Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability:A comprehensive systematic review

The recent advancements made in the realms of Artificial Intelligence(AI)and Artificial Intelligence of Things(AIoT)have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart cities.These strides have,in turn,impacted smart eco-cities,catalyzing ongoing improvements and driving solutions to address complex environmental challenges.This aligns with the visionary concept of smarter eco-cities,an emerging paradigm of urbanism characterized by the seamless integration of advanced technologies and environmental strategies.However,there remains a significant gap in thoroughly understanding this new paradigm and the intricate spectrum of its multifaceted underlying dimensions.To bridge this gap,this study provides a comprehensive systematic review of the burgeoning landscape of smarter eco-cities and their leadingedge AI and AIoT solutions for environmental sustainability.To ensure thoroughness,the study employs a unified evidence synthesis framework integrating aggregative,configurative,and narrative synthesis approaches.At the core of this study lie these subsequent research inquiries:What are the foundational underpinnings of emerging smarter eco-cities,and how do they intricately interrelate,particularly urbanism paradigms,environmental solutions,and data-driven technologies?What are the key drivers and enablers propelling the materialization of smarter eco-cities?What are the primary AI and AIoT solutions that can be harnessed in the development of smarter eco-cities?In what ways do AI and AIoT technologies contribute to fostering environmental sustainability practices,and what potential benefits and opportunities do they offer for smarter eco-cities?What challenges and barriers arise in the implementation of AI and AIoT solutions for the development of smarter eco-cities?The findings significantly deepen and broaden our understanding of both the significant potential of AI and AIoT technologies to enhance sustainable urban development practices,as well as the formidable nature of the challenges they pose.Beyond theoretical enrichment,these findings offer invaluable insights and new perspectives poised to empower policymakers,practitioners,and researchers to advance the integration of eco-urbanism and AI-and AIoT-driven urbanism.Through an insightful exploration of the contemporary urban landscape and the identification of successfully applied AI and AIoT solutions,stakeholders gain the necessary groundwork for making well-informed decisions,implementing effective strategies,and designing policies that prioritize environmental well-being.

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

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative models.These advancements are reshaping data-driven planning strategies,practices,and approaches,thereby facilitating the achievement of environmental sustainability goals.This transformative wave signals a fundamental shift d marked by the synergistic operation of artificial intelligence(AI),artificial intelligence of things(AIoT),and urban digital twin(UDT)technologies.While previous research has largely explored urban AI,urban AIoT,and UDT in isolation,a significant knowledge gap exists regarding their synergistic interplay,collaborative integration,and collective impact on data-driven environmental planning in the dynamic context of sustainable smart cities.To address this gap,this study conducts a comprehensive systematic review to uncover the intricate interactions among these interconnected technologies,models,and domains while elucidating the nuanced dynamics and untapped synergies in the complex ecosystem of sustainable smart cities.Central to this study are four guiding research questions:1.What theoretical and practical foundations underpin the convergence of AI,AIoT,UDT,data-driven planning,and environmental sustainability in sustainable smart cities,and how can these components be synthesized into a novel comprehensive framework?2.How does integrating AI and AIoT reshape the landscape of datadriven planning to improve the environmental performance of sustainable smart cities?3.How can AI and AIoT augment the capabilities of UDT to enhance data-driven environmental planning processes in sustainable smart cities?4.What challenges and barriers arise in integrating and implementing AI,AIoT,and UDT in data-driven environmental urban planning,and what strategies can be devised to surmount or mitigate them?Methodologically,this study involves a rigorous analysis and synthesis of studies published between January 2019 and December 2023,comprising an extensive body of literature totaling 185 studies.The findings of this study surpass mere interdisciplinary theoretical enrichment,offering valuable insights into the transformative potential of integrating AI,AIoT,and UDT technologies to advance sustainable urban development practices.By enhancing data-driven environmental planning processes,these integrated technologies and models offer innovative solutions to address complex environmental challenges.However,this endeavor is fraught with formidable challenges and complexities that require careful navigation and mitigation to achieve desired outcomes.This study serves as a comprehensive reference guide,spurring groundbreaking research endeavors,stimulating practical implementations,informing strategic initiatives,and shaping policy formulations in sustainable urban development.These insights have profound implications for researchers,practitioners,and policymakers,providing a roadmap for fostering resiliently designed,technologically advanced,and environmentally conscious urban environments.