On-site robotic and automated techniques for building renovation and new construction

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: Improved resource efficiency compared to current practices; Improved accuracy (designed vs. as-built) of on-site renovation and construction works, compared to current best practices; Significant reduction in time spent by building professionals on site; Reduced GHG emissions at the construction site. Scope: The rate of deep renovation of buildings can be accelerated by modernising the construction sector and embracing the latest developments in robotics and automated systems. There is need for further development of techniques using innovative on-site robotic and other automated systems that make renovation and construction works more sustainable, less disruptive, faster as well as more accurate, cost effective and resource efficient, while delivering, at least, the same building elem… more

1. %47
   ERHAN KARAKOÇ

   Doktor Öğretim ÜyesiAnkara Medipol Üniversitesi

   Shared topics: Building Energy and Comfort Optimization · BIM and Construction Integration

2. %46
   MERVE ERTOSUN YILDIZ

   Doktor Öğretim ÜyesiSakarya Üniversitesi

   Shared topics: Building Energy and Comfort Optimization · Sustainable Building Design and Assessment · Construction Project Management and Performance

3. %44
   DUYGU TEKİN

   Doktor Öğretim ÜyesiBayburt Üniversitesi

   Shared topics: Building Energy and Comfort Optimization · BIM and Construction Integration

4. %43
   SELCEN NUR ERİKCİ ÇELİK

   Doktor Öğretim ÜyesiBeykoz Üniversitesi

   Shared topics: Building Energy and Comfort Optimization · BIM and Construction Integration

5. %40
   SUNA YILDIRIM

   Doktor Öğretim ÜyesiMalatya Turgut Özal Üniversitesi

   Shared topics: Building Energy and Comfort Optimization

6. %40
   SÜMEYYE SENA BASTEM

   Araştırma GörevlisiVan Yüzüncü Yıl Üniversitesi

   Shared topics: Building Energy and Comfort Optimization · BIM and Construction Integration

The fit is computed by code on every request: semantic similarity (55%) between the call text (title, EU keywords, start of the official description) and the academic’s YÖKSİS fields, keywords and OpenAlex topics, plus shared distinctive terms (45%; common words weigh little). Below 40% is not shown. A subject hint only — not an eligibility, capacity or merit assessment. Hidden profiles are never listed.