Att möta utmaningarna med återbruk : AI för en mer resurseffektiv byggindustri

The construction industry is facing major challenges related to climate impact and resource consumption. One approach to addressing these challenges is to increase the reuse of building materials. At the same time, artificial intelligence (AI) is emerging as a technology with the potential to support more efficient and sustainable construction processes. This thesis explores how AI can be used to overcome the current obstacles limiting reuse in the construction sector. The study is based on the significant amount of construction waste and the many practical, technical, and structural challenges that hinder reuse. These include a lack of traceability, standardisation, quality assurance, coordination between stakeholders, and effective logistics. AI has the potential to support these processes through automation, material flow analysis, and decision support tools. The aim of the study is to gain a deeper understanding of these challenges and to investigate how existing AI solutions can be applied in practice to support reuse. A qualitative method was used, combining a literature review with semi-structured interviews involving professionals from both reuse and AI sectors. The findings show that AI can play an important role in facilitating reuse, but its implementation is still at an early stage. Realising its full potential requires increased knowledge, shared practices, and technical adaptations.

Publication Details

Journal
Hogskolan Ihalmstad (Halmstad University)
Published
2025-01-01
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
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article

Att möta utmaningarna med återbruk : AI för en mer resurseffektiv byggindustri

Hogskolan Ihalmstad (Halmstad University)
Recycled Aggregate Concrete Performance
article

Att möta utmaningarna med återbruk : AI för en mer resurseffektiv byggindustri

article en

Abstract

The construction industry is facing major challenges related to climate impact and resource consumption. One approach to addressing these challenges is to increase the reuse of building materials. At the same time, artificial intelligence (AI) is emerging as a technology with the potential to support more efficient and sustainable construction processes. This thesis explores how AI can be used to overcome the current obstacles limiting reuse in the construction sector. The study is based on the significant amount of construction waste and the many practical, technical, and structural challenges that hinder reuse. These include a lack of traceability, standardisation, quality assurance, coordination between stakeholders, and effective logistics. AI has the potential to support these processes through automation, material flow analysis, and decision support tools. The aim of the study is to gain a deeper understanding of these challenges and to investigate how existing AI solutions can be applied in practice to support reuse. A qualitative method was used, combining a literature review with semi-structured interviews involving professionals from both reuse and AI sectors. The findings show that AI can play an important role in facilitating reuse, but its implementation is still at an early stage. Realising its full potential requires increased knowledge, shared practices, and technical adaptations.

Hogskolan Ihalmstad (Halmstad University)
Openalex Percentile: Top 50%
Recycled Aggregate Concrete Performance
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Att möta utmaningarna med återbruk : AI för en mer resurseffektiv byggindustri · Hogskolan Ihalmstad (Halmstad University) (2025) | TGRS Research Map | TGRS