Industry

• Professional, Scientific, and Technical Services (MMajor)
• Other Professional, Scientific, and Technical Services (76Subcategory)

Industry Pain Points

• Low Energy Efficiency: The operation of air conditioning systems typically requires a large amount of energy. The consumption of energy negatively impacts the environment and also results in high energy costs for companies and individuals. Therefore, improving the energy efficiency of air conditioning systems is crucial, which includes developing energy-saving technologies, optimizing design, and control systems to reduce wastage and carbon emissions.
• Low Degree of Intelligent Control and Automation: Air conditioning systems often rely on manual adjustments, lacking smart management, which results in low energy efficiency and inconvenience.
• High Maintenance Costs: Air conditioning systems typically operate for extended periods and require consideration of material quality, design reliability, and regular maintenance to extend their lifespan and reduce maintenance costs.
• Difficulty in Knowledge Transfer: The operation of chiller rooms has long relied on the transmission of expertise through experience, but this unconverted systematic knowledge can lead to a knowledge gap, affecting the overall safety and efficiency of operations.

Benefits of AI Implementation

• Enhanced Energy Efficiency: Artificial intelligence can train on vast datasets, including temperature, humidity, and power usage, to optimize the operation of air conditioning systems. Moreover, through intelligent monitoring and prediction, it can automatically adjust the operational modes of air conditioning equipment/to achieve energy-saving effects.
• Optimized Fault Prediction (Alert) Processes and Reduced Maintenance Costs: Artificial intelligence can perform fault prediction and issue early warnings by monitoring and analyzing operational data from air conditioning systems to detect potential faults and facilitate timely maintenance or repairs, improving system reliability and availability.
• Enhanced User Experience: Artificial intelligence can learn users' needs or habits and automatically adjust based on different scenarios and times, providing a more comfortable indoor environment. For instance, it can automatically adjust the airspeed and temperature according to external temperature changes, enhancing environmental comfort.
• Remote Monitoring and Management: AI and IoT can enable remote monitoring and management of air conditioning systems, reducing labor costs and operational risks.

Common AI Technologies or Applications

• Convolutional Neural Networks,QDeep Learning: Using AI technologies such as convolutional neural networks can analyze multidimensional data collected from sensors (like temperature, humidity, air quality, etc.), and adjust the air conditioning system settings accordingly. CombiningQlearning by experimenting with different configurations and receiving environmental feedback (such as user satisfaction) can optimize performance, making air conditioning systems respond more intelligently to environmental changes and user demands, achieving energy efficiency and improved comfort.
• Support Vector Machine, Convolutional Neural Networks: Using AI technologies such as support vector machines can analyze monitoring data to distinguish between normal operating conditions and potential fault signs. Through training, support vector machines can effectively identify patterns needing attention or early warning. Combined with convolutional neural networks, they learn and recognize complex patterns in the data, providing precise fault prediction and alerts, helping to minimize the downtime and maintenance costs of air conditioning systems.

「Translated content is generated by ChatGPT and is for reference only. Translation date：2024-05-19」