Advisor
Co-advisor
Research Topic
Occupancy-Driven Energy Conservation Strategies for Sustainable Smart Buildings
Research Abstract
Internet of Things and Artificial Intelligence are two technologies that are increasingly being used to improve energy efficiency in smart buildings. IoT sensors can be deployed throughout a building to collect real-time data on energy consumption, occupancy patterns, activity recognition, and environmental conditions. This data can then be analyzed using machine learning algorithms to identify patterns and optimize building energy consumption. For example, Neural Network algorithms can be used to predict occupancy patterns, so that a building can adjust heating and cooling systems accordingly, or to identify areas of the building that are using excessive energy and recommend energy-saving measures. By combining IoT and machine learning, smart buildings can achieve significant energy savings and improve occupant comfort and productivity.