Evaluation of Direct and Indirect Methods for Occupancy Detection and Air Quality Control in Buildings

Objectives

The aim of this master thesis is to evaluate direct and indirect methods for detecting occupancy in buildings, focusing on their application for air quality control. Through a combination of literature review and experimental work, the thesis will assess the use of CO2 sensors for indirect occupancy detection. The experimental activities will take place at the KTH Live-In Lab, where new methodologies for occupancy estimation using CO2 data from ventilation systems will be tested.

Background

Occupancy detection plays a crucial role in optimizing energy consumption and improving air quality in modern buildings. Current methods can be categorized into direct (e.g., motion sensors, cameras) and indirect methods (e.g., CO2 levels). Indirect methods are less intrusive and often more cost-effective but require more sophisticated algorithms to accurately estimate occupancy levels.

This master thesis will focus on assessing both direct and indirect methods of occupancy detection, with a particular emphasis on indirect methods using air quality sensors. The experimental activities will be carried out at the KTH Live-In Lab, a platform for innovation where industry and academia develop and test new technologies and methodologies in real-world conditions. The project aims to explore the potential of CO2 sensors installed on ventilation collectors to estimate building occupancy and to collaborate with companies such as Equa and Bengt Dahlgren for practical insights and validation of methodologies.

Task description

The master thesis will consist of the following tasks:

Literature review on both direct and indirect methods for detecting occupancy in buildings, including their strengths, limitations, and applications for air quality control.
Experimental Activity:
- Perform experimental tests on the use of CO2 sensors for estimating building occupancy.
- Install and monitor CO2 sensors on ventilation collectors in the KTH Live-In Lab.
- Analyze data to assess the effectiveness of CO2 levels as an indicator of occupancy.
Building modelling
- An existing IDA ICE model will be used to evaluate different time schedules for occupancy in the building
- Energy utilization in KTH Live-In Lab will be simulated and compared using time schedules for lighting, equipment and occupancy using data from experiment.
- Update and optimize the existing IDA ICE model of KTH Live-In Lab

Learning outcomes

Upon completion of the thesis, the student will achieve the following:

In-depth understanding of both direct and indirect methods for occupancy detection and their applications in building management systems.
Experience with real-world experimental activities, including the installation, monitoring, and analysis of CO2 sensors.
Experience in processing and interpreting sensor data to estimate occupancy levels in buildings.
Practical experience working with real-world systems and industry partners to integrate occupancy detection methodologies into air quality control systems.
Be able to analize, update and optimize indata for a Building model