Building Information and Energy Modeling for Greenhouses

Based on existing work [2], a start has been made to integrate Linked Data into the agricultural field. However, the focus of this field has been on agricultural performance (“how can we monitor crop growth?”). However, the energy use perspective is lacking from this approach. Building Information Modelling (BIM) is a well-established practice within the Construction, Architecture, and Engineering industry, and provides opportunities to analyse the energy use of buildings in the design and operation phase. This adoption of BIM in the agricultural industry, however, seems to be lacking. Moreover, considering the complex issue of energy use within agriculture, a more holistic technology is required. Therefore, the potential of Linked Data needs to be explored.

Semantic Web and Linked Data technologies provide the opportunity to gain insights into data which are currently stored in so called ‘data silos’. Bridging these silos is essential for the development of holistic tools which can answer complex questions regarding energy use and greenhouse performance. 

Objectives

1. Develop an ontology (based on existing ontologies like CGO [2], BOT [3], BOP [4], and NEO [5]) that gives insight into greenhouse energy use
2. Create a dataset from multiple domains relevant to the created ontology
3. Use the dataset and ontology to assess the energy-saving potential in a greenhouse setting 

Literature

1.  Conforti, P., Giampietro, M. (1997) Fossil energy use in agriculture: an international comparison. Agriculture, Ecosystems & Environment, Volume 65, Issue 3. https://doi.org/10.1016/S0167-8809(97)00048-0.
2. Bakker, R., Van Drie, R., Bouter, C., Van Leeuwen, S., Van Rooijen, L., & Top, J. (2021). The Common Greenhouse Ontology: An Ontology Describing Components, Properties, and Measurements inside the Greenhouse. Engineering Proceedings. https://doi.org/10.3390/engproc2021009027.
3. Rasmussen, M.H., Pauwels, P., Lefrancois, M., Schneider, G.F. (2021) Building Topology Ontology. https://w3c-lbd-cg.github.io/bot/
4. Donkers, A.J.A., Yang, D., De Vries, B., Baken, N. (2021). Building Performance Ontology. Revision: 1.6. https://w3id.org/bop
5. de Meij, S.R., Donkers, A.J.A., Yang, D., Klepper, M. (2023). Making Urban Energy Use More Intelligible Using Semantic Digital Twins. https://sanderdemeij.github.io/neo/

Requirements: 

• Courses: Linked Data (INF35806) or similar knowledge
• Required skills/knowledge: preferably skills or interest in linked data, greenhouse technology

Contact person(s)

Önder Babur (< email deleted for security reasons >)

Sander de Meij (< email deleted for security reasons >)