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    Innovator in the Spotlight

    Sietse de Vries

    A photorealistic simulation of dynamic natural light for perception in VR

    EngD trainee Sietse is working on a photorealistic simulation of dynamic natural light for perception in virtual reality (VR). His research is part of the IntelLight+ project.

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    New project videos: Brains4Buildings

    The built environment is responsible for about 36% of the global energy demand. About 5-30% of the energy use of buildings is related to energy waste due to faults in heating, ventilation and air conditioning systems. The goal is to develop a self-learning module that can monitor and diagnose climate systems in large buildings.

    Generic, robust and reliable fault detection & diagnosis tool

    Rick Kramer is the leader of this project and Srinivasan is one of his PhD candidates. Srinivasan is focusing on developing a generic, robust and reliable fault detection and diagnosis tool that can help with the early detection of these faults and eliminate energy wastage.

    Personalized control system in an office environment

    Within this project, EngD trainee Petros is focusing on the people within large buildings. He is doing research on the control and functionality of a personalized control system that people will be able to use in their office environment to tailor it according to their needs and preferences.

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    CM-FDD-HVAC

    Continuous Monitoring and Fault Detection Diagnosis of large HVAC systems
    (Heating, Ventilation and Air Conditioning)

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    Start year 2019

    About the project

    The need to reduce CO2 emissions makes energy in the built environment a key issue given that inefficient buildings represent around 35% of the total energy consumption. Continuous Monitoring (CM) and Fault Detection and Diagnosis (FDD) are complex but important technologies in detecting inefficiencies in Heating Ventilation Air Conditioning (HVAC). With a rise in demand for cooling caused by global warming, this project is developing a new approach based on data analytics and machine learning. This will enable resulting CM and FDD modules to be programmed in a state-of-the-art Building Management System (BMS) and become market-ready by the end of the project.

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    Wim Zeiler I Project leader

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    In full speed with students and young professionals

    14 February 2022
    We are already over a month into the new year and, despite COVID, we kicked off at full speed!
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    ECoS-IAQ

    Partners

    Start year 2020

    About the project

    Installations in buildings are responsible for around 35% of all energy consumption, approximately 20% of which is due to inefficient operations. Inferior environmental conditions within classrooms can have both short- and long-term health effects, mainly due to the presence of particulate matter. With greater insights into sensors, data interpretation, trend signaling, continuous monitoring, fault detection/diagnosis and predictive maintenance, problems can be identified in the Heating Ventilation Air Conditioning (HVAC) systems of schools. The ECoS-IAQ project focuses on the creation of product development concepts for air handling manufacturers, air filter manufacturers, control companies and installers.

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    Wim Zeiler I Project leader

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    ECoS-IAQ

    Partners

    Start year 2020

    About the project

    The goal is to develop a self-learning module that can monitor and diagnose climate systems in large buildings. This will enable a climate system to perform better; for instance, lower energy consumption, better thermal comfort and better air quality. More efficient maintenance is also possible. The module will be used as an add-on for the Building Energy Management System (BEMS) of offices.

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    Wim Zeiler I Project leader

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    More about the project

    Rick Kramer – Project leader & Srinivasan Gopalan – PhD canditate

    Petros Zimianitis – EngD trainee