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Future Trends: What Lies Ahead for AI in Facility Management

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By Raghav Kapur, Director, SILA

For commercial and residential real estate owners opting for professional facility management services, the implementation of advanced technologies has been unlocking many cost, security and optimisation benefits. This is especially true with artificial intelligence (AI) technology, with human intelligence being simulated by machines or software to transform how large real estate spaces are managed with minimum human intervention. What’s more, AI-powered applications are able to perceive, reason, learn and interact with machines, equipment and even humans, to perform cognitive tasks more efficiently and without any lapses. Recognizing AI’s potential in revolutionising the facility management space, let us look at key trends that are likely to become the new normal in the near future.

Powering management and conversational tools to improve response times

For large real estate spaces with high user movement, the task of managing different building systems within the premises can be a daunting affair. While building management systems (BMS) have relied on traditional computer technologies to monitor and control these systems, gaining valuable insights on equipment performance and applying optimization strategies still requires human intelligence. With AI systems however, it is possible to extrapolate energy and resource consumption in different external climatic conditions and manage critical systems in line with occupancy patterns, all without the need for human involvement.

AI-enabled sensors can enable facility management firms to schedule predictive maintenance operations and even determine the periodicity of operations like filter cleaning in line with seasonal changes. Combining this with AI chatbots that can understand user inputs and accurately interpret them, it is possible to achieve quick response times when complying with user demands, while also unlocking significant efficiency gains and reducing labour requirements. Thus, facility management firms that are increasingly integrating AI in their existing systems are best placed to manage modern buildings, providing huge cost savings by preventing machine downtime and maintaining superlative occupant comfort standards.

Reducing energy consumption by tracking user movement

In conjunction with the internet of things (IoT) technology that facilitates communication between connected devices and the cloud, AI-enabled sensors can help optimise energy consumption in line with changing occupancy levels. This is done by continuously measuring the temperature difference between ambient air and required comfort conditions, automatically enabling or disabling HVAC systems across all monitored spaces within large buildings. Other parameters such as humidity, ventilation and occupant movement are also considered to achieve energy- efficient cooling and heating operations, with totally autonomous and self-adaptive AI softwares constantly working towards maintaining the best airflow conditions.

For industrial premises too where chillers are often employed to manage air quality standards, AI-powered control systems can reduce PM 2.5 concentrations by as much as 90%, while also optimising energy consumption by as much as 25%. In fact, with sustainability now being the central theme when designing and constructing new buildings, the role of AI in reducing energy consumption and paring down the overall carbon footprint of building operations will gain more prominence.

Automated vehicle, visitor and attendance management through AI-powered surveillance

In order to maintain high safety and security standards across residential or commercial projects, it is important to detect threats or potential hazards 24X7 and take remedial action instantaneously. Towards this end, automatic number-plate recognition (ANPR) technology is being increasingly deployed to scour vehicle images and detect unauthorised entry. For human movement, AI-based facial recognition technology can detect multiple faces in an image and compare them with internal databases to screen visitors with 100% accuracy.

This negates the need for invasive and manual screening methods that can cause dissatisfaction and inconvenience, ushering in a more superior visitor management system that can cater to heavy vehicular and human movement. From an attendance point of view too, AI-powered location or facial based attendance systems can provide accurate attendance and payroll-ready reports, eliminating the need for manual roll calls and other traditional yet inefficient methods.

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