Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment m...Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment malfunctions,can cause dynamic changes in airport and sectorcapacity,resulting in significant alterations to optimized flight schedules and the calculated pre-departure slots.Therefore,taking into account capacity uncertainties is essential to create a moreresilient flight schedule.This paper addresses the flight pre-departure sequencing issue and intro-duces a capacity uncertainty model for optimizing flight schedule at the airport network level.The goal of the model is to reduce the total cost of flight delays while increasing the robustnessof the optimized schedule.A chance-constrained model is developed to address the capacity uncer-tainty of airports and sectors,and the significance of airports and sectors in the airport network isconsidered when setting the violation probability.The performance of the model is evaluated usingreal flight data by comparing them with the results of the deterministic model.The development ofthe model based on the characteristics of this special optimization mechanism can significantlyenhance its performance in addressing the pre-departure flight scheduling problem at the airportnetwork level.展开更多
Navigation system integrity monitoring is crucial for mission(e.g.safety)critical applications.Receiver autonomous integrity monitoring(RAIM)based on consistency checking of redundant measurements is widely used for m...Navigation system integrity monitoring is crucial for mission(e.g.safety)critical applications.Receiver autonomous integrity monitoring(RAIM)based on consistency checking of redundant measurements is widely used for many applications.However,there are many challenges to the use of RAIM associated with multiple constellations and applications with very stringent requirements.This paper discusses two positioning techniques and corresponding integrity monitoring methods.The first is the use of single frequency pseudorange-based dual constellations.It employs a new cross constellation single difference scheme to benefit from the similarities while addressing the differences between the constellations.The second technique uses dual frequency carrier phase measurements from GLONASS and the global positioning system for precise point positioning.The results show significant improvements both in positioning accuracy and integrity monitoring as a result of the use of two constellations.The dual constellation positioning and integrity monitoring algorithms have the potential to be extended to multiple constellations.展开更多
Mechanical, physical and manufacturing properties of east iron make it attractive for many fields of application, such as cranks and cylinder holds. As in design of all metals, fatigue life prediction is an intrinsic ...Mechanical, physical and manufacturing properties of east iron make it attractive for many fields of application, such as cranks and cylinder holds. As in design of all metals, fatigue life prediction is an intrinsic part of the design process of structural sections that are made of cast iron. A methodology to predict high-cycle fatigue life of cast iron is proposed. Stress amplitude-strain amplitude, strain amplitude-number of loading cycles relationships of cast iron are investigated. Also, fatigue life prediction in terms of Smith, Watson and Topper parameter is carried out using the proposed method. Results indicate that the analytical outcomes of the proposed methodology are in good accordance with the experimental data for the two studied types of cast iron： EN-GJS-400 and EN-GJS-600.展开更多
In safety-critical systems such as transportation aircraft, redundancy of actuators is introduced to improve fault tolerance. How to make the best use of remaining actuators to allow the system to continue achieving a...In safety-critical systems such as transportation aircraft, redundancy of actuators is introduced to improve fault tolerance. How to make the best use of remaining actuators to allow the system to continue achieving a desired operation in the presence of some actuators failures is the main subject of this paper. Considering that many dynamical systems, including flight dynamics of a transportation aircraft, can be expressed as an input affine nonlinear system, a new state repre- sentation is adopted here where the output dynamics are related with virtual inputs associated with the intended operation. This representation, as well as the distribution matrix associated with the effectiveness of the remaining operational actuators, allows us to define different levels of fault tol- erant governability with respect to actuators＇ failures. Then, a two-stage control approach is devel- oped, leading frst to the inversion of the output dynamics to get nominal values for the virtual inputs and then to the solution of a linear quadratic （LQ） problem to compute the solicitation of each operational actuator. The proposed approach is applied to the control of a transportation air- craft which performs a stabilized roll maneuver while a partial failure appears. Two fault scenarios are considered and the resulting performance of the proposed approach is displayed and discussed.展开更多
In Europe, computation of displacement demand for seismic assessment of existing buildings is essentially based on a simplified formulation of the N2 method as prescribed by Eurocode 8(EC8). However, a lack of accurac...In Europe, computation of displacement demand for seismic assessment of existing buildings is essentially based on a simplified formulation of the N2 method as prescribed by Eurocode 8(EC8). However, a lack of accuracy of the N2 method in certain conditions has been pointed out by several studies. This paper addresses the assessment of effectiveness of the N2 method in seismic displacement demand determination in non-linear domain. The objective of this work is to investigate the accuracy of the N2 method through comparison with displacement demands computed using non-linear timehistory analysis(NLTHA). Results show that the original N2 method may lead to overestimation or underestimation of displacement demand predictions. This may affect results of mechanical model-based assessment of seismic vulnerability at an urban scale. Hence, the second part of this paper addresses an improvement of the N2 method formula by empirical evaluation of NLTHA results based on EC8 ground-classes. This task is formulated as a mathematical programming problem in which coefficients are obtained by minimizing the overall discrepancy between NLTHA and modified formula results. Various settings of the mathematical programming problem have been solved using a global optimization metaheuristic. An extensive comparison between the original N2 method formulation and optimized formulae highlights benefits of the strategy.展开更多
Piezoelectric resonant de-icing systems are attracting great interest.This paper aims to assess the implementation of these systems at the aircraft level.The article begins with the model to compute the power requirem...Piezoelectric resonant de-icing systems are attracting great interest.This paper aims to assess the implementation of these systems at the aircraft level.The article begins with the model to compute the power requirement of a piezoelectric resonant de-icing system sized from the prototype detailed in Part 1/2 of this article.Then the mass,drag,and fuel consumption of this system and the subcomponents needed for its implementation are assessed.The features of a piezoelectric resonant de-icing system are finally computed for aircraft similar to Airbus A320 aircraft and aircraft of different categories(Boeing 787,ATR 72 and TBM 900)and compared with the existing thermal and mechanical ice protection systems.A sensitivity analysis of the main key sizing parameters of the piezoelectric de-icing system is also performed to identify the main axes of improvement for this technology.The study shows the potential of such ice protection systems.In particular,for the realistic input parameters chosen in this work,the electro-mechanical solution can provide a 54% reduction in terms of mass and a 92% reduction in terms of power consumption for an A320 aircraft architecture,leading to a 74% decrease in the associated fuel consumption compared to the actual air bleed system.展开更多
In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past ...In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past decades. Yet other types of buildings, in particular commercial centers, haven’t received the same level of interest. As a result, there is a need for effective and practical measures to decrease their energy consumption, both for heating and electricity. The objective of the paper is to demonstrate that it is possible, through coherent strategies, to integrate energy issues and bioclimatic principles into the design process of commercial centers. It analyzes the exemplary case study of Marin Commercial Center (Switzerland). The interdisciplinary approach, based on integrated design strategies, aimed at increasing the energy efficiency while keeping the cost comparable to the market cost. The main design principles include natural ventilation, nighttime cooling with energy recovery and natural lighting, as well as optimization of mechanical systems. The results of the simulations show that Marin Center attains the best energy performance observed so far among Swiss commercial centers. It also meets the Swiss Minergie standard. The paper thus questions traditional design processes and outlines the need for interdisciplinary evaluation and monitoring approaches tailored for commercial centers. Even though most crucial decisions are taken during the early stages, all phases of the process require systematic optimization strategies, especially operating stages. Recommendations include legal measures, in particular in the fields of ventilation and air-conditioning, education, professional development and technology transfer, and financial incentives for the replacement of energy intensive installations.展开更多
Soil organic carbon (SOC) losses due to poor soil management in dryland are now well documented. However, the influence of soil properties on organic carbon change is not well known. The groundnut plant (Arachis hypog...Soil organic carbon (SOC) losses due to poor soil management in dryland are now well documented. However, the influence of soil properties on organic carbon change is not well known. The groundnut plant (Arachis hypogaea L.), and the dominant crop system in the Senegal’s Soudanian zone, have been compared with semi-natural savanna. Leaves, stems and roots biomass were measured, and soil characteristics were analysed. The total leaves and stems biomass was 1.7 and 2.7 Mg ha-1 dry matter in groundnut fields and savanna respectively. Total SOC stocks were low (8 to 20 Mg C·ha-1 within upper 0.2 m depth, 20 to 64 Mg C·ha-1 within upper 1 m depth) and were significantly lower (P δ13C values show that SOC quality is transformed from the savanna plants (C4/C3 mixed-pools) to C3-pools in groundnut cultivated zone, with the organic matter signature more preserved in the clayey soils. This study confirms that converting woodland to groundnut fields provokes texture transformation and SOC loss. The results call for the extreme necessity to regenerate the wooded zone or encourage practices that favour SOC restitution.展开更多
Rapid urbanization,alongside escalating resource depletion and ecological degradation,underscores the critical need for innovative urban development solutions.In response,sustainable smart cities are increasingly turn...Rapid urbanization,alongside escalating resource depletion and ecological degradation,underscores the critical need for innovative urban development solutions.In response,sustainable smart cities are increasingly turning to cutting-edge technologiesdsuch as Generative Artificial Intelligence(GenAI),Foundation Models(FMs),and Urban Digital Twin(UDT)frameworksdto transform urban planning and design practices.These transformative tools provide advanced capabilities to analyze complex urban systems,optimize resource management,and enable evidence-based decision-making.Despite recent progress,research on integrating GenAI and FMs into UDT frameworks remains scant,leaving gaps in our ability to capture complex urban flows and multimodal dynamics essential to achieving environmental sustainability goals.Moreover,the lack of a robust theoretical foundation and real-world operationali-zation of these tools hampers comprehensive modeling and practical adoption.This study introduces a pioneering Large Flow Model(LFM),grounded in a robust foundational framework and designed with GenAI capabilities.It is specifically tailored for integration into UDT systems to enhance predictive an-alytics,adaptive learning,and complex data management functionalities.To validate its applicability and relevance,the Blue City Project in Lausanne City is examined as a case study,showcasing the ability of the LFM to effectively model and analyze urban flowsdnamely mobility,goods,energy,waste,materials,and biodiversitydcritical to advancing environmental sustainability.This study highlights how the LFM addresses the spatial challenges inherent in current UDT frameworks.The LFM demonstrates its novelty in comprehensive urban modeling and analysis by completing impartial city data,estimating flow data in new locations,predicting the evolution of flow data,and offering a holistic understanding of urban dynamics and their interconnections.The model enhances decision-making processes,supports evidence-based planning and design,fosters integrated development strategies,and enables the development of more efficient,resilient,and sustainable urban environments.This research advances both the theoretical and practical dimensions of AI-driven,environmentally sustainable urban devel-opment by operationalizing GenAI and FMs within UDT frameworks.It provides sophisticated tools and valuable insights for urban planners,designers,policymakers,and researchers to address the com-plexities of modern cities and accelerate the transition towards sustainable urban futures.展开更多
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 pe...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.展开更多
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-dr...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.展开更多
Eye tracking is growing in popularity for multiple application areas,yet analysing and exploring the large volume of complex data remains difficult for most users.We present a comprehensive eye tracking visual analyti...Eye tracking is growing in popularity for multiple application areas,yet analysing and exploring the large volume of complex data remains difficult for most users.We present a comprehensive eye tracking visual analytics system to enable the exploration and presentation of eye-tracking data across time and space in an efficient manner.The application allows the user to gain an overview of general patterns and perform deep visual analysis of local gaze exploration.The ability to link directly to the video of the underlying scene allows the visualisation insights to be verified on the fly.The system was motivated by the need to analyse eye-tracking data collected from an‘in the wild’study with energy network operators and has been further evaluated via interviews with 14 eye-tracking experts in multiple domains.Results suggest that,thanks to state-of-the-art visualisation techniques and by providing context with videos,our system could enable an improved analysis of eye-tracking data through interactive exploration,facilitating comparison between different participants or conditions,thus enhancing the presentation of complex data analysis to non-experts.This research paper provides four contributions:(1)analysis of a motivational use case demonstrating the need for rich visual-analytics workflow tools for eye-tracking data;(2)a highly dynamic system to visually explore and present complex eye-tracking data;(3)insights from our applied use case evaluation and interviews with experienced users demonstrating the potential for the system and visual analytics for the wider eye-tracking community.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U2033203,U1833126,61773203,61304190)。
文摘Air traffic flow management has been a major means for balancing air traffic demandand airport or airspace capacity to reduce congestion and flight delays.However,unpredictable fac-tors,such as weather and equipment malfunctions,can cause dynamic changes in airport and sectorcapacity,resulting in significant alterations to optimized flight schedules and the calculated pre-departure slots.Therefore,taking into account capacity uncertainties is essential to create a moreresilient flight schedule.This paper addresses the flight pre-departure sequencing issue and intro-duces a capacity uncertainty model for optimizing flight schedule at the airport network level.The goal of the model is to reduce the total cost of flight delays while increasing the robustnessof the optimized schedule.A chance-constrained model is developed to address the capacity uncer-tainty of airports and sectors,and the significance of airports and sectors in the airport network isconsidered when setting the violation probability.The performance of the model is evaluated usingreal flight data by comparing them with the results of the deterministic model.The development ofthe model based on the characteristics of this special optimization mechanism can significantlyenhance its performance in addressing the pre-departure flight scheduling problem at the airportnetwork level.
文摘Navigation system integrity monitoring is crucial for mission(e.g.safety)critical applications.Receiver autonomous integrity monitoring(RAIM)based on consistency checking of redundant measurements is widely used for many applications.However,there are many challenges to the use of RAIM associated with multiple constellations and applications with very stringent requirements.This paper discusses two positioning techniques and corresponding integrity monitoring methods.The first is the use of single frequency pseudorange-based dual constellations.It employs a new cross constellation single difference scheme to benefit from the similarities while addressing the differences between the constellations.The second technique uses dual frequency carrier phase measurements from GLONASS and the global positioning system for precise point positioning.The results show significant improvements both in positioning accuracy and integrity monitoring as a result of the use of two constellations.The dual constellation positioning and integrity monitoring algorithms have the potential to be extended to multiple constellations.
文摘Mechanical, physical and manufacturing properties of east iron make it attractive for many fields of application, such as cranks and cylinder holds. As in design of all metals, fatigue life prediction is an intrinsic part of the design process of structural sections that are made of cast iron. A methodology to predict high-cycle fatigue life of cast iron is proposed. Stress amplitude-strain amplitude, strain amplitude-number of loading cycles relationships of cast iron are investigated. Also, fatigue life prediction in terms of Smith, Watson and Topper parameter is carried out using the proposed method. Results indicate that the analytical outcomes of the proposed methodology are in good accordance with the experimental data for the two studied types of cast iron： EN-GJS-400 and EN-GJS-600.
文摘In safety-critical systems such as transportation aircraft, redundancy of actuators is introduced to improve fault tolerance. How to make the best use of remaining actuators to allow the system to continue achieving a desired operation in the presence of some actuators failures is the main subject of this paper. Considering that many dynamical systems, including flight dynamics of a transportation aircraft, can be expressed as an input affine nonlinear system, a new state repre- sentation is adopted here where the output dynamics are related with virtual inputs associated with the intended operation. This representation, as well as the distribution matrix associated with the effectiveness of the remaining operational actuators, allows us to define different levels of fault tol- erant governability with respect to actuators＇ failures. Then, a two-stage control approach is devel- oped, leading frst to the inversion of the output dynamics to get nominal values for the virtual inputs and then to the solution of a linear quadratic （LQ） problem to compute the solicitation of each operational actuator. The proposed approach is applied to the control of a transportation air- craft which performs a stabilized roll maneuver while a partial failure appears. Two fault scenarios are considered and the resulting performance of the proposed approach is displayed and discussed.
文摘In Europe, computation of displacement demand for seismic assessment of existing buildings is essentially based on a simplified formulation of the N2 method as prescribed by Eurocode 8(EC8). However, a lack of accuracy of the N2 method in certain conditions has been pointed out by several studies. This paper addresses the assessment of effectiveness of the N2 method in seismic displacement demand determination in non-linear domain. The objective of this work is to investigate the accuracy of the N2 method through comparison with displacement demands computed using non-linear timehistory analysis(NLTHA). Results show that the original N2 method may lead to overestimation or underestimation of displacement demand predictions. This may affect results of mechanical model-based assessment of seismic vulnerability at an urban scale. Hence, the second part of this paper addresses an improvement of the N2 method formula by empirical evaluation of NLTHA results based on EC8 ground-classes. This task is formulated as a mathematical programming problem in which coefficients are obtained by minimizing the overall discrepancy between NLTHA and modified formula results. Various settings of the mathematical programming problem have been solved using a global optimization metaheuristic. An extensive comparison between the original N2 method formulation and optimized formulae highlights benefits of the strategy.
文摘Piezoelectric resonant de-icing systems are attracting great interest.This paper aims to assess the implementation of these systems at the aircraft level.The article begins with the model to compute the power requirement of a piezoelectric resonant de-icing system sized from the prototype detailed in Part 1/2 of this article.Then the mass,drag,and fuel consumption of this system and the subcomponents needed for its implementation are assessed.The features of a piezoelectric resonant de-icing system are finally computed for aircraft similar to Airbus A320 aircraft and aircraft of different categories(Boeing 787,ATR 72 and TBM 900)and compared with the existing thermal and mechanical ice protection systems.A sensitivity analysis of the main key sizing parameters of the piezoelectric de-icing system is also performed to identify the main axes of improvement for this technology.The study shows the potential of such ice protection systems.In particular,for the realistic input parameters chosen in this work,the electro-mechanical solution can provide a 54% reduction in terms of mass and a 92% reduction in terms of power consumption for an A320 aircraft architecture,leading to a 74% decrease in the associated fuel consumption compared to the actual air bleed system.
文摘In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past decades. Yet other types of buildings, in particular commercial centers, haven’t received the same level of interest. As a result, there is a need for effective and practical measures to decrease their energy consumption, both for heating and electricity. The objective of the paper is to demonstrate that it is possible, through coherent strategies, to integrate energy issues and bioclimatic principles into the design process of commercial centers. It analyzes the exemplary case study of Marin Commercial Center (Switzerland). The interdisciplinary approach, based on integrated design strategies, aimed at increasing the energy efficiency while keeping the cost comparable to the market cost. The main design principles include natural ventilation, nighttime cooling with energy recovery and natural lighting, as well as optimization of mechanical systems. The results of the simulations show that Marin Center attains the best energy performance observed so far among Swiss commercial centers. It also meets the Swiss Minergie standard. The paper thus questions traditional design processes and outlines the need for interdisciplinary evaluation and monitoring approaches tailored for commercial centers. Even though most crucial decisions are taken during the early stages, all phases of the process require systematic optimization strategies, especially operating stages. Recommendations include legal measures, in particular in the fields of ventilation and air-conditioning, education, professional development and technology transfer, and financial incentives for the replacement of energy intensive installations.
文摘Soil organic carbon (SOC) losses due to poor soil management in dryland are now well documented. However, the influence of soil properties on organic carbon change is not well known. The groundnut plant (Arachis hypogaea L.), and the dominant crop system in the Senegal’s Soudanian zone, have been compared with semi-natural savanna. Leaves, stems and roots biomass were measured, and soil characteristics were analysed. The total leaves and stems biomass was 1.7 and 2.7 Mg ha-1 dry matter in groundnut fields and savanna respectively. Total SOC stocks were low (8 to 20 Mg C·ha-1 within upper 0.2 m depth, 20 to 64 Mg C·ha-1 within upper 1 m depth) and were significantly lower (P δ13C values show that SOC quality is transformed from the savanna plants (C4/C3 mixed-pools) to C3-pools in groundnut cultivated zone, with the organic matter signature more preserved in the clayey soils. This study confirms that converting woodland to groundnut fields provokes texture transformation and SOC loss. The results call for the extreme necessity to regenerate the wooded zone or encourage practices that favour SOC restitution.
基金support provided by Innosuisse for the Blue City Flagship Project(Flagship ID#PFFS-21-03).
文摘Rapid urbanization,alongside escalating resource depletion and ecological degradation,underscores the critical need for innovative urban development solutions.In response,sustainable smart cities are increasingly turning to cutting-edge technologiesdsuch as Generative Artificial Intelligence(GenAI),Foundation Models(FMs),and Urban Digital Twin(UDT)frameworksdto transform urban planning and design practices.These transformative tools provide advanced capabilities to analyze complex urban systems,optimize resource management,and enable evidence-based decision-making.Despite recent progress,research on integrating GenAI and FMs into UDT frameworks remains scant,leaving gaps in our ability to capture complex urban flows and multimodal dynamics essential to achieving environmental sustainability goals.Moreover,the lack of a robust theoretical foundation and real-world operationali-zation of these tools hampers comprehensive modeling and practical adoption.This study introduces a pioneering Large Flow Model(LFM),grounded in a robust foundational framework and designed with GenAI capabilities.It is specifically tailored for integration into UDT systems to enhance predictive an-alytics,adaptive learning,and complex data management functionalities.To validate its applicability and relevance,the Blue City Project in Lausanne City is examined as a case study,showcasing the ability of the LFM to effectively model and analyze urban flowsdnamely mobility,goods,energy,waste,materials,and biodiversitydcritical to advancing environmental sustainability.This study highlights how the LFM addresses the spatial challenges inherent in current UDT frameworks.The LFM demonstrates its novelty in comprehensive urban modeling and analysis by completing impartial city data,estimating flow data in new locations,predicting the evolution of flow data,and offering a holistic understanding of urban dynamics and their interconnections.The model enhances decision-making processes,supports evidence-based planning and design,fosters integrated development strategies,and enables the development of more efficient,resilient,and sustainable urban environments.This research advances both the theoretical and practical dimensions of AI-driven,environmentally sustainable urban devel-opment by operationalizing GenAI and FMs within UDT frameworks.It provides sophisticated tools and valuable insights for urban planners,designers,policymakers,and researchers to address the com-plexities of modern cities and accelerate the transition towards sustainable urban futures.
基金funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No.101034260.
文摘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.
文摘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.
基金The observational study that motivated the initial develop-ment of VETA was funded by the Australian Energy Market Opera-tor(AEMO).We would like to thank all AEMO participants and all eye tracking experts who participated in the evaluation.We also acknowledge the use of Monash Business Behavioural Laboratory equipment in this project.
文摘Eye tracking is growing in popularity for multiple application areas,yet analysing and exploring the large volume of complex data remains difficult for most users.We present a comprehensive eye tracking visual analytics system to enable the exploration and presentation of eye-tracking data across time and space in an efficient manner.The application allows the user to gain an overview of general patterns and perform deep visual analysis of local gaze exploration.The ability to link directly to the video of the underlying scene allows the visualisation insights to be verified on the fly.The system was motivated by the need to analyse eye-tracking data collected from an‘in the wild’study with energy network operators and has been further evaluated via interviews with 14 eye-tracking experts in multiple domains.Results suggest that,thanks to state-of-the-art visualisation techniques and by providing context with videos,our system could enable an improved analysis of eye-tracking data through interactive exploration,facilitating comparison between different participants or conditions,thus enhancing the presentation of complex data analysis to non-experts.This research paper provides four contributions:(1)analysis of a motivational use case demonstrating the need for rich visual-analytics workflow tools for eye-tracking data;(2)a highly dynamic system to visually explore and present complex eye-tracking data;(3)insights from our applied use case evaluation and interviews with experienced users demonstrating the potential for the system and visual analytics for the wider eye-tracking community.
