Occupancy estimation using environmental parameters

• المؤلف الرئيسي: Tan, Shannan Jing Xiang
• مؤلفون آخرون: Soh Yeng Chai
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2022
• الموضوعات: Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/158096
• المؤسسة: Nanyang Technological University

Occupancy information is important for energy efficient operations of Air Conditioning and Mechanical Ventilation (ACMV) systems. To predict the occupancy in a room, environmental sensors are increasingly used as cost effective and non-intrusive ways to obtain the occupancy information. This requires extraction of environmental parameters such as carbon dioxide, temperature and humidity which are used to provide a non-intrusive representation of occupancy in the room. These parameters are extracted by a data collection system consisting of a temperature sensor, humidity sensor and a gas sensor. This paper shows prediction using Logistic Regression to predict the occupancy of the room whether it is occupied or not occupied. Experiments are done in a small room in a building with few occupants.