Artificial intelligence for sustainable development of smart cities and urban land-use management

Masoumi, Zohreh; Genderen, J.L. van

doi:10.1080/10095020.2023.2184729

Cited by 9 publications

(4 citation statements)

References 55 publications

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“…[ 7 ] for a bibliometric analysis). They particularly highlight the crucial contributions of AI and AIoT in enhancing operational efficiency mechanisms and strategic planning methods [ 8 , 19 , 21 , 22 , 24 , 27 , 104 , 105 ]. In light of this, the conventional approaches to urban planning, which have long grappled with the dynamic properties and behaviors of complex systems [ [78] , [79] , [80] , [81] ], have served as a fertile ground and significant opportunity for the integration of AI and AIoT to deepen our understanding of the complexities inherent in urban environments.…”

Section: Results: Analysis and Synthesismentioning

confidence: 99%

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Bibri,

Huang,

Jagatheesaperumal

et al. 2024

Environmental Science and Ecotechnology

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Section: Results: Analysis and Synthesismentioning

confidence: 99%

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Bibri,

Huang,

Jagatheesaperumal

et al. 2024

Environmental Science and Ecotechnology

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“…Cooperate health requires clear health management from companies for employees' physical and mental health maintenance. Feeling good increases productivity and sufficient creativity relaxation and is targeted at implementation, leading to a competitive advantage over other companies ( 39 , 40 ).…”

Section: Challenges and Developments In The Forestrymentioning

confidence: 99%

Impact of forestry on environment and human health: an evidence-based investigation

Addas

2023

Front. Public Health

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There is an increasing interest in the health effects of the forest. Without active participation in forestry, conflicts between the various stakeholders are foreseeable. The impact of forests on human life is unforgettable, and everyone gets enormous benefits from trees and greenery. COVID-19 has caused many changes in human behavior, which needs much attention. Environmental change's impact is considered a better solution and influences human behavior. Scientists around the globe are conducting research experiments on trees and the effect of forestry on human health, which is increasing in terms of social, ecological, and economic services. Trees provide full support to enhance the quality of life and minimize air pollution. Forests must be noticed to get benefits (e.g., carbon storage, fruits, human health considerations, economic benefits, and biodiversity). This research aims to explain the area of forest and health from the perspective of Saudi Arabian forestry and develop strategic measures for the proactive design of this topic. The research entailed expert interviews with forestry representatives and a quantitative survey of medical students. Our findings show that implementing strategic measures, such as establishing a forest and health, improves health and eliminates air pollution. It shows many other establishment and planning strategies, such as the use of professional visitor monitoring, the development of product innovations, the use of digitalization, and the development of integrated forest management.

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“…A study by ref. [49] assessed the performance of a nondominated sorting genetic algorithm II (NSGA-II), PSO, and a multi-objective evolutionary algorithm (EA/D) based on solution dispersion, the diversity of the solution space, and the number of dominant solutions in Pareto-front parameters. Reportedly, PSO exhibited the best diversity of solutions, while the EA/D outperformed the other two in terms of computational time.…”

Section: Value and Frontiersmentioning

confidence: 99%

“…The authors declare no conflict of interest. Application of SA to high dimensional non-linear multi-objective multisite land allocation [39] Improved knowledge-informed GA for multi-objective land use allocation BLI-Heuristic algorithms [29] Modified NSGA-II BLI-Sustainable development [108] Probabilistic-based gradient multi-objective land use optimization BLI-Gradient methods in optimization [50] Validity and accuracy comparison b/n various algorithms in land use allocation (including SA) CRC-What SA it is and its application [49] Application of particle swarm optimization for multi-objective urban land use optimization BLI-Heuristic algorithm [104] Application of an improved artificial immune system for multi-objective land use allocation BLI-Heuristic algorithms [109] Application of hybrid heuristic algorithms to multi-objective land use suitability assessment of the quadratic assignment problem BLI-Heuristic algorithms [110] Multi-objective optimization model to consider transportation, formulated as mixed-integer programing BLI-Integer programing [80] Improved artificial bee colony algorithm to solve spatial problems BLI-Heuristic algorithms [97] Application of GA and game theory to solve land allocation problems BLI-Heuristic algorithms [36] Simulating optimal multi-objective land use Applying multi-agent system and particle swarm [111] Urban growth boundary determination based on a multi-objective land use optimization applying a Pareto-front degradation searching strategy where lands were defined as agents CRC-Application of agent in land use optimization [112] Collaborative optimal allocation of urban land to determine the growth boundary of urban agglomeration BLI-The difficulty of transforming optimal land use structures into spatial layout [113] An agent-based optimization of water allocation (market) wherein farmers were represented as an agricultural agent CRC-Application of agent in land use optimization [114] Linking agent-based modeling with the territorial life cycle assessment in land use planning BLI-Complexity of spatial and temporal dynamics of territorial transformation [115] Optimizing deep underground infrastructure layouts based on a multi-agent system where each DUI is represented by an agent CRC-The SE of multi-agent systems [116] Land use simulation (optimization) using CLUMondo mode BLI-Complexity of quantifying conflicting interests; Use of fractal dimension; Sensitivity of complex landscape patch boundary to human disturbance [117] Use of gray multi-objective optimization and Patch generating land use simulation in land use optimization (hybrid methods) BLI-The relationship of land use structure optimization and sustainable development…”

Section: Conflicts Of Interestmentioning

confidence: 99%

A Land Use Planning Literature Review: Literature Path, Planning Contexts, Optimization Methods, and Bibliometric Methods

Mehari,

Genovese

2023

Land

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Land use planning studies are accumulating in unprecedented quantities, and have created a wide space for an extensive summary, the synthesis of fundamental developments, a sharpening of the focus of future study issues, and the dissemination of concise information among the academic community and the policy making environment. Nonetheless, the publication rate and content coverage of land use planning literature reviews have been relatively low. This study aims to contribute to the field by first assessing the effectiveness of the bibliometric method as a literature study method. It then summarizes the developments in the land use planning literature in general path building process, the planning context, and the development of methods. The study findings highlight that the bibliometric method tends to reward information carriage papers rather than original contributors. More than 85% of the time, published articles are cited for general information rather than their core research contribution, suggesting the incomprehensiveness of the bibliometric method in studying real knowledge development. In terms of the land use planning context, significant gaps are observed, particularly in urban land use, including the detachment of the general goal-oriented objective formulations from basic land use allocation theories and conceptual models. A serious concern also arises that the formulations of certain urban land use optimization objectives appear to contradict the original concept of a sustainable city. To address these gaps, this paper suggests several key research frontiers, including linking the basic land use allocation and utility theories to land use optimization, and a need to shift current urban land use planning/optimization approaches from spatial optimization, which changes land uses to meet flow resources, towards optimizing the flow of resources to fit the resilient nature of existing spatial configurations and physical establishments in the built environment. Additionally, evaluating the existing built environment for optimality should be prioritized rather than solely focusing on new developments. In terms of method development, the study suggests that advancing current loosely coupled methods into more integrated systems may be a promising frontier. In general, the paper strongly suggests the possible reiteration of the land use planning study landscape to make sustainable development discourse more concrete and to make the method development stage involve more integrated systems. Immediate research interventions may be the standardizing of land use planning studies through the development of protocols and standard benchmark problems.

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Artificial intelligence for sustainable development of smart cities and urban land-use management

Cited by 9 publications

References 55 publications

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Impact of forestry on environment and human health: an evidence-based investigation

A Land Use Planning Literature Review: Literature Path, Planning Contexts, Optimization Methods, and Bibliometric Methods

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