B4B is a multi-year, multi-stakeholder project focused on developing methods to harness big data from smart meters, building management systems and the Internet of Things devices, to reduce energy consumption, increase comfort, respond flexibly to user behaviour and local energy supply and demand, and save on installation maintenance costs. This will be done through the development of faster and more efficient Machine Learning and Artificial Intelligence models and algorithms. The project is geared to existing utility buildings such as commercial and institutional buildings.
The main question in this PhD thesis is: How can Business Rules Management be configured and valued in organizations? A BRM problem space framework is proposed, existing of service systems, as a solution to the BRM problems. In total 94 vendor documents and approximately 32 hours of semi-structured interviews were analyzed. This analysis revealed nine individual service systems, in casu elicitation, design, verification, validation, deployment, execution, monitor, audit, and version. In the second part of this dissertation, BRM is positioned in relation to BPM (Business Process Management) by means of a literature study. An extension study was conducted: a qualitative study on a list of business rules formulated by a consulting organization based on the Committee of Sponsoring Organizations of the Treadway Commission risk framework. (from the summary of the Thesis p. 165)
For the integrated implementation of Business Process Management and supporting information systems many methods are available. Most of these methods, however, apply a one-size fits all approach and do not take into account the specific situation of the organization in which an information system is to be implemented. These situational factors, however, strongly determine the success of any implementation project. In this paper a method is provided that establishes situational factors of and their influence on implementation methods. The provided method enables a more successful implementation project, because the project team can create a more suitable implementation method for business process management system implementation projects.
Polycotton textiles are fabrics made from cotton and polyester. It is used in many textile applications such as sporting cloths, nursery uniforms and bed sheets. As cotton and polyester are quite different in their polymer nature, polycotton textiles are hard to recycle and therefore mostly incinerated. Incineration of discarded polycotton, and substitution by virgin polycotton, create a significant environmental impact. However, textile manufacturers and brand owners will become obliged to apply recycled content in clothing from 2023 onwards. Therefore, the development of more sustainable recycling alternatives for the separation and purification of polycotton into its monomers and cellulose is vital. In a recently approved GoChem project, it has been shown that cotton can be separated from polyester successfully, using a chemical recycling process. The generated solution is a mixture of suspended and partially decolorized cotton (cellulose) and a liquid fraction produced from the depolymerization of the polyester (monomers). A necessary further step of this work is the investigation of possible separation methods to recover the cotton and purify the obtained polyester monomers into polymer-grade pure products suitable for repolymerization. Repolymerize is a new consortium, composed of the first project members, plus a separation and purification process group, to investigate efficient and high yield purification steps to recover these products. The project will focus on possible steps to separate the suspended fraction (cotton) and further recover of high purity ethylene glycol from the rest fraction (polyester depolymerization solution). The main objective is to create essential knowledge so the private partners can evaluate whether such process is technologically and economically feasible.
Making buildings smarter will save energy and make energy systems more flexible to address grid congestion. This is done by adding smart functionalities (such as machine learning and AI) to existing building management systems and by making full use of building data. Applied research and innovation on smart buildings is urgently needed to evaluate the best smart solutions for buildings applicable to different types of buildings across different contexts, and to assess their costs and benefits. Research on smart buildings, therefore, plays a large role in European, national and regional R&I agenda’s on energy, climate and digitalisation. Amsterdam University of Amsterdam (AUAS) has a growing research group on building energy management and smart buildings, supporting the sustainable transition of its own campus and the Amsterdam region. However, to date, AUAS has not been able to engage in international research projects in this area. Recently, AUAS became a partner in an European University Alliance (U!REKA European University), U!REKA comprises of six universities of applied sciences across Europe with its mission focusing on climate neutral communities and cities. Several partners with U!REKA are also conducting research on smart buildings and smart campuses, but, like AUAS, still in relative isolation. U!REKA will provide the collaboration framework for future joint research to be kick-started by the proposed SIA pilot project. In this research project, AUAS will cooperate with the Technical University Eindhoven, Metropolia University of Applied Sciences (Helsinki) and Politecnico de Lisboa (Lisbon) as consortium partners. Supporting partners are Frankfurt University of Applied Sciences, KTH Royal Institute of Technology (Stockholm) and TVVL (Dutch knowledge platform and association of professionals in the installation sector). The research is based on smart building case studies on the campuses of the project partners.
The Sustainable Rivers Management (SRM) research group (HAN/VHL Universities of Applied Sciences) and the Smart Rivers Foundation (SRF) have identified an added value for collaboration in order to educate the professionals of the future. There they want to set up a joint research programme to link capacity building efforts amongst professionals with higher applied education. This project will boost the strategic partnership between the SRM group at HAN/VHL, SRF and its strategic partners. Smart River Foundation and Bureau Drift have identified the DNA or intrinsic nature of various river systems in the Netherlands (NL) using 20 years of expert knowledge. This approach is now increasingly being adopted by practitioners and policy makers in NL. The DNA of a river can only be determined after having analysed all the landscape factors involved and the interactions herein. These factors or layers are multidisciplinary and relate to the water system, abiotic and biotic variables and anthropogenic impact. However, a clear methodology for identifying the DNA of a river system is lacking. This project aims to develop this methodology and to test it internationally. A method for identifying the DNA of a river will support technical managers of Water Framework Directive (WFD) and Hoogwaterbeschermingsprogramma (Flood Protection Program, HWBP) projects in the Netherlands to realise spatial quality in their projects. Moreover, the Smart Rivers approach also becomes applicable to other river systems around the world. This will provide a sound basis for supporting existing and new international partnerships.
