Modernity and Tradition in the Context of Erbil Old Town

PurposeThis paper aims to shed light on adaptive reuse in traditional architecture (TA) in Erbil, Iraq.Design/methodology/approachAn inductive approach and qualitative method were used in this study. The inductive research approach was used because there was no clear image of adaptive reuse in traditional cafés (TCs) in Erbil. Besides, there are no studies of TCs in Erbil particularly. Thus, there is a lack of knowledge about what adaptations took place in TCs in Erbil. The qualitative method extracted themes and issues from case studies of four TCs in Erbil citadel's buffer zone. This included a physical survey and observation of the TCs in Erbil and 18 semi-structured interviews with the owners, servers and visitors.FindingsThe analysis shows the flexibility of the TCs in Erbil as a face of adaptive re-use (AR) which is explained through the capacity linked to space modifications, the addition of modern devices, the function linked to space modifications, service addition, the condition linked to space modifications and the addition of modern devices. Also, TCs in Erbil has a spatial identity and architectural value that proves it is worthy enough to be preserved through unique spirituality linked to preserving the place.Research limitations/implicationsThe findings are limited to the cases of TCs in mountain regain and may not be applicable or appropriate to other cafés in other different countries.Originality/valueThere are three aspects of authenticity in the current research. Firstly, the TCs in Erbil have not been studied before. Secondly, TCs that have been discovered have made AR of themselves whilst maintaining their original function-serving beverages, to stimulate creativity. Thirdly, most of the studies of AR have dealt with historical and heritage architecture, whilst the current research paper is dealing with TA.

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“…From Abbas (2020), Akram et al . (2019), Al-Jaff et al . (2017) and Al-Khulaifi (2003) a lot of TA functions were highlighted including:…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Adaptation re-use of traditional cafés in Erbil, Iraq

Agha

Hussein

2023

IJBPA

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“…Historic districts serve as a testament to urban development, embodying a wealth of cultural heritage and historical memory [13,14]. The preservation and monitoring of these districts are not only expressions of respect for historical culture but also critical components of sustainable urban development [15,16].…”

Section: Development Of Historical District Protectionmentioning

confidence: 99%

Artificial Intelligence for Routine Heritage Monitoring and Sustainable Planning of the Conservation of Historic Districts: A Case Study on Fujian Earthen Houses (Tulou)

Fan,

Chen,

Zheng

2024

Buildings

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With its advancements in relation to computer science, artificial intelligence has great potential for protecting and researching the world heritage Fujian earthen houses (Tulou) historical district. Wood is an important material used in the construction of Fujian earthen houses (Tulou); wood is used in both the main structure of the buildings and for decoration. However, professionals must invest significant time and energy in evaluating any damage before repairing a building. In this context, this study proposes and optimizes a detection method based on the YOLOv8 model for detecting damage to the wooden structure of Fujian earthen houses. Through multiple experiments and adjustments, we gradually improved the detection performance of the model and verified its effectiveness and reliability in practical applications. The main results of this study are as follows: (1) This machine-learning-based object detection method can efficiently and accurately identify damaged contents, overcoming the limitations of traditional evaluation methods in terms of labor and time costs. This approach will aid in the daily protection monitoring of historical districts and serves as a preliminary method for their renewal and restoration. (2) Through multiple rounds of experiments, we optimized the YOLOv8 model and significantly improved its detection accuracy and stability by removing samples with complex backgrounds, improving label quality, and adjusting hyperparameters. In the final experiment, the model’s overall mAP was only 57.00% at most. However, during the field test, the model successfully identified nearly all damage points, including holes, stains, and cracks in the wooden structure of the analyzed earthen building, effectively fulfilling the requirements of the detection task. (3) In the KuiJu Lou field test in Fujian Tulou, the model also performed well in complex environments and was able to reliably detect damage types such as holes, stains, and cracks in the wooden structure. This test confirmed the model’s efficiency and stability in practical applications and provided reliable technical support for Fujian Tulou protection and restoration.

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