An Adaptive Model for Distributing and Balancing Air Conditioning in Crowded Places

This paper studies how the Heating, Ventilation, & Air conditioning (HVAC) systems can be optimized in response to global heat and energy demand rises. We advocate a performance based framework geared towards high-density sites such as terminals and malls to obtain energy efficiency without sacrificing operational function. The model combines cutting-edge sensors, control and variable components, and feedback loops to continuously adapt HVAC usage in response to temperature, humidity data, and occupancy levels. An important feature of the model is its use of Internet-of-Things (IoT) technology to make networked devices able to share information automatically. Those types of integration include power consumption, network dynamics, load forecasting, and even user perception, making the model so resilient and scalable. The method is intended to be adaptable as situations arise based on changes in incident weather and room usage. A major consideration has been including potential users (especially older people). The goal is to improve occupant comfort, save energy, and encourage sustainable management of HVAC systems in crowded spaces. Experimental results show that there can be a high energy saving if certain scenarios are considered without compromising the comfort of living.