Affiliations: [a]
School of Architecture and Civil Engineering, Xiamen University, Xiamen, China
| [b]
School of Architecture and Urban planning, Fuzhou University, Fuzhou, China
Correspondence:
[*]
Corresponding author. Yajun Wang, School of Architecture and Urban planning, Fuzhou University, Fuzhou 350116, China. [email protected].
Abstract: The street design and landscape in China include cultural elements representing the Heritage and history of this generation. Such designs are planned, fabricated, and implemented based on previous elements and novel findings from the past. The novel findings are identified using sophisticated technologies like the Internet of Things (IoT). Therefore, this article introduces a Cultural Design Planning Method (CDPM) for Street Landscape (SL) in maintaining the renowned Heritage of Chinese roads. The proposed method relies on IoT-based data and cultural elements from the previous design and its impact on society. In this case, the impact is computed using attraction and cultural progression from the tourists and location. The cultural element’s connectivity and resemblance to the current location display the cultural progression. Such progression and impacts are recurrently validated using deep learning; the learning process identifies the elements and their associated impact on society. The previous and current street designs are augmented in the learning process to leverage placement and street design precision. The landscapes are periodically validated based on the current trends and associations.
Keywords: Chinese cultural elements, deep learning, IoT, street landscape
