Conceptual Design of an AI-Assisted PCM Thermal Panel for Sustainable Building Applications.

The increasing demand for heating and cooling in buildings, driven by rapid urbanization and climate change, has led to higher energy consumption and carbon emissions. Improving thermal energy efficiency has therefore become an important objective in sustainable building design. This paper proposes the conceptual design of an Artificial Intelligence (AI)-assisted Phase Change Material (PCM) thermal panel for residential and commercial buildings. The proposed system combines encapsulated PCMs with embedded temperature sensors and an AI-assisted control framework to improve indoor thermal regulation. During periods of high temperature, the PCM absorbs and stores excess heat, while during cooler conditions it releases the stored heat, thereby maintaining a more stable indoor temperature and reducing dependence on conventional heating, ventilation, and air-conditioning (HVAC) systems. The AI component continuously analyzes environmental parameters such as indoor and outdoor temperature, humidity, occupancy, and weather conditions to support intelligent thermal management and optimize panel operation under different climatic conditions. This paper presents the conceptual architecture, operating principle, and expected performance of the proposed system based on existing research in PCM technology and AI-assisted energy management. The proposed design is expected to enhance thermal comfort, improve building energy efficiency, reduce electricity consumption and carbon emissions, and support the development of sustainable and smart building infrastructure. Keywords: sustainable construction; Artificial Intelligence (AI); energy efficiency; Phase Change Material (PCM); Thermal Panel; Thermal Energy Storage; Smart Buildings