The rapid advancement of drone technology and digital twin systems has significantly transformed environmental monitoring,particularly in the field of water quality assess-ment.This paper systematically reviews the cu...The rapid advancement of drone technology and digital twin systems has significantly transformed environmental monitoring,particularly in the field of water quality assess-ment.This paper systematically reviews the current state of research on the application of drones,digital twins,and their integration for water quality monitoring and management.It highlights key themes,insights,research trends,commonly used methodologies,and future directions from existing studies,aiming to provide a foundational reference for further research to harness the promising potential of these technologies for effective,scalable solutions in water resource management,addressing both immediate and long-term environmental challenges.The systematic review followed PRISMA guidelines,rigorously analysing hundreds of relevant papers.Key findings emphasise the effective-ness of drones in capturing real-time,high-resolution spatial and temporal data,as well as the value of digital twins for predictive and simulation-based analysis.Most importantly,the review demonstrates the potential of integrating these technologies to enhance sus-tainable water management practices.However,it also identifies a significant research gap in fully integrating drones with digital twins for comprehensive water quality manage-ment.In response,the review outlines future research directions,including improvements in data integration techniques,predictive models,and interdisciplinary collaboration.展开更多
Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable ...Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable robotic systems.Thus,personalization and rapid optimization of the effort are critical.Although respirometry is the gold standard for estimating metabolic costs,this method requires a heavy,bulky,and rigid system,limiting the system’s field deployability.Here,this paper reports a soft,flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton,used to estimate metabolic costs and physical effort,demonstrating the potential for real-time wearable robot adjustments based on biofeedback.Data from a set of activities,including walking,running,and squatting with the biopatch and exoskeleton,determines the relationship between metabolic costs and heart rate variability root mean square of successive differences(HRV-RMSSD)(R=−0.758).Collectively,the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.展开更多
基金National Science Foundation,Grant/Award Numbers:2152282,2302833University of Louisville。
文摘The rapid advancement of drone technology and digital twin systems has significantly transformed environmental monitoring,particularly in the field of water quality assess-ment.This paper systematically reviews the current state of research on the application of drones,digital twins,and their integration for water quality monitoring and management.It highlights key themes,insights,research trends,commonly used methodologies,and future directions from existing studies,aiming to provide a foundational reference for further research to harness the promising potential of these technologies for effective,scalable solutions in water resource management,addressing both immediate and long-term environmental challenges.The systematic review followed PRISMA guidelines,rigorously analysing hundreds of relevant papers.Key findings emphasise the effective-ness of drones in capturing real-time,high-resolution spatial and temporal data,as well as the value of digital twins for predictive and simulation-based analysis.Most importantly,the review demonstrates the potential of integrating these technologies to enhance sus-tainable water management practices.However,it also identifies a significant research gap in fully integrating drones with digital twins for comprehensive water quality manage-ment.In response,the review outlines future research directions,including improvements in data integration techniques,predictive models,and interdisciplinary collaboration.
基金the National Science Foundation/the Centers for Disease Control and Prevention(grant NRI‐2024742)supported by the IEN Center Grant from the Georgia Tech Institute for Electronics and Nanotechnologysupported by the National Science Foundation(grant ECCS-2025462).
文摘Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable robotic systems.Thus,personalization and rapid optimization of the effort are critical.Although respirometry is the gold standard for estimating metabolic costs,this method requires a heavy,bulky,and rigid system,limiting the system’s field deployability.Here,this paper reports a soft,flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton,used to estimate metabolic costs and physical effort,demonstrating the potential for real-time wearable robot adjustments based on biofeedback.Data from a set of activities,including walking,running,and squatting with the biopatch and exoskeleton,determines the relationship between metabolic costs and heart rate variability root mean square of successive differences(HRV-RMSSD)(R=−0.758).Collectively,the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.
