Article
Engineering, Electrical & Electronic
Hajer Abed, Simon Bellemare-Rousseau, Benjamin Belanger-Huot, Mehran Ahadi, Etienne Drouin, Mourad Roudjane, Marc-Andre Dugas, Amine Miled, Younes Messaddeq
Summary: A new wearable smart T-Shirt design for monitoring breathing rate using Received Signal Strength Indicator (RSSI) is proposed. The design includes a wireless sensor for monitoring breathing rate, a wireless power transfer system, and a user interface for analyzing the collected data. The study presents breathing curves obtained from a breathing sensor incorporated in a smart T-shirt and applies data analysis methods to extract important parameters for medical diagnosis. Additional results are also presented for different tests on male and female subjects using another design of a smart T-shirt system consisting of an array of six sensors.
IEEE SENSORS JOURNAL
(2022)
Article
Geosciences, Multidisciplinary
Chenhui Wang, Wei Guo, Kai Yang, Xi Wang, Qingjia Meng
Summary: This study proposes a novel landslide monitoring method based on the LoRa network and intelligent sensing IoT, which can detect abnormal changes of landslides in real time and provide a better data collection scheme for disaster monitoring and prediction.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Environmental Sciences
Yifan Sheng, Guangli Xu, Bijing Jin, Chao Zhou, Yuanyao Li, Weitao Chen
Summary: Landslide susceptibility mapping is important for assessing landslide risks. This study integrates spatio-temporal probability analysis and MT-InSAR method to dynamically map landslide hazards. The results identify key factors for landslide development and show that machine learning methods, particularly CNN, outperform statistical methods in accuracy. Adopting the CNN approach can enhance LSM accuracy.
Review
Environmental Sciences
Renato Macciotta, Michael T. Hendry
Summary: Transportation infrastructure in mountainous terrain and river valleys are susceptible to various landslide phenomena. Remote sensing techniques offer a way to enhance monitoring tools for geotechnical engineers, improving identification of landslides, complementing in-place instrumentation, and defining landslide extents and deformation mechanisms. The application of these techniques in Western Canada has provided practical insights for risk management strategies in dealing with landslide hazards.
Article
Chemistry, Multidisciplinary
Gabriel Hermosilla, Francisco Pizarro, Sebastian Fingerhuth, Francisco Lazcano, Francisco Santibanez, Nelson Baker, David Castro, Carolina Yanez
Summary: This article introduces a wireless sensor designed for pest detection, specifically targeting the Lobesia botrana moth. The sensor utilizes acoustic-based detection to identify flying moths, successfully tested in a controlled laboratory setting and in a vineyard region where the moth has been detected previously. The device provides real-time detection statistics and yields results consistent with traditional field traps.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Honghui Wang, Tianxiang Zhuo, Pan Zhong, Chaoyu Wei, Dingkang Zou, Yunshun Zhong
Summary: This article presents a magnetic induction communication transceiver MI-S125-III for transmitting internal characteristic parameters of landslide mass. Experimental results from a physical model show that the device can monitor the inclination angle of landslides and track the sliding process.
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Maximilian C. Scardelletti, Sameer Kulkarni, Robert R. Romanofsky
Summary: This paper demonstrates the fabrication and characterization of a novel wireless pressure sensor system that can monitor and report real-time changes in pressure on the rotor blade of a low speed axial compressor. The pressure sensor is wirelessly connected to a circuit box located on the compressor drum and the data is transmitted to a stationary antenna. The measurements from the wireless pressure system accurately show the changing pressure and can signal when the compressor stalls.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Rang Liu, Ming Li, Honghao Luo, Qian Liu, A. Lee Swindlehurst
Summary: Integrated sensing and communication (ISAC) is a key solution for addressing spectrum congestion and increasing demands. By sharing resources and using reconfigurable intelligent surface (RIS) technology, ISAC achieves higher efficiencies. This article analyzes the potential of deploying RIS in ISAC systems to improve communication and sensing performance, discusses existing explorations, presents a case study, and outlines open challenges and research directions.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Biodiversity Conservation
Yihao Wang, Chunjiang Zhao, Daming Dong, Kun Wang
Summary: Monitoring animal activities is crucial for assessing the impact of environmental conditions and human activities on different species. Recent developments in entomology-based monitoring methods, such as radar and machine vision, have greatly improved the accuracy and efficiency of data collection. This study focuses on laser-based monitoring methods, which allow real-time observation of insect activity and the study of their responses to environmental changes. We summarize four specific applications of these methods, including electronic trapping, collecting backscattered light or fluorescence, and indirectly monitoring insect populations by analyzing forest canopy characteristics. We also discuss the challenges and opportunities of these methods and highlight future research directions.
ECOLOGICAL INDICATORS
(2023)
Article
Engineering, Electrical & Electronic
Morad Zouheir, Mohammed Zniber, Syeda Qudsia, Tan-Phat Huynh
Summary: In this study, a (copper sulfide)-carrageenan nanocomposite was developed and used as a relative humidity sensor. Data acquisition and real-time monitoring were conducted using low-cost, wireless, and portable hardware.
SENSORS AND ACTUATORS A-PHYSICAL
(2021)
Article
Chemistry, Analytical
Saverio Romeo, Antonio Cosentino, Francesco Giani, Giandomenico Mastrantoni, Paolo Mazzanti
Summary: Remote monitoring sensors are now a standard practice in landslide characterization and monitoring, with the potential for high spatial and temporal resolution data when combining different technologies. This study conducted intensive monitoring at the Poggio Baldi landslide using radar, photography, and acoustic sensors, demonstrating their capability to understand the rock slope evolution and ongoing gravitational processes.
Article
Environmental Sciences
Bo Yu, Ning Wang, Chong Xu, Fang Chen, Lei Wang
Summary: This study proposes DeenNet, a specially designed model for landslide detection, which effectively maintains landslide features using a decoder-encoder network structure. Experimental results show that DeenNet outperforms other typical encoder-decoder networks, demonstrating its great potential for various applications.
Article
Automation & Control Systems
Dang Van Huynh, Tan Do-Duy, Long D. Nguyen, Minh-Tuan Le, Nguyen-Son Vo, Trung Q. Duong
Summary: In this article, a new UAV-aided intelligent wireless sensing scheme is proposed for minimizing the time and energy consumption of data collection. The simulation results demonstrate the suitability of the proposed approach for time-critical mission applications such as emergency communications, public safety, and disaster relief networks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Zhongxiang Wei, Fan Liu, Christos Masouros, Nanchi Su, Athina P. Petropulu
Summary: Integrated sensing and communication (ISAC) is a candidate 6G technology that aims to unify the operations of future networks. While information security challenges arise from including information signaling in the waveform, the sensing capability in ISAC transmission offers opportunities for secure techniques. This article discusses the challenges, opportunities, and approaches to securing ISAC transmission, as well as the potential of using sensing capability for obtaining target information.
IEEE COMMUNICATIONS MAGAZINE
(2022)
Article
Environmental Sciences
Faming Huang, Siyu Tao, Deying Li, Zhipeng Lian, Filippo Catani, Jinsong Huang, Kailong Li, Chuhong Zhang
Summary: This study aims to reduce the uncertainty in landslide susceptibility prediction (LSP) by exploring the neighborhood characteristics of landslide spatial datasets. Remote sensing and GIS were used to acquire and manage neighborhood environmental factors, and the landslide clustering effect was represented using the landslide aggregation index in GIS. Results showed that considering the neighborhood characteristics improved the accuracy of LSP.
Article
Geochemistry & Geophysics
Ping Lu, Wenyang Shi, Zhongbin Li
Summary: This study demonstrates the suitability and potential of low-orbit miniature satellites like PlanetScope for rapid mapping of landslide inventory. By combining change detection methods with the region-based level set evolution (RLSE) method, the efficiency and accuracy of landslide mapping can be improved.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Engineering, Civil
Gang Zhao, Ronghua Liu, Mingxiang Yang, Tongbi Tu, Meihong Ma, Yang Hong, Xiekang Wang
Summary: The study proposed a deep learning-based approach for flash flood warning in mountainous and hilly areas of China, outperforming traditional methods and showing better results when considering spatial features and long time series of precipitation. The approach provided reliable flash flood warnings, particularly when used in conjunction with ensemble results to mitigate uncertainty caused by small or unbalanced learning samples.
JOURNAL OF HYDROLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Taereem Kim, Tiantian Yang, Lujun Zhang, Yang Hong
Summary: This study applies CNN models to predict rainfall observation imagery for hurricane predictions. The results show satisfactory performance of the CNN models, but with limitations in underestimating larger rainfall rates.
ATMOSPHERIC RESEARCH
(2022)
Article
Geography, Physical
Binjie Chen, Yang Ye, Cheng Tong, Jinsong Deng, Ke Wang, Yang Hong
Summary: This article proposes a novel big data based iterative variation mining framework (IVMF) to reconstruct large-scale aerosol optical depth (AOD) data over China from 2000 to 2020. The results demonstrate that the IVMF can effectively and accurately resolve the missing AOD data problem, and have great potential to be generalized to other regions and remote sensing products.
GISCIENCE & REMOTE SENSING
(2022)
Article
Engineering, Civil
Zhi Li, Guoqiang Tang, Pierre Kirstetter, Shang Gao, J-L F. Li, Yixin Wen, Yang Hong
Summary: This study evaluates the performance of IMERG in extreme precipitation events in the US and compares different sensors and products. The results reveal uncertainties and variations in extreme precipitation estimates in IMERG.
JOURNAL OF HYDROLOGY
(2022)
Article
Geography, Physical
Davide Festa, Manuela Bonano, Nicola Casagli, Pierluigi Confuorto, Claudio De Luca, Matteo Del Soldato, Riccardo Lanari, Ping Lu, Michele Manunta, Mariarosaria Manzo, Giovanni Onorato, Federico Raspini, Ivana Zinno, Francesco Casu
Summary: This study utilizes satellite-based multi-temporal interferometric datasets to investigate terrain changes in Italy, and classifies triggering factors, showing that landslides and subsidence events are the main causes of terrain deformation.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Engineering, Civil
Weiyue Li, Qin Jiang, Xiaogang He, Haiqing Sun, Weiwei Sun, Marco Scaioni, Sheng Chen, Xin Li, Jun Gao, Yang Hong
Summary: This study develops an effective method to fuse multiple satellite-based precipitation products and improve their accuracy. The results demonstrate that the fused precipitation estimates outperform individual satellite-based products and perform better across different precipitation thresholds.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Zhi Li, Shang Gao, Mengye Chen, Jonathan J. Gourley, Yang Hong
Summary: Floods in the US exhibit strong spatiotemporal variability, mainly controlled by precipitation types and catchment attributes. In a future warmer climate, flood frequency and extent are projected to increase, while rainfall and flood seasonality are expected to weaken. The correlation between extreme rainfall and flood onsets will also change.
Article
Computer Science, Interdisciplinary Applications
Zhi Li, Mengye Chen, Shang Gao, Yixin Wen, Jonathan J. Gourle, Tiantian Yang, Randall Kolar, Yang Hong
Summary: This study evaluates the performance of hydrologic and hydraulic models with and without the reinfiltration process in extreme flooding events. The results emphasize the importance of considering the reinfiltration process even in extreme flood simulations. Saturated hydraulic conductivity and antecedent soil moisture are identified as the main factors contributing to the differences in model performance. The evaluation against stream gauges and high water marks for the Hurricane Harvey event shows that the reinfiltration scheme significantly improves the efficiency score and reduces the maximum depth differences. A recent update of the CREST-iMAP model Version 1.1, which incorporates two-way coupling and the reinfiltration scheme, has also been released for public access.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Civil
Mengye Chen, Zhi Li, Shang Gao, Ming Xue, Jonathan J. Gourley, Randall L. Kolar, Yang Hong
Summary: Flood prediction techniques have advanced and this study showcases a comprehensive flood prediction for Hurricane Harvey using high-resolution quantitative precipitation forecasts and deep learning nowcasts. The results indicate the strengths and limitations of different methods in terms of accuracy and precipitation intensity prediction.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Qi Liu, Jie Niu, Ping Lu, Feifei Dong, Fujun Zhou, Xianglian Meng, Wei Xu, Shan Li, Bill X. Hu
Summary: This study compared the performance of machine learning (ML) and deep learning (DL) methods in estimating the active layer thickness (ALT) and seasonal thaw depth of permafrost on the Qinghai-Tibetan Plateau. The results showed that convolutional neural networks (CNN) and long short-term memory (LSTM) models developed with longer lagging times exhibited better performance in thaw depth prediction compared to the randomforest (RF) models. The study also found an increasing trend in ALT on the Qinghai-Tibetan Plateau from 2003 to 2011, especially in the northern region. Additionally, the seasonal thaw depth deepened in different seasons.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Geochemistry & Geophysics
Ping Lu, Jiangping Han, Yonghong Yi, Tong Hao, Fujun Zhou, Xianglian Meng, Yinsheng Zhang, Rongxing Li
Summary: This study utilized InSAR technology to monitor the dynamic changes in permafrost in the Hoh Xil region on the Tibetan Plateau. The results show that the permafrost in this region is experiencing disturbances, which are closely related to changes in land surface temperature. Thawing permafrost has led to the formation and evolution of thermokarst landforms, such as retrogressive thaw slumps and thermokarst lakes.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Chengyuan Zhang, Qunming Wang, Ping Lu, Yong Ge, Peter M. Atkinson
Summary: This article proposes a fast and slow changes constrained spatio-temporal subpixel mapping (FSSTSPM) method to enhance subpixel mapping (SPM) by utilizing temporal information from time-series images. The FSSTSPM method is validated using synthetic datasets and real datasets, and the results demonstrate its superiority, especially in the presence of proportion errors.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geosciences, Multidisciplinary
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, Yang Hong
Summary: This study presents a hydrologic modeling framework, CREST-VEC, which combines a gridded water balance model and a newly developed vector-based routing scheme. The framework demonstrates significant improvements in computational efficiency and performance compared to conventional fully-gridded models, and incorporates a lake module for further enhanced accuracy. The proposed framework provides a solid basis for continental- and global-scale water modeling and allows for optimized streamflow predictions with quantified uncertainty information.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Environmental Sciences
Zhi Li, Shang Gao, Mengye Chen, Jonathan J. Gourley, Changhai Liu, Andreas F. Prein, Yang Hong
Summary: This study uses high-resolution climate simulations to reveal the changes in future flash floods. The results show that flashiness of floods in the US will increase, particularly in the Southwest and central regions. It calls for climate-resilient measures for emerging flash flood hot spots.
COMMUNICATIONS EARTH & ENVIRONMENT
(2022)
