Hae Young Noh
Associate Professor of Civil and Environmental Engineering
Bio
Hae Young Noh is an associate professor in the Department of Civil and Environmental Engineering. Her research introduced the new concept of “structures as sensors” to enable physical structures (e.g., buildings and vehicle frames) to be user- and environment-aware. In particular, these structures indirectly sense humans and surrounding environments through their structural responses (i.e., vibrations) by inferring the desired information (e.g., human behaviors, environmental conditions, heating and cooling system performance), instead of directly measuring the sensing targets with additional dedicated sensors (e.g., cameras, motion sensors). This concept brought a paradigm shift in how we view these structures and how the structures interact with us.
Traditionally, structures that we inhabit (such as buildings or vehicles) are considered as passive and unchanging objects that we need to monitor and control, utilizing a dense set of sensors to collect information. This has often been complicated by “noise” caused by the occupants and environments. For example, building vibrations induced by indoor and outdoor environmental and operational conditions (e.g., people walking around, traffic outside, heating system running, etc.), have been often seen as noise that needs to be removed in traditional building science and structural engineering; however, they are a rich source of information about structure, users, environment, and resources. Similarly, in vehicle engineering, researchers and engineers have been investigating control and dynamics to reduce vehicle vibration for safety and comfort. However, vibrations measured inside vehicles contain information about transportation infrastructure, vehicle itself, and driver.
Noh's work utilizes this “noise” to empower the structures with the ability to perceive and understand the information about users and surroundings using their own responses, and actively adopt and/or interact to enhance their sustainability and the occupants’ quality of life. Since she utilizes the structure itself as a sensing medium, information collection involves a simpler set of hardware that can be easily maintained throughout the structural lifetime. However, the analysis of data to separate the desired information becomes more challenging. This challenge is addressed through high-rate dynamic sensing and multi-source inferencing. Ultimately, her work aims to allow structural systems to become general sensing platforms that are easier and more practical to deploy and maintain in a long-term.
At Stanford University, Noh received her PhD and MS degrees in the CEE department and her second MS degree in Electrical Engineering. Noh earned her BS in Mechanical and Aerospace Engineering at Cornell University.
Honors & Awards
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Best Paper Award, ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI) (2020)
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Best Student Paper Award, ASCE Engineering Mechanics Institute Dynamics Committee (ASCE EMI) (2020)
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Best Student Paper Award, ASCE Engineering Mechanics Institute Dynamics Committee (ASCE EMI) (2019)
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Best Demo Award, ACM Systems for Energy-Efficient Buildings, Cities, and Transportation (ACM BuildSys) (2019)
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Best Poster Award, IEEE/ACM Information Processing and Sensor Network (IPSN) (2019)
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Best Paper Award, IEEE International Conference on Machine Learning and Applications (ICMLA) (2018)
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Best Student Paper Award, ASCE Engineering Mechanics Institute Dynamics Committee (ASCE EMI) (2018)
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CIT Dean’s Early Career Fellow, Carnegie Mellon University (2018)
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NSF CAREER Award, National Science Foundation (NSF) (2017)
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Google Faculty Research Award, Google (2017)
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People’s Choice Paper Award, ACM Systems for Energy-Efficient Built Environments (ACM BuildSys) (2017)
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Best Poster Award & Best Poster Runner-Up, ACM Embedded Networked Sensor Systems (ACM SenSys) (2016)
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MobiSys 2016 Junior Faculty/Postdoc Grants, ACM Mobile Systems, Applications, and Services (ACM MobiSys) (2016)
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Best Poster Award, IEEE/ACM Information Processing and Sensor Network (IPSN) (2015)
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Google Faculty Research Award, Google (2014)
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Berkman Faculty Development Fund, Carnegie Mellon University (2013-2015)
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John A. Blume Fellowship, - (2010-2011)
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Samsung Scholarship Foundation Merit-Based Scholarship, Samsung Scholarship Foundation (2006-2010)
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American Society of Civil Engineers Essay Contest Award, American Society of Civil Engineers (2010)
Professional Education
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PhD, Stanford University, Civil and Environmental Engineering (2011)
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MS, Stanford University, Electrical Engineering (2011)
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MS, Stanford University, Civil and Environmental Engineering (2008)
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BS, Cornell University, Mechanical and Aerospace Engineering (2005)
2024-25 Courses
- Data Analytics for Physical Systems
CEE 154, CEE 254 (Aut) - Structural Monitoring
CEE 286 (Win) -
Independent Studies (8)
- Advanced Engineering Problems
CEE 399 (Aut, Win, Spr) - Directed Reading or Special Studies in Civil Engineering
CEE 198 (Aut, Win, Spr) - Independent Project in Civil and Environmental Engineering
CEE 199L (Aut, Win, Spr) - Independent Project in Civil and Environmental Engineering
CEE 299L (Aut, Win, Spr) - Independent Study in Civil Engineering for CEE-MS Students
CEE 299 (Aut, Win, Spr) - Report on Civil Engineering Training
CEE 398 (Aut, Win, Spr) - Undergraduate Honors Thesis
CEE 199H (Aut, Win, Spr) - Undergraduate Research in Civil and Environmental Engineering
CEE 199 (Aut, Win, Spr)
- Advanced Engineering Problems
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Prior Year Courses
2023-24 Courses
- Data Analytics for Physical Systems
CEE 154, CEE 254 (Aut)
2022-23 Courses
- Data Analytics for Physical Systems
CEE 154, CEE 254 (Aut) - Intro to Solid Mechanics
ENGR 14 (Spr) - Structural Monitoring
CEE 286 (Win)
2021-22 Courses
- Data Analytics for Physical Systems
CEE 154, CEE 254 (Aut) - Structural Monitoring
CEE 286 (Win)
- Data Analytics for Physical Systems
Stanford Advisees
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Doctoral Dissertation Advisor (AC)
Jatin Aggarwal, Yuyan Wu -
Master's Program Advisor
Andrés Arias Vásquez, Shu Chen, Helong Huang, Xinyi Li, Seoyoung Oh, Liana Wong, Hongyu Wu, Isabel Yamashita, Olivia Yamashita -
Doctoral (Program)
Jatin Aggarwal, Doyun Hwang, Yuyan Wu
All Publications
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iLOCuS: Incentivizing Vehicle Mobility to Optimize Sensing Distribution in Crowd Sensing
IEEE TRANSACTIONS ON MOBILE COMPUTING
2020; 19 (8): 1831–47
View details for DOI 10.1109/TMC.2019.2915838
View details for Web of Science ID 000545425200007
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Step-Level Occupant Detection across Different Structures through Footstep-Induced Floor Vibration Using Model Transfer
JOURNAL OF ENGINEERING MECHANICS
2020; 146 (3)
View details for DOI 10.1061/(ASCE)EM.1943-7889.0001719
View details for Web of Science ID 000507898900007
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Diagnosis algorithms for indirect structural health monitoring of a bridge model via dimensionality reduction
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2020; 136
View details for DOI 10.1016/j.ymssp.2019.106454
View details for Web of Science ID 000529083600015
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Occupant localization using footstep-induced structural vibration
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2018; 112: 77–97
View details for DOI 10.1016/j.ymssp.2018.04.026
View details for Web of Science ID 000438180800007
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Characterizing human activity induced impulse and slip-pulse excitations through structural vibration
JOURNAL OF SOUND AND VIBRATION
2018; 414: 61–80
View details for DOI 10.1016/j.jsv.2017.10.034
View details for Web of Science ID 000417643200005
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Track monitoring from the dynamic response of a passing train: A sparse approach
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2017; 90: 141–53
View details for DOI 10.1016/j.ymssp.2016.12.009
View details for Web of Science ID 000393633700010
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Physics-Informed Machine Learning for Inverse Design of Optical Metamaterials
ADVANCED PHOTONICS RESEARCH
2023
View details for DOI 10.1002/adpr.202300158
View details for Web of Science ID 001078969300001
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Characterizing the variability of footstep-induced structural vibrations for open-world person identification
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2023; 204
View details for DOI 10.1016/j.ymssp.2023.110756
View details for Web of Science ID 001076113900001
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TelecomTM: A Fine-Grained and Ubiquitous Traffic Monitoring System Using Pre-Existing Telecommunication Fiber-Optic Cables as Sensors
PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT
2023; 7 (2)
View details for DOI 10.1145/3596262
View details for Web of Science ID 001005382400019
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IDIoT: Multimodal Framework for Ubiquitous Identification and Assignment of Human-carriedWearable Devices
ACM TRANSACTIONS ON INTERNET OF THINGS
2023; 4 (2)
View details for DOI 10.1145/3579832
View details for Web of Science ID 000999148400003
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Turning Telecommunication Fiber-Optic Cables into Distributed Acoustic Sensors for Vibration-Based Bridge Health Monitoring
STRUCTURAL CONTROL & HEALTH MONITORING
2023; 2023
View details for DOI 10.1155/2023/3902306
View details for Web of Science ID 000975166800001
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A hierarchical semantic segmentation framework for computer vision-based bridge damage detection
SMART STRUCTURES AND SYSTEMS
2023; 31 (4): 325-334
View details for DOI 10.12989/sss.2023.31.4.325
View details for Web of Science ID 000994013500003
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Stranger Detection and Occupant Identification Using Structural Vibrations
SPRINGER-VERLAG SINGAPORE PTE LTD. 2023: 905-914
View details for DOI 10.1007/978-3-031-07254-3_91
View details for Web of Science ID 000871789600089
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The field of human building interaction for convergent research and innovation for intelligent built environments.
Scientific reports
2022; 12 (1): 22092
Abstract
Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.
View details for DOI 10.1038/s41598-022-25047-y
View details for PubMedID 36543830
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Seismic multi-hazard and impact estimation via causal inference from satellite imagery.
Nature communications
2022; 13 (1): 7793
Abstract
Rapid post-earthquake reconnaissance is important for emergency responses and rehabilitation by providing accurate and timely information about secondary hazards and impacts, including landslide, liquefaction, and building damage. Despite the extensive collection of geospatial data and satellite images, existing physics-based and data-driven methods suffer from low estimation performance due to the complex and event-specific causal dependencies underlying the cascading processes of earthquake-triggered hazards and impacts. Herein, we present a rapid seismic multi-hazard and impact estimation system that leverages advanced statistical causal inference and remote sensing techniques. The unique feature of this system is that it provides accurate and high-resolution estimations on a regional scale by jointly inferring multiple hazards and building damage from satellite images through modeling their causal dependencies. We evaluate our system on multiple seismic events from diverse countries around the globe. Our results corroborate that incorporating causal dependencies significantly improves large-scale estimation accuracy for multiple hazards and impacts compared to existing systems. The results also reveal quantitative causal mechanisms among earthquake-triggered multi-hazard and impact for multiple seismic events. Our system establishes a new way to extract and utilize the complex interactions of multiple hazards and impacts for effective disaster responses and advancing understanding of seismic geological processes.
View details for DOI 10.1038/s41467-022-35418-8
View details for PubMedID 36526641
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Ten questions concerning human-building interaction research for improving the quality of life
BUILDING AND ENVIRONMENT
2022; 226
View details for DOI 10.1016/j.buildenv.2022.109681
View details for Web of Science ID 000878660700002
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HierMUD: Hierarchical multi-task unsupervised domain adaptation between bridges for drive-by damage diagnosis
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
2022
View details for DOI 10.1177/14759217221081159
View details for Web of Science ID 000840350900001
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Adaptive Hybrid Model-Enabled Sensing System (HMSS) for Mobile Fine-Grained Air Pollution Estimation
IEEE TRANSACTIONS ON MOBILE COMPUTING
2022; 21 (6): 1927-1944
View details for DOI 10.1109/TMC.2020.3034270
View details for Web of Science ID 000791765200002
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Recursive Sparse Representation for Identifying Multiple Concurrent Occupants Using Floor Vibration Sensing
PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT
2022; 6 (1)
View details for DOI 10.1145/3517229
View details for Web of Science ID 000904877500010
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Predicting peak stresses in microstructured materials using convolutional encoder-decoder learning
MATHEMATICS AND MECHANICS OF SOLIDS
2022
View details for DOI 10.1177/10812865211055504
View details for Web of Science ID 000739405600001
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Poster Abstract: SeatBeats Heart Rate Monitoring System using Structural Seat Vibrations
IEEE COMPUTER SOC. 2022: 511-512
View details for DOI 10.1109/IPSN54338.2022.00056
View details for Web of Science ID 000855254100048
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Re-Vibe: Vibration-based Indoor Person Re-Identification through Cross-Structure Optimal Transport
ASSOC COMPUTING MACHINERY. 2022: 348-352
View details for DOI 10.1145/3563357.3566134
View details for Web of Science ID 001066191100058
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Poster Abstract: Integration of Physics-Based Building Model and Sensor Data to Develop an Adaptive Digital Twin
ASSOC COMPUTING MACHINERY. 2022: 282-283
View details for DOI 10.1145/3563357.3567745
View details for Web of Science ID 001066191100037
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A Neural-Based Bandit Approach to Mobile Crowdsourcing
ASSOC COMPUTING MACHINERY. 2022: 15-21
View details for DOI 10.1145/3508396.3512886
View details for Web of Science ID 000927583300003
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Editorial: Understanding Human-Infrastructure Interactions: Context-Aware Structures and Interfaces
FRONTIERS IN BUILT ENVIRONMENT
2021; 7
View details for DOI 10.3389/fbuil.2021.698620
View details for Web of Science ID 000661429000001
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Obstruction-invariant occupant localization using footstep-induced structural vibrations
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2021; 153
View details for DOI 10.1016/j.ymssp.2020.107499
View details for Web of Science ID 000651824100008
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PhyMDAN: Physics-informed knowledge transfer between buildings for seismic damage diagnosis through adversarial learning
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2021; 151
View details for DOI 10.1016/j.ymssp.2020.107374
View details for Web of Science ID 000640530600014
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Structure- and Sampling-Adaptive Gait Balance Symmetry Estimation Using Footstep-Induced Structural Floor Vibrations
JOURNAL OF ENGINEERING MECHANICS
2021; 147 (2)
View details for DOI 10.1061/(ASCE)EM.1943-7889.0001889
View details for Web of Science ID 000608028000007
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PIWIMS: Physics Informed Warehouse Inventory Monitory via Synthetic Data Generation
ASSOC COMPUTING MACHINERY. 2021: 613-618
View details for DOI 10.1145/3460418.3480415
View details for Web of Science ID 000723951900139
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MassHog: Weight-Sensitive Occupant Monitoring for Pig Pens using Actuated Structural Vibrations
ASSOC COMPUTING MACHINERY. 2021: 600-605
View details for DOI 10.1145/3460418.3480414
View details for Web of Science ID 000723951900137
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An efficient Bayesian framework for updating PAGER loss estimates
EARTHQUAKE SPECTRA
2020; 36 (4): 1719–42
View details for DOI 10.1177/8755293020944177
View details for Web of Science ID 000591902000005
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FAIM: Vision and Weight Sensing Fusion Framework for Autonomous Inventory Monitoring in Convenience Stores
FRONTIERS IN BUILT ENVIRONMENT
2020; 6
View details for DOI 10.3389/fbuil.2020.568372
View details for Web of Science ID 000585434200001
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Fine-Grained Activity of Daily Living (ADL) Recognition Through Heterogeneous Sensing Systems With Complementary Spatiotemporal Characteristics
FRONTIERS IN BUILT ENVIRONMENT
2020; 6
View details for DOI 10.3389/fbuil.2020.560497
View details for Web of Science ID 000583354900001
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PAS: Prediction-Based Actuation System for City-Scale Ridesharing Vehicular Mobile Crowdsensing
IEEE INTERNET OF THINGS JOURNAL
2020; 7 (5): 3719–34
View details for DOI 10.1109/JIOT.2020.2968375
View details for Web of Science ID 000536066300005
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O-MedAL: Online active deep learning for medical image analysis
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
2020; 10 (4)
View details for DOI 10.1002/widm.1353
View details for Web of Science ID 000509415300001
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OAC: Overlapping Office Activity Classification through IoT-Sensed Structural Vibration
IEEE COMPUTER SOC. 2020: 216–22
View details for DOI 10.1109/IoTDI49375.2020.00028
View details for Web of Science ID 000583907800020
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Structural Property Guided Gait Parameter Estimation Using Footstep-Induced Floor Vibrations
SPRINGER INTERNATIONAL PUBLISHING AG. 2020: 191–94
View details for DOI 10.1007/978-3-030-12115-0_25
View details for Web of Science ID 000620329200025
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Enhancing the Data Learning With Physical Knowledge in Fine-Grained Air Pollution Inference
IEEE ACCESS
2020; 8: 88372–84
View details for DOI 10.1109/ACCESS.2020.2993610
View details for Web of Science ID 000538766800003
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Demo Abstract: Active Structural Occupant Detector
IEEE. 2020: 353–54
View details for DOI 10.1109/IPSN48710.2020.00-10
View details for Web of Science ID 000609813400042
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Poster Abstract: Using Deep Learning to Classify The Acceleration Measurement Devices
IEEE. 2020: 351–52
View details for DOI 10.1109/IPSN48710.2020.00-11
View details for Web of Science ID 000609813400041
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DAMAGE-SENSITIVE AND DOMAIN-INVARIANT FEATURE EXTRACTION FOR VEHICLE-VIBRATION-BASED BRIDGE HEALTH MONITORING
IEEE. 2020: 3007–11
View details for Web of Science ID 000615970403051
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IDIoT: Towards Ubiquitous Identification of IoT Devices through Visual and Inertial Orientation Matching During Human Activity
IEEE COMPUTER SOC. 2020: 40–52
View details for DOI 10.1109/IoTDI49375.2020.00012
View details for Web of Science ID 000583907800004
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Structures as Sensors: Indirect Sensing for Inferring Users and Environments
COMPUTER
2019; 52 (10): 84–88
View details for DOI 10.1109/MC.2019.2925651
View details for Web of Science ID 000489755200013
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Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh
SCIENTIFIC DATA
2019; 6: 146
Abstract
We present DR-Train, the first long-term open-access dataset recording dynamic responses from in-service light rail vehicles. Specifically, the dataset contains measurements from multiple sensor channels mounted on two in-service light rail vehicles that run on a 42.2-km light rail network in the city of Pittsburgh, Pennsylvania. This dataset provides dynamic responses of in-service trains via vibration data collected by accelerometers, which enables a low-cost way of monitoring rail tracks more frequently. Such an approach will result in more reliable and economical ways to monitor rail infrastructure. The dataset also includes corresponding GPS positions of the trains, environmental conditions (including temperature, wind, weather, and precipitation), and track maintenance logs. The data, which is stored in a MAT-file format, can be conveniently loaded for various potential uses, such as validating anomaly detection and data fusion as well as investigating environmental influences on train responses.
View details for DOI 10.1038/s41597-019-0148-9
View details for Web of Science ID 000481667300002
View details for PubMedID 31406119
View details for PubMedCentralID PMC6690915
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Empirical investigation of regression models for predicting system behavior in air handling units
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT
2019; 25 (3): 247–60
View details for DOI 10.1080/23744731.2018.1523660
View details for Web of Science ID 000461671700001
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A graphical approach to assess the detectability of multiple simultaneous faults in air handling units
ENERGY AND BUILDINGS
2019; 184: 275–88
View details for DOI 10.1016/j.enbuild.2018.12.008
View details for Web of Science ID 000457505700023
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Characterizing Structural Changes to Estimate Walking Gait Balance
SPRINGER INTERNATIONAL PUBLISHING AG. 2019: 333–35
View details for DOI 10.1007/978-3-319-74421-6_44
View details for Web of Science ID 000558187900044
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Detecting Anomalies in Longitudinal Elevation of Track Geometry Using Train Dynamic Responses via a Variational Autoencoder
SPIE-INT SOC OPTICAL ENGINEERING. 2019
View details for DOI 10.1117/12.2513711
View details for Web of Science ID 000483016400039
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A Damage Localization and Quantification Algorithm for Indirect Structural Health Monitoring of Bridges Using Multi-Task Learning
AMER INST PHYSICS. 2019
View details for DOI 10.1063/1.5099821
View details for Web of Science ID 000479309100117
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Area Occupancy Counting Through Sparse Structural Vibration Sensing
IEEE PERVASIVE COMPUTING
2019; 18 (1): 28–37
View details for DOI 10.1109/MPRV.2018.2873574
View details for Web of Science ID 000467076100005
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Gait Health Monitoring Through Footstep-Induced Floor Vibrations
ASSOC COMPUTING MACHINERY. 2019: 319–20
View details for DOI 10.1145/3302506.3312608
View details for Web of Science ID 000474338900035
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Vehicle Dispatching for Sensing Coverage Optimization in Mobile Crowdsensing Systems
ASSOC COMPUTING MACHINERY. 2019: 311–12
View details for DOI 10.1145/3302506.3312604
View details for Web of Science ID 000474338900031
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Secure Pairing via Video and IMU Verification
ASSOC COMPUTING MACHINERY. 2019: 333–34
View details for DOI 10.1145/3302506.3312492
View details for Web of Science ID 000474338900042
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Deskbuddy: an Office Activity Detection System
ASSOC COMPUTING MACHINERY. 2019: 352–53
View details for DOI 10.1145/3302506.3312490
View details for Web of Science ID 000474338900051
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Incentivizing Large-scale Vehicular Crowdsensing System For Smart City Applications
SPIE-INT SOC OPTICAL ENGINEERING. 2019
View details for DOI 10.1117/12.2514021
View details for Web of Science ID 000483016400040
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A Deep Autoencoder Model for Pollution Map Recovery with Mobile Sensing Networks
ASSOC COMPUTING MACHINERY. 2019: 577–83
View details for DOI 10.1145/3341162.3349327
View details for Web of Science ID 000501543800136
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Device-free Multiple People Localization through Floor Vibration
ASSOC COMPUTING MACHINERY. 2019: 57–61
View details for DOI 10.1145/3360773.3360887
View details for Web of Science ID 000525871200014
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Device-free Sleep Stage Recognition through Bed Frame Vibration Sensing
ASSOC COMPUTING MACHINERY. 2019: 39–43
View details for DOI 10.1145/3360773.3360883
View details for Web of Science ID 000525871200010
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A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition
ASSOC COMPUTING MACHINERY. 2019: 29–33
View details for DOI 10.1145/3359427.3361918
View details for Web of Science ID 000533258400008
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WhereWear: Calibration-free Wearable Device Identification through Ambient Sensing
ASSOC COMPUTING MACHINERY. 2019: 29–34
View details for DOI 10.1145/3325424.3329667
View details for Web of Science ID 000557845800007
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P-Loc: A Device-free Indoor Localization System Utilizing Building Power-line Network
ASSOC COMPUTING MACHINERY. 2019: 611–15
View details for DOI 10.1145/3341162.3349328
View details for Web of Science ID 000558324800141
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Demo Abstract: Autonomous Inventory Monitoring through Multi-Modal Sensing (AIM3S) for Cashier-Less Stores
ASSOC COMPUTING MACHINERY. 2019: 395–96
View details for DOI 10.1145/3360322.3361018
View details for Web of Science ID 000557872600071
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Fine-Grained Recognition of Activities of Daily Living through Structural Vibration and Electrical Sensing
ASSOC COMPUTING MACHINERY. 2019: 149–58
View details for DOI 10.1145/3360322.3360851
View details for Web of Science ID 000557872600017
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AIM3S: Autonomous Inventory Monitoring through Multi-Modal Sensing for Cashier-Less Convenience Stores
ASSOC COMPUTING MACHINERY. 2019: 135–44
View details for DOI 10.1145/3360322.3360834
View details for Web of Science ID 000557872600015
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Smart Home Occupant Identification via Sensor Fusion Across On-Object Devices
ACM TRANSACTIONS ON SENSOR NETWORKS
2018; 14 (3-4)
View details for DOI 10.1145/3218584
View details for Web of Science ID 000457137600008
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Conductive Thread-Based Textile Sensor for Continuous Perspiration Level Monitoring
SENSORS
2018; 18 (11)
Abstract
Individual perspiration level indicates a person's physical status as well as their comfort level. Therefore, continuous perspiration level measurement enables people to monitor these conditions for applications including fitness assessment, athlete physical status monitoring, and patient/elderly care. Prior work on perspiration (sweat) sensing required the user either to be static or to wear the adhesive sensor directly on the skin, which limits users' mobility and comfort. In this paper, we present a novel conductive thread-based textile sensor that measures an individual's on-cloth sweat quantity. The sensor consists of three conductive threads. Each conductive thread is surrounded by a braided cotton cover. An additional braided cotton cover is placed outside the three conductive threads, holding them in a position that is stable for measurement. the sensor can be embedded at various locations on a person's clothing. When the person sweats, the cotton braids absorb the sweat and change the conductivity (resistance) between conductive threads. We used a voltage dividing circuit to measure this resistance as the sensor output (DC). We then conducted a sensor calibration to map this measured voltage to the quantity of electrolyte solution (with the same density as sweat) applied to the sensor. We used this sensor to measure individuals' perspiration quantity and infer their perceived perspiration levels. The system is able to limit the average prediction error to 0.4 levels when compared to five pre-defined perceived perspiration levels.
View details for DOI 10.3390/s18113775
View details for Web of Science ID 000451598900185
View details for PubMedID 30400608
View details for PubMedCentralID PMC6263898
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Robust Building Energy Load Forecasting Using Physically-Based Kernel Models
ENERGIES
2018; 11 (4)
View details for DOI 10.3390/en11040862
View details for Web of Science ID 000434703400173
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MyoVibe: Enabling Inertial Sensor-Based Muscle Activation Detection In High-Mobility Exercise Environments
ACM TRANSACTIONS ON SENSOR NETWORKS
2018; 14 (1)
View details for DOI 10.1145/3149127
View details for Web of Science ID 000433515800006
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Occupant-Induced Office Floor Vibration Dataset for Activity Level Monitoring
ASSOC COMPUTING MACHINERY. 2018: 5–6
View details for DOI 10.1145/3277868.3277871
View details for Web of Science ID 000510907400003
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Do You Peel What I Hear? Enabling Autonomous IoT Device Pairing using Different Sensor Types
IEEE. 2018: 836–52
View details for DOI 10.1109/SP.2018.00041
View details for Web of Science ID 000442163200050
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Demo Abstract: PosePair: Pairing loT Devices Through Visual Human Pose Analysis
IEEE. 2018: 144–45
View details for DOI 10.1109/IPSN.2018.00035
View details for Web of Science ID 000449016500027
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VVRRM: Vehicular Vibration-based Heart RR-Interval Monitoring System
ASSOC COMPUTING MACHINERY. 2018: 37–42
View details for DOI 10.1145/3177102.3177110
View details for Web of Science ID 000455265400007
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UniverSense: IoT Device Pairing through Heterogeneous Sensing Signals
ASSOC COMPUTING MACHINERY. 2018: 55–60
View details for DOI 10.1145/3177102.3177108
View details for Web of Science ID 000455265400010
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MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis
IEEE. 2018: 481–88
View details for DOI 10.1109/ICMLA.2018.00078
View details for Web of Science ID 000463034400070
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Guiding the Data Learning Process with Physical Model in Air Pollution Inference
IEEE. 2018: 4475–83
View details for Web of Science ID 000468499304076
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Human Gait Monitoring Using Footstep-Induced Floor Vibrations Across Different Structures
ASSOC COMPUTING MACHINERY. 2018: 1382–91
View details for DOI 10.1145/3267305.3274187
View details for Web of Science ID 000461550100261
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Occupant Activity Level Estimation Using Floor Vibration
ASSOC COMPUTING MACHINERY. 2018: 1355–63
View details for DOI 10.1145/3267305.3274184
View details for Web of Science ID 000461550100258
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Moisture Based Perspiration Level Estimation
ASSOC COMPUTING MACHINERY. 2018: 1301–8
View details for DOI 10.1145/3267305.3274177
View details for Web of Science ID 000461550100252
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PGA: Physics Guided and Adaptive Approach for Mobile Fine-Grained Air Pollution Estimation
ASSOC COMPUTING MACHINERY. 2018: 1321–30
View details for DOI 10.1145/3267305.3274179
View details for Web of Science ID 000461550100254
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Poster Abstract: Generative Model Based Fine-Grained Air Pollution Inference for Mobile Sensing Systems
ASSOC COMPUTING MACHINERY. 2018: 426–27
View details for DOI 10.1145/3274783.3275216
View details for Web of Science ID 000469016400084
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Demo Abstract: Vibration-Based Occupant Activity Level Monitoring System
ASSOC COMPUTING MACHINERY. 2018: 349–50
View details for DOI 10.1145/3274783.3275177
View details for Web of Science ID 000469016400046
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Poster Abstract: Robust Detection of Motor-Produced Audio Signals
ASSOC COMPUTING MACHINERY. 2018: 412–13
View details for DOI 10.1145/3274783.3275209
View details for Web of Science ID 000469016400077
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Structural Vibration Sensing to Evaluate Animal Activity on a Pig Farm
ASSOC COMPUTING MACHINERY. 2018: 25–26
View details for DOI 10.1145/3277868.3277881
View details for Web of Science ID 000510907400013
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Seat Vibration for Heart Monitoring in a Moving Automobile
ASSOC COMPUTING MACHINERY. 2018: 7–8
View details for DOI 10.1145/3277868.3277872
View details for Web of Science ID 000510907400004
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A data fusion approach for track monitoring from multiple in-service trains
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2017; 95: 363–79
View details for DOI 10.1016/j.ymssp.2017.03.023
View details for Web of Science ID 000401595500022
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Bayesian Updating of Earthquake Vulnerability Functions with Application to Mortality Rates
EARTHQUAKE SPECTRA
2017; 33 (3): 1173–89
View details for DOI 10.1193/081216EQS133M
View details for Web of Science ID 000410693200018
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Updating Structural Parameters with Spatially Incomplete Measurements Using Subspace System Identification
JOURNAL OF ENGINEERING MECHANICS
2017; 143 (7)
View details for DOI 10.1061/(ASCE)EM.1943-7889.0001226
View details for Web of Science ID 000399896200004
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Track-monitoring from the dynamic response of an operational train
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2017; 87: 1–16
View details for DOI 10.1016/j.ymssp.2016.06.041
View details for Web of Science ID 000390086600001
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Delay Effect in Mobile Sensing System for Urban Air Pollution Monitoring
ASSOC COMPUTING MACHINERY. 2017
View details for DOI 10.1145/3131672.3136997
View details for Web of Science ID 000462783500073
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SurfaceVibe: Vibration-Based Tap & Swipe Tracking on Ubiquitous Surfaces
IEEE. 2017: 197–208
View details for DOI 10.1145/3055031.3055077
View details for Web of Science ID 000426984900016
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Characterizing Left-Right Gait Balance Using Footstep-Induced Structural Vibrations
SPIE-INT SOC OPTICAL ENGINEERING. 2017
View details for DOI 10.1117/12.2260376
View details for Web of Science ID 000410169000038
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Poster Abstract: Interdependent Component Framework for Simulating Indoor Internet-of-Things Systems (Intercom)
IEEE. 2017: 315–16
View details for DOI 10.1145/3055031.3055066
View details for Web of Science ID 000426984900051
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Calibration-Free Footstep Frequency Estimation Using Structural Vibration
SPRINGER INTERNATIONAL PUBLISHING AG. 2017: 287–89
View details for DOI 10.1007/978-3-319-54777-0_35
View details for Web of Science ID 000432208200035
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An energy-based sparse representation of ultrasonic guided-waves for online damage detection of pipelines under varying environmental and operational conditions
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
2017; 82: 260–78
View details for DOI 10.1016/j.ymssp.2016.05.022
View details for Web of Science ID 000384397500017
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Individualized Calibration of Industrial-Grade Gas Sensors in Air Quality Sensing System
ASSOC COMPUTING MACHINERY. 2017
View details for DOI 10.1145/3131672.3136998
View details for Web of Science ID 000462783500074
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SenseTribute: Smart Home Occupant Identification via Fusion Across On-Object Sensing Devices
ASSOC COMPUTING MACHINERY. 2017
View details for DOI 10.1145/3137133.3137152
View details for Web of Science ID 000463798000002
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Automated synchronization of driving data using vibration and steering events
PATTERN RECOGNITION LETTERS
2016; 75: 9–15
View details for DOI 10.1016/j.patrec.2016.02.011
View details for Web of Science ID 000374479300002
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Sparse representation of ultrasonic guided-waves for robust damage detection in pipelines under varying environmental and operational conditions
STRUCTURAL CONTROL & HEALTH MONITORING
2016; 23 (2): 369–91
View details for DOI 10.1002/stc.1776
View details for Web of Science ID 000368033700012
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Burnout: A Wearable System for Unobtrusive Skeletal Muscle Fatigue Estimation
IEEE. 2016
View details for Web of Science ID 000381741700002
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Occupant Traffic Estimation through Structural Vibration Sensing
SPIE-INT SOC OPTICAL ENGINEERING. 2016
View details for DOI 10.1117/12.2222024
View details for Web of Science ID 000382319400005
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Characterizing Wave Propagation to Improve Indoor Step-Level Person Localization using Floor Vibration
SPIE-INT SOC OPTICAL ENGINEERING. 2016
View details for DOI 10.1117/12.2222136
View details for Web of Science ID 000382319400004
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Robust Occupant Detection Through Step-Induced Floor Vibration by Incorporating Structural Characteristics
SPRINGER. 2016: 357–67
View details for DOI 10.1007/978-3-319-29763-7_35
View details for Web of Science ID 000381725500035
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Development of empirical and analytical fragility functions using kernel smoothing methods
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
2015; 44 (8): 1163-1180
View details for DOI 10.1002/eqe.2505
View details for Web of Science ID 000354730500001
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STIM: Smart Train Infrastructure Monitoring
ASSOC COMPUTING MACHINERY. 2015: 330–31
View details for DOI 10.1145/2737095.2742923
View details for Web of Science ID 000493278400032
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Mitigating the effects of variable speed on drive-by infrastructure monitoring
SPIE-INT SOC OPTICAL ENGINEERING. 2015
View details for DOI 10.1117/12.2084435
View details for Web of Science ID 000355726100007
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Effects of damage location and size on sparse representation of guided-waves for damage diagnosis of pipelines under varying temperature
SPIE-INT SOC OPTICAL ENGINEERING. 2015
View details for DOI 10.1117/12.2084439
View details for Web of Science ID 000355725000052
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Nonlinear feature extraction methods for removing temperature effects in multi-mode guided-waves in pipes
SPIE-INT SOC OPTICAL ENGINEERING. 2015
View details for DOI 10.1117/12.2084436
View details for Web of Science ID 000355725000051
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Temperature variation effects on sparse representation of guided-waves for damage diagnosis in pipelines
SPIE-INT SOC OPTICAL ENGINEERING. 2015
View details for DOI 10.1117/12.2084434
View details for Web of Science ID 000355725000045
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Rail-infrastructure Monitoring through the Dynamic Response of a Passing Train
DESTECH PUBLICATIONS, INC. 2015: 1451–58
View details for Web of Science ID 000365445301089
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Step-Level Person Localization Through Sparse Sensing Of Structural Vibration
ASSOC COMPUTING MACHINERY. 2015: 376–77
View details for DOI 10.1145/2737095.2742924
View details for Web of Science ID 000493278400054
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MyoVibe: Vibration Based Wearable Muscle Activation Detection In High Mobility Exercises
ASSOC COMPUTING MACHINERY. 2015: 27–38
View details for DOI 10.1145/2750858.2804258
View details for Web of Science ID 000383742200003
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Indoor Person Identification through Footstep Induced Structural Vibration
ASSOC COMPUTING MACHINERY. 2015: 81–86
View details for DOI 10.1145/2699343.2699364
View details for Web of Science ID 000546003000015
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Structural Sensing System with Networked Dynamic Sensing Configuration
ASSOC COMPUTING MACHINERY. 2015: 344–45
View details for DOI 10.1145/2737095.2737147
View details for Web of Science ID 000493278400038
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BOES: Building Occupancy Estimation System Using Sparse Ambient Vibration Monitoring
SPIE-INT SOC OPTICAL ENGINEERING. 2014
View details for DOI 10.1117/12.2046510
View details for Web of Science ID 000344110800045
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Toward characterizing the effects of environmental and operational conditions on diffuse-field ultrasonic guided-waves in pipes
SPIE-INT SOC OPTICAL ENGINEERING. 2014
View details for DOI 10.1117/12.2046347
View details for Web of Science ID 000344110800044
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Data-Driven Forecasting Algorithms for Building Energy Consumption
Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
SPIE-INT SOC OPTICAL ENGINEERING. 2013
View details for DOI 10.1117/12.2009894
View details for Web of Science ID 000323283300022
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Development of fragility functions as a damage classification/prediction method for steel moment-resisting frames using a wavelet-based damage sensitive feature
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
2012; 41 (4): 681-696
View details for DOI 10.1002/eqe.1151
View details for Web of Science ID 000301430900006
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Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage
Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
SPIE-INT SOC OPTICAL ENGINEERING. 2012
View details for DOI 10.1117/12.915409
View details for Web of Science ID 000304192100005
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Use of Wavelet-Based Damage-Sensitive Features for Structural Damage Diagnosis Using Strong Motion Data
JOURNAL OF STRUCTURAL ENGINEERING-ASCE
2011; 137 (10): 1215-1228
View details for DOI 10.1061/(ASCE)ST.1943-541X.0000385
View details for Web of Science ID 000296514500019
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Application of a sparse representation method using K-SVD to data compression of experimental ambient vibration data for SHM
Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011
SPIE-INT SOC OPTICAL ENGINEERING. 2011
View details for DOI 10.1117/12.881887
View details for Web of Science ID 000294447800132
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Application of time series based damage detection algorithms to the benchmark experiment at the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan
SMART STRUCTURES AND SYSTEMS
2009; 5 (1): 95-117
View details for Web of Science ID 000260847000007
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Application of a time series based damage detection algorithm to the Taiwanese benchmark experiment
10th International Conference on Application of Statistics and Probability in Civil Engineering
TAYLOR & FRANCIS LTD. 2007: 551–552
View details for Web of Science ID 000252204100214