Design of a sustainable, positive energy building model for community living can be mapped to many sustainable development goals. A transdisciplinary project based learning approach for graduate students of environmental design and mentors from different disciplines through regular interaction with …

"The aim of the regional and transnational collaboration within the CoVE SEED project is to develop regional Centres of Vocational Excellence (CoVEs) for sustainable energy education. Continuous boundary crossing occurs throughout this collaborative process. However, limited insight existed into what …

The question is, can the faculties provide data on their energy consumption to raise energy awareness with students and employees? Typically, campus cafeterias show us how it's done and set a good example by displaying the carbon dioxide emission score of the daily menu. The challenge typically lies …

The transition to sustainable energy systems is both technological and social, requiring new forms of learning, collaboration, and governance. This poster examines how inclusive skills ecosystems can foster a just energy transition by drawing on insights from a bi-continental capacity-building network …

Technical report summarizing the work of KIEM Spotter

The Brains4Buildings project aims to develop methods to design new smart building climate management systems that, among other things, reduce energy consumption, increase comfort and respond flexibly to user behavior. We set out to develop design guidelines to help B4B stakeholders when designing innovative …

Paper voor TRA2024

Slomp, J. and Gupta, J.N.D., Lean Planning & Control in a High-Variety/Low-Volume Environment, 2024, in Challenging the Future, Proceeding of the European Lean Educator Conference, ELEC 2023, ‘s-Hertogenbosch, The Netherlands, October 24–26, 2023, Editors Ton van Kollenburg, Alinda Kokkinou, and Olivia …

.College Reader and educational model HVAC and Smart Grid

Anomalies in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings can lead to performance degradation, energy inefficiencies, and occupant discomfort. Automated anomaly detection is essential to prevent these issues. Machine learning based anomaly detection techniques are effective …