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"IEEE Sensors Alert" is a new service of the IEEE Sensors Council. Started as one of its new initiatives, this weekly digest publishes teasers and condensed versions of our journal papers in layperson's language.
Articles Posted in the Month (March 2023)
Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Takuya Sakamoto (Author)
Early detection and diagnosis of Cardiovascular diseases save lives. The arterial pulse wave velocity (PWV) is one of the essential parameters to diagnose and monitor cardiovascular risk and condition. In the emerging trends of noncontact monitoring, the researchers experimentally demonstrated the accuracy of contactless technology for measuring arterial pulse wave propagation using an array radar system and laser displacement sensors that could replace contact monitoring.
Soft Biomimetic Optical Tactile Sensing With the TacTip: A Review
Author: Nathan F. Lepora
Published in: IEEE Sensors Journal (Volume: 21, Issue: 19, October 2021)
Summary Contributed by: Dayarnab Baidya
The sense of touch has a different significance in the human body than other senses, like hearing, sight, smell, and taste. The dexterous use of our hands for touch depends on the intelligent use of tactile perception. However, robotic hands lack the same level of dexterity as human hands. The researchers are working to develop methods to simulate the capabilities of the human sense of touch in machines.
Wireless Power and Data Transmission for Implanted Devices via Inductive Links: A Systematic Review
Author: Mohammad Javad Karimi, Alexandre Schmid, Catherine Dehollain
Published in: IEEE Sensors Journal (Volume: 21, Issue: 6, March2021)
Summary Contributed by: Mohammad Javad Karimi (Author)
Implantable medical devices (IMD) are developed to control and report acquired biological data from an implanted device in the body or brain to an external stage for biomedical purposes. They receive power from batteries or wireless power transmissions (WPT). Due to their simplicity and safety, magnetic waves are extensively studied and developed for powering in biomedical applications.
Multi-Sensor Complex Network Data Fusion Under the Condition of Uncertainty of Coupling Occurrence Probability
Author: Xianfeng Li, Sen Xu
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Payal Savani
Complex multi-sensor networks face challenges in storage management, data processing and resource optimization. Data fusion methods analyze and integrate diverse sensor information to produce coherent and accurate information. Researchers propose an adaptive weighted fusion algorithm on grouped sensor data that can efficiently reduce data redundancy, optimize resources, and lower network congestion. It showed higher accuracy and energy efficiency than other fusion algorithms.
Swin-Depth: Using Transformers and Multi-Scale Fusion for Monocular-Based Depth Estimation
Author: Zeyu Cheng, Yi Zhang, Chengkai Tang
Published in: IEEE Sensors Journal (Volume: 21, Issue: 23, December 2021)
Summary Contributed by: Zeyu Cheng (Author)
Depth estimation using monocular sensors is an important and challenging task in computer vision. The paper proposes a monocular depth estimation network Swin-Depth, which estimates the depth of a scene from only a single image. The proposed method achieved state-of-the-art results on challenging datasets based on hierarchical representation learning in Transformer-based monocular depth estimation networks and multi-scale fusion attention. It provides an accurate and efficient solution to the depth estimation problem.
Chipless RFID Sensors for Wearable Applications: A Review
Author: Santanu Kumar Behera
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, December 2022)
Summary Contributed by: Anupama
RFID-a radio-frequency identification technology, is gaining popularity as a wireless sensor for track and trace applications. The high cost of chipped-RFID tags makes them unsuitable for mass production. The Chipless-RFID tag is lightweight, durable, reliable, and energy-sufficient and can be mass-produced using inexpensive conductive inks or yarns. Improving range and data capacity in chipless-RFID tags could make them indispensable as wearables.
Realistic LiDAR With Noise Model for Real-Time Testing of Automated Vehicles in a Virtual Environment
Author: Juan P. Espineira, Jonathan Robinson, Jakobus Groenewald, Pak Hung Chan, Valentina Donzella
Published in: IEEE Sensors Journal (Volume: 21, Issue: 8, April 2021)
Summary Contributed by: Juan P. Espineira (Author)
The advancement in the automotive industry has made connected automotive solutions a reality. However, real-time testing and evaluating the solutions in the virtual environment is crucial to validate their safety and reliability. The paper presents a simulated LiDAR model with a rain model that runs in real-time in a high-fidelity simulated environment. It enables real-time testing using LiDAR data to be completed in a virtual environment.
Design and Realization of Wide Field-of-View 3D MEMS LiDAR
Author: Chia-Hsing Lin, Hao-Sheng Zhang, Chia-Ping Lin, Guo-Dung J. Su
Published in: IEEE Sensors Journal (Volume: 22, Issue: 1, January2022)
Summary Contributed by: Dayarnab Baidya
The usual MEMS mirror-based Light detection and ranging (LiDAR) systems are suitably lightweight and accurate but have a narrow field of view (FOV). The proposed LiDAR prototype with a customized wide-angle lens in front of the MEMS mirrors could successfully scan a large FOV to produce a 3D image with negligible distortion. Successful integration may increase its potential use in autonomous vehicles, drones, mobile robotic devices, disaster prediction etc.
Polymer Optical Fiber Liquid Level Sensor: A Review
Author: Runjie He, Chuanxin Teng, Santosh Kumar, Carlos Marques, Rui Min
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, January 2022)
Summary Contributed by: Rui Min (Author)
Polymer optical fibers (POFs) are compact, flexible, and resistant to chemical corrosion and electromagnetic interference. POFs are an excellent choice for high accuracy liquid level sensing. The materials like polymethyl methacrylate (PMMA) and perfluorinated polymer (CYTOP) are selected based on their bandwidth, chemical, and absorption characteristics. POFs with intensity modulation and wavelength modulation show better performance in liquid-level sensing.
Recent Applications of Different Microstructure Designs in High Performance Tactile Sensors: A Review
Author: Xuguang Sun, Tiezhu Liu, Jun Zhou, Lei Yao, Shuli Liang, Ming Zhao, Chunxiu Liu, Ning Xue
Published in: IEEE Sensors Journal (Volume: 21, Issue: 9, May2021)
Summary Contributed by: E.V.V. Hari Charan
The Internet of Things, robot hands, and smart living has increased the demand to develop flexible tactile sensors. The tactile sensors have perspective applications in healthcare monitoring, electronic skin, and artificial intelligence. The microstructure of the sensing unit is an essential factor in developing and improving the tactile sensor's sensitivity, response time, resolution, and robustness.
Fundamentals and Advancements of Topology Discovery in Underwater Acoustic Sensor Networks: A Review
Author: Yuan Liu, Haiyan Wang, Xiaohong Shen, Ruiqin Zhao, Lin Cai
Published in: IEEE Sensors Journal (Volume: 21, Issue: 19, October 2021)
Summary Contributed by: Yuan Liu (Author)
Underwater acoustic sensor networks (UANs) are an enabling technology to explore and uncover the mysterious oceans, a vast unknown territory on Earth. The first and often neglected challenge to building a UAN is to discover network topology. The study presented here provides a comprehensive review of existing approaches for UAN topology discovery, the challenges, and the opportunities beckoning further research.
Susceptibility of Stimuli-Responsive Hydrogels With Embedded Magnetic Microparticles for Inductively Wireless Chemical Sensing
Author: J. H. Park, S. H. Song, M. Ochoa, H. Jiang
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, January 2022)
Summary Contributed by: Abhishek Srivastava
Understanding the role of pH value in clinical diagnostic and drug delivery has recently gained research interest. Measuring pH value helps diagnose and assess different medical conditions, like skin structure and wound status, during a healing process. pH sensing is also used to control the release of the drug at the site of its measurement. The paper presents the susceptibility characterization of magnetic microparticles for sensing pH values for biomedical applications.
Neglecting quality monitoring can lead to contamination and degradation of packaged food. Temperature variation during storage encourages the growth of microorganisms and bacteria, making supervision essential for quality control. Smart packaging with inbuilt temperature and strain sensors can detect these anomalies caused by microbial contamination. The sensor also incorporates an NFC (near field communication) tag and an LED (light emitting diode) indicator for user-friendly notification.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Pranjali Maru
IoT applications, with their unique functionality and applications, are improving human lives. Analysis of a large amount of sensor data collected from these applications is made possible with the help of AI. The convergence of AI and IoT has proven to be a successful idea and has found its applications in health care, agriculture, the environment, and transportation.
In autonomous systems, mmWave radar sensors are highly reliable for target localization and tracking. However, due to the limited number of transceivers, they cannot accurately estimate the angle of arrival (AoA) of the targets. The researchers developed a novel machine learning-based AoA estimation and field of view (FoV) enhancement techniques for mmWave FMCW radars operating in the frequency range of 77-81 GHz. It has an improved field of view in both azimuth and elevation.
Time of Flight (ToF) camera sensor has emerged as a promising technology. Depth intensity pixel associated higher frame rate images, lightweight, compact design, and reduced power consumption and errors in the output have built great potential for ToF imaging in various domains. Despite its limitations like low resolutions and high noise, the ToF cameras are extensively used in computer graphics, machine vision, and robotics.
Hand gesture recognition has become an integral part of Human-Computer Interactions. The paper introduces a methodology using a video-based dataset and convolutional neural network (CNN) model. It utilizes an RGB-Depth camera to create a dataset of six distinct hand gestures. A lightweight CNN model is then developed to detect and classify hand movements. The experimental results highlight its accuracy and efficiency, facilitating its practical use in scenarios demanding precise gesture recognition.
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