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"IEEE Sensors Alert" is a pilot project 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 (February 2023)
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.
Humans are paying a heavy price for economic growth and overall development, whether infrastructure or industrial growth. The pollution and greenhouse gas emissions have led to environmental concerns and climate change, affecting health and life’s quality. However, a rise in environmental awareness created a demand for Environment monitoring systems (EMS) to detect the source and quantify the pollution level by providing a real-time data monitoring and alarm system.
MEMS gyroscope has advanced with the advancements in processing and manufacturing technology. However, their structure and system-based noise level continue to pose challenges in proper implementation and restrict their performance with high accuracy and precision. This paper proposes a system-level noise model that analyzes the relationship between frequency split and noise performance. It identifies noise sources and contributes to bias instability, establishing a frequency-tuning criterion for different noise requirements.
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