Artificial Intelligence in Landscape Architecture: A Survey
- URL: http://arxiv.org/abs/2408.14700v1
- Date: Mon, 26 Aug 2024 23:54:17 GMT
- Title: Artificial Intelligence in Landscape Architecture: A Survey
- Authors: Yue Xing, Wensheng Gan, Qidi Chen,
- Abstract summary: We introduce the many potential benefits that AI brings to the design, planning, and management aspects of landscape architecture (LA)
We discuss how AI can assist the LA field in solving its current development problems, including urbanization, environmental degradation and ecological decline, irrational planning, insufficient management and maintenance, and lack of public participation.
This article provides both theoretical and practical guidance for LA designers, researchers, and technology developers.
- Score: 8.138678558516052
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The development history of landscape architecture (LA) reflects the human pursuit of environmental beautification and ecological balance. With the advancement of artificial intelligence (AI) technologies that simulate and extend human intelligence, immense opportunities have been provided for LA, offering scientific and technological support throughout the entire workflow. In this article, we comprehensively review the applications of AI technology in the field of LA. First, we introduce the many potential benefits that AI brings to the design, planning, and management aspects of LA. Secondly, we discuss how AI can assist the LA field in solving its current development problems, including urbanization, environmental degradation and ecological decline, irrational planning, insufficient management and maintenance, and lack of public participation. Furthermore, we summarize the key technologies and practical cases of applying AI in the LA domain, from design assistance to intelligent management, all of which provide innovative solutions for the planning, design, and maintenance of LA. Finally, we look ahead to the problems and opportunities in LA, emphasizing the need to combine human expertise and judgment for rational decision-making. This article provides both theoretical and practical guidance for LA designers, researchers, and technology developers. The successful integration of AI technology into LA holds great promise for enhancing the field's capabilities and achieving more sustainable, efficient, and user-friendly outcomes.
Related papers
- Comprehensive Overview of Artificial Intelligence Applications in Modern Industries [0.3374875022248866]
This paper explores the applications of AI across four key sectors: healthcare, finance, manufacturing, and retail.
We discuss the implications of AI integration, including ethical considerations, the future trajectory of AI development, and its potential to drive economic growth.
arXiv Detail & Related papers (2024-09-19T19:22:52Z) - Artificial Intelligence and Human Geography [1.6135760596596367]
This paper examines the recent advances and applications of AI in human geography.
It includes the use of machine (deep) learning, including place representation and modeling, spatial analysis and predictive mapping, and urban planning and design.
arXiv Detail & Related papers (2023-12-14T11:20:22Z) - Artificial Intelligence in Sustainable Vertical Farming [0.0]
The paper provides a comprehensive exploration of the role of AI in sustainable vertical farming.
The review synthesizes the current state of AI applications, encompassing machine learning, computer vision, the Internet of Things (IoT), and robotics.
The implications extend beyond efficiency gains, considering economic viability, reduced environmental impact, and increased food security.
arXiv Detail & Related papers (2023-11-17T22:15:41Z) - On the Opportunities of Green Computing: A Survey [80.21955522431168]
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades.
The needs for high computing power brings higher carbon emission and undermines research fairness.
To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
arXiv Detail & Related papers (2023-11-01T11:16:41Z) - AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities
and Challenges [60.56413461109281]
Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big data generated by IT Operations processes.
We discuss in depth the key types of data emitted by IT Operations activities, the scale and challenges in analyzing them, and where they can be helpful.
We categorize the key AIOps tasks as - incident detection, failure prediction, root cause analysis and automated actions.
arXiv Detail & Related papers (2023-04-10T15:38:12Z) - Selected Trends in Artificial Intelligence for Space Applications [69.3474006357492]
This chapter focuses on differentiable intelligence and on-board machine learning.
We discuss a few selected projects originating from the European Space Agency's (ESA) Advanced Concepts Team (ACT)
arXiv Detail & Related papers (2022-12-10T07:49:50Z) - A Survey on AI Sustainability: Emerging Trends on Learning Algorithms
and Research Challenges [35.317637957059944]
We review major trends in machine learning approaches that can address the sustainability problem of AI.
We will highlight the major limitations of existing studies and propose potential research challenges and directions for the development of next generation of sustainable AI techniques.
arXiv Detail & Related papers (2022-05-08T09:38:35Z) - Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
It has become an important topic to explore the impact of AI on society from a people-centered perspective.
Previous works in citizen science have identified methods of using AI to engage the public in research.
This article discusses the challenges of applying AI in Community Citizen Science.
arXiv Detail & Related papers (2021-10-05T12:51:11Z) - Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society.
A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests.
This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
arXiv Detail & Related papers (2021-06-25T22:31:55Z) - Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations.
Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
arXiv Detail & Related papers (2021-01-15T10:43:10Z) - Developing Future Human-Centered Smart Cities: Critical Analysis of
Smart City Security, Interpretability, and Ethical Challenges [5.728709119947406]
Key challenges include security, robustness, interpretability, and ethical challenges to a successful deployment of AI or ML in human-centric applications.
Globally there are calls for technology to be made more humane and human-compatible.
arXiv Detail & Related papers (2020-12-14T18:54:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.