Enhancing Middle Stream of Fluorocarbon Gas Management in Malaysia through AI-Driven Solutions

Fluorocarbon (FC) gases, widely used in refrigeration and air-conditioning (RAC) systems, posesignificant environmental risks due to their ozone depletion potential (ODP) and global warmingpotential (GWP). In Malaysia, the midstream (usage) phase of FC gas management remains acritical hotspot for emissions, primarily due to undetected leaks and inefficient maintenancepractices. Traditional reactive approaches to leak detection and maintenance are insufficient toaddress these challenges, necessitating a shift toward proactive, AI-driven solutions. This studyexplores the potential of digital technologies, including IoT-enabled sensors, predictivemaintenance algorithms, and blockchain-based inventory systems, to enhance FC gas managementin Malaysia. Using a mixed-methods approach, the research employs the DPSIR (Driving Forces,Pressures, State, Impacts, and Responses) framework and SWOT (Strengths, Weaknesses,Opportunities, Threats) analysis to identify key challenges and opportunities in the current FC gaslifecycle. The findings reveal that AI-driven predictive maintenance and real-time leak detectioncan significantly reduce emissions, improve energy efficiency, and extend the lifespan of(refrigeration and air conditioning) RAC equipment. Furthermore, integrating blockchaintechnology can enhance transparency and compliance in FC gas inventory management. The studyconcludes that adopting these digital solutions, alongside structured training programs fortechnicians, can transform Malaysia’s midstream FC gas management, aligning it with globalsustainability goals. This research contributes to the growing body of knowledge on AI-drivenenvironmental management and offers actionable insights for policymakers and industrystakeholders.