Get exclusive breakthroughs on sensors in IoT, energy, healthcare, and more, delivered straight to your inbox.
"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 (March 2025)
High-Frequency Dynamic Compensation for Contact Scanning Probe Based on Dual-Parameter Feedback Optimization of Pole Configuration
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Saurabh Dubey
Contact scanning probes may have issues of reduced accuracy due to high speed and high frequency. This paper presents the innovative contact scanning probe, utilizing dual-parameter feedback to optimize pole configuration. It enhances accuracy by correcting high-speed and high-frequency errors with real-time accuracy and dynamic compensation. The approach aims to improve measurement accuracy and stability in high-speed scanning systems. It has promising potential in precision manufacturing, nanotechnology, and medical fields.
From Simulation to Surgery: Comprehensive Validation of an Optical Sensor for Monitoring Focal Laser Ablation of Solid Organ Tumors
Author: Geoghegan Rory, Hughes Griffith, Marks Leonard, Natarajan Shyam, Priester Alan, Sisk Anthony, Sun Songping, Tirado Richard
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Rory Geoghegan (Author)
Focal laser ablation (FLA) is a minimally invasive procedure using thermal coagulation to treat tumors with fewer side effects than surgery. However, it lacks an accurate and affordable monitoring method. This paper presents an optical sensor for real-time monitoring of the ablation process. The sensor has been validated through simulations, ex vivo, and clinical studies and can detect the coagulation boundary precisely without tissue-specific calibration.
Exploring and Identifying Bias-Instability Noise Sources in Mode-Split MEMS Gyroscopes Based on Electrostatic Frequency Tuning
Author: Jie Lin, Yang Zhao, Guoming Xia, Qin Shi, Anping Qiu
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Kamalesh Tripathy
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.
Conventional electronic substrates offer stability and reliability. However, they significantly contribute to electronic waste (e-waste). This study explores stone-based substrates, ranging from natural raw stone to stone paper, as sustainable alternatives for high-performance thin-film temperature sensors. Integrating biodegradable zinc (Zn)-based resistance temperature detectors (RTDs) and amorphous InGaZnO (IGZO)-based thermistors pave the way for dissolvable sensors and reusable substrates, thus leading to less harmful e-waste and advancing eco-friendly electronics.
EV-Fusion: A Novel Infrared and Low-Light Color Visible Image Fusion Network Integrating Unsupervised Visible Image Enhancement
Author: Wang Xia, Sun Qiyang, Yan Changda, Zhang Xin
Published in: IEEE Sensors Journal (Volume: 24, Issue: 4, February 2024)
Summary Contributed by: Saurabh Dubey
EV-Fusion is an innovative technology for low-light visibility applications. It enhances infrared and color images, surpassing nine leading methods in visual fidelity, brightness, and spatial frequency. Its real-time, high-contrast fusion capabilities show promise for military surveillance and traffic security, ensuring visibility of critical details in low-light conditions. Built on a Swin Local-Global Block framework, it utilizes color visible image enhancement and intensity image fusion modules to enhance texture and overall image quality.
Classification Strategies for Radar-Based Continuous Human Activity Recognition With Multiple Inputs and Multilabel Output
Author: Ingrid Ullmann, Ronny G. Guendel, Nicolas Christian Kruse, Francesco Fioranelli, Alexander Yarovoy
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Ullmann Ingrid (Author)
Fall detection systems can support independent living for people prone to falls. This paper introduces a novel approach using a radar-based continuous human activity recognition(HAR) system to study different activities by processing radar data in segments and using multilabel classification to recognize activities. The study explores deep learning methods, sensor networks, radar data types, and classification settings to enhance the effectiveness of accurate real-time activity recognition and detecting falls.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Saurabh Dubey
A breakthrough in PbSe thin-film transverse thermoelectric (TTE) photodetectors enhances sensitivity by adding 15-µm graphite coatings with light-trapping structures. This innovation improves photothermal conversion and sensitive light absorption, achieving a detection sensitivity of 415 µV cm/W, five times higher than traditional uncoated films. The increased efficiency positions this sensor as an advanced self-powered, ultrabroadband photodetector with future thermal sensor applications across various fields, ranging from ultraviolet to far-infrared wavelengths.
A Novel Plasmonic Nanoantenna-Based Sensor for Illicit Materials and Drugs Detection
Author: Marco Scalici, Patrizia Livreri
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Patrizia Livreri (Author)
The advancements in terahertz(THz) radiation have opened avenues for potential applications in the security and defense sectors. This paper introduces novel plasmonic nanoantennas-based sensors for detecting illicit materials and drugs through terahertz (THz) spectroscopy. Two innovative designs, the butterfly and shamrock nanoantennas, offer high sensitivity across specific THz frequencies. Their combined performance enables accurate, non-destructive molecular identification, providing an advanced tool for security, biomedical, and environmental applications.
Displacement Sensitivity and Range Enhancement Through Buckled Beam-Assisted OE-HCCR
Author: Qi Zhang, Yizheng Chen, Zhuo Li, Yan Tang, Yun Liang, Yi Huang, Xiaobei Zhang
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Kamalesh Tripathy
Displacement measurement sensitivity has broad industrial, scientific and construction applications. The paper proposes an ultrasensitive and wide-range displacement sensor using an open-ended hollow coaxial cable resonator (OE-HCCR) assisted by a buckled beam. The integration of buckled beams enhances sensitivity and extends the measurement range. The sensor demonstrates significant improvements in signal-to-noise ratio and accuracy. The developed system will contribute to advancing micro-scale and nano-scale displacement technology.
Monitoring of Lactococcus Lactis Growth Based on Reduced-Graphene Oxide TFT for Dairy Industry Applications
Author: L. Franchin, S. Casalini, A. Cester; A. Paccagnella, S. Bonaldo
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Franchin Lara (Author)
The biological activity of Lactococcus lactis (L. lactis) affects milk fermentation. This paper explores reduced-graphene oxide thin-film (rGO-TFT) to develop an effective biosensor, based on the field-effect transistor, for monitoring bacteria proliferation in dairy plants. This biosensor offers a real-time, highly sensitive, reliable, and non-invasive method to assess fermentation processes by detecting changes in electrical properties as bacterial populations grow, thus enabling precise bacterial growth monitoring in the dairy industry.
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.
The two-faced sensor system, JANUS, is designed to help beekeepers track bee activities like ‘Swarming’ and ‘Robbing’. The outward-looking Doppler radar monitors the bee flights while the inward-looking piezoelectric transducer senses the vibrations made by bees inside the hive. Researchers were able to use the level, duration and correlation between the two sensor signals to provide sufficient indication about different types of bee activity.
A non-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
Copyright 2023 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions
This site is also available on your smartphone.
