Maximizing efficiency and sustainability: The role of AI in facility management / Ts. Elma Dewiyana Ismail

Ismail, Elma Dewiyana (2023) Maximizing efficiency and sustainability: The role of AI in facility management / Ts. Elma Dewiyana Ismail. RISE: Catalysing Global Research Excellence (3): 22. pp. 1-4. ISSN 2805-5883


Facility Management (FM) is a complex discipline that can benefit from the use of Artificial Intelligence (AI). AI has the potential to revolutionize FM by enabling data-driven decision-making and automation of routine tasks. This article explores the various applications of AI in FM and examines its potential benefits and challenges. Predictive maintenance is one area where AI can be applied in FM. By analyzing data from building systems and equipment, AI can predict when maintenance or repairs will be needed, allowing facility managers to schedule activities efficiently and minimize downtime and repair costs. AI monitors the performance of equipment, such as HVAC systems, elevators, and lighting, and analyzes data like temperature, vibration, noise, and energy consumption to identify potential issues before they become critical. Energy management is another area where AI can be valuable. By analyzing data from various building systems, such as HVAC, lighting, and electrical equipment, AI algorithms can identify patterns and inefficiencies in energy consumption. This enables facility managers to optimize energy usage, reduce costs, and improve sustainability. For example, AI can suggest modifications to improve energy efficiency, such as by installing energy-efficient lighting and adjusting HVAC settings. AI can also predict energy usage patterns and optimize energy usage accordingly.


Item Type: Article
Email / ID Num.
Ismail, Elma Dewiyana
Subjects: Q Science > Q Science (General) > Back propagation (Artificial intelligence)
Divisions: Universiti Teknologi MARA, Shah Alam > Vice Chancellor Office > Pejabat Timbalan Naib Canselor (Penyelidikan & Inovasi)
Journal or Publication Title: RISE: Catalysing Global Research Excellence
ISSN: 2805-5883
Number: 3
Page Range: pp. 1-4
Keywords: Facility management, data-driven decision-making, automation
Date: November 2023
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