ventilation, electricity, and water—compared to other categories of building management. According to National Grid, energy costs typically constitute approximately 19% of total expenditures for the average commercial facility in the US. Clearly, this category warrants careful management attention, both in terms of cost reduction and environmental consciousness.

While numerous methods exist to reduce energy consumption across facilities, AI offers a hands-off approach to addressing major energy drains like HVAC, refrigeration, and electricity. Through predictive analytics, AI-enabled technology can monitor and optimize energy usage in real-time. For instance, it can adjust heating levels during periods of inactivity based on historical usage patterns derived from advanced models of a building’s thermal characteristics or IoT sensors detecting foot traffic.

The Nest thermostat exemplifies accessible AI technology, having been available since 2011. As advertised on the brand’s website, this AI-powered thermostat “learns what temperature you prefer and creates a schedule around it.” Independent studies have demonstrated that the Nest thermostat can save residential users between 10-12% on heating bills and up to 15% on cooling. While currently only utilized for commercial purposes in small buildings and offices, the potential for savings in these environments is likely even greater.

Beyond real-time monitoring, AI technology, in conjunction with IoT and remote management dashboards, can also detect energy leaks and operational inefficiencies, such as poorly fitted HVAC ducts or a malfunctioning electrical transformer. It can even forecast when these issues are most likely to occur. This enables FM teams to enhance planning and strategy regarding energy costs and facility occupancy.

3. Identify Security Risks

AI is revolutionizing physical security measures at commercial facilities, addressing a significant priority for most FM teams, although it may not always be given top priority until a breach occurs. As surveillance systems become more intricate and the volume of security-related data expands, AI can help bridge the gaps where manual review and management fall short.

In the realm of FM security risks, examples include access control, CCTV surveillance, intrusion detection, package screening, and weapon detection, all of which rely on data-driven security technology. While these applications offer utility on their own, integrating artificial intelligence and machine learning can enhance their effectiveness.

A prominent startup, Aegis AI, has developed AI-powered software capable of identifying when a person in video footage is carrying a weapon. This layer of situational awareness adds considerable value to facility security programs, particularly when supplemented with emergency alerts and notifications to first responders.

Another emerging company, IC Realtime, has introduced “Ella,” an app and web platform leveraging AI to analyze CCTV footage and make it instantly searchable using tags such as “red car” or “black hoodie.”

Such AI-enabled technologies hold immense promise for businesses with extensive facilities or retail presence. Traditional surveillance systems often require a team of security personnel to monitor multiple screens simultaneously, with the level of surveillance directly correlating with the number of individuals required to oversee it—a costly investment prone to human error. AI presents a potent solution capable of processing vast amounts of visual data without fatigue, detecting less obvious threats like shoplifting or the delivery of suspicious packages that might otherwise go unnoticed under human supervision.

4. Smarter Reporting & Analytics

An extensive analytics program is crucial for the success of any FM team. By analyzing facility data, managers can enhance visibility, make data-driven decisions, and strategize for long-term initiatives while adhering to budgetary constraints and overarching goals.

In today’s landscape, AI is transforming the traditional analytics paradigm. Historically, facility data was manually sorted, and decisions were often influenced by an analyst’s intuition. AI now automates these processes, generating quicker and more reliable insights through a comprehensive analysis of historical data. By mitigating human biases and errors, AI-powered FM software efficiently distinguishes between capital and operational costs, enhances predictability, and refines demand forecasting.

Furthermore, AI in FM analytics offers consistency. Even new or inexperienced employees can make informed choices in asset management with AI-enabled software. Backed by years or decades of facility data, prescriptive analytics guide decision-making processes and recommend logical, cost-effective actions, minimizing the need for manual research.

Ultimately, personalized insights from AI-powered analytics enable businesses to reduce costs, prevent breakdowns, and maintain satisfaction among both customers and employees.

Final

The potential of IoT and AI in facilities management is just beginning to unfold, but their prospects appear promising. Some experts suggest that FM could be the industry poised to reap the most benefits from AI in the foreseeable future, particularly considering its abundance of repetitive and time-consuming tasks. With AI-enabled technology integrated, FM professionals stand to gain enhanced efficiency, cost reductions, strengthened contractor relationships, and improved asset reliability.

 

 

 

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