Get exclusive breakthroughs on sensors in IoT, energy, healthcare, and more, delivered straight to your inbox.
"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 (Feb 2021)
Sensory Systems in Micro-Processor Controlled Prosthetic Leg: A Review
Author: Nur Azah Hamzaid, Nur Hidayah Mohd Yusof, Farahiyah Jasni.
Published in: IEEE Sensors Journal (Volume: 20, Issue: 9, May 2020)
In recent years, Micro-processor controlled prosthetic legs (MPCPL) are being preferred over conventional prosthetics because they use actuators to replace missing joint function and hence are more functional. Due to this the user’s walking gait and metabolic energy consumption can be imitated very well. The state-of-the-art MPCPL takes commands from the brain through muscles motion, converts that into the user’s gait intention and performs the locomotive motion based on the kinetics sensory system’s input. Very soon the comfort of the motion control will be complimented by taking inputs of eyes and ears to ensure gait further safer.
Author: Jacob T. Robinson, Eric Pohlmeyer, Malte C. Gather, Caleb Kemere, John E. Kitching, George G. Malliaras, Adam Marblestone, Kenneth L. Shepard.
Published in: IEEE Sensors Journal (Volume: 19, Issue: 22, November 2020)
Brain-sensing technologies have immense opportunities and challenges for researchers to explore and identify the best strategies to translate them into products and therapies to improve patients’ lives with neurological and other disorders. It raises the possibility of creating neural interfaces that can more effectively restore or repair neural function and reveal fundamental properties of neural information processing. The transition of these technologies into commercial products and therapies has enormous scope in the future.
Sensors and Systems for Wearable Environmental Monitoring Toward IoT-Enabled Applications: A Review
Author: Md Abdulla Al Mamun and Mehmet Rasit Yuce.
Published in: IEEE Sensors Journal (Volume: 19, Issue: 18, September 2019)
Environmental pollution has a significant impact on the health of the people and the atmosphere around them. The advancement in microelectronics, communication technologies, and miniature environmental sensing devices has boosted the wearable environmental monitoring systems (WEMS) to monitor environmental pollution. Since there is a strong interrelation between environmental pollution with the economic consequences and escalations in healthcare costs, wearable environmental devices are boon for society.
Author: Authors: Anshul Gaur, Abhishek Singh, Ashok Kumar, Kishor S. Kulkarni, Sayantani Lala, Kamal Kapoor, Vishal Srivastava, Anuj Kumar, and Subhas Chandra Mukhopadhyay
Published in: IEEE Sensors Journal (Volume: 19, Issue: 9, May 2019)
The progress on fire sensing technologies has been quite substantial due to advancements in sensing, information, and communications technologies. The sensing system’s hardware and algorithm ensure its excellent ability to detect early fire with less false positives. The information and communication technology focuses on issuing an early warning to notify the occupants and the fire department. Developing a robust fire system demands establishing the benchmark parameters for heat, flame, smoke, and gas levels detection in every fire scenario.
Sensing as a Service: Challenges, Solutions and Future Directions
Author: Xiang Sheng, Jian Tang, Xuejie Xiao and Guoliang Xue.
Published in: IEEE Sensors Journal (Volume: 13, Issue: 10, October 2013)
Mobile phones do have various sensors which are used for exciting sensing applications by creating a cloud computing platform. This could be used as crowd-sourced platform to create innumerable novel sensing applications which are energy-efficient too.
A robust pavement crack detection network is imperative to mitigate traffic accidents and minimize maintenance costs. The paper proposed an efficient hybrid model by merging YOLOv5 and Transformer, utilizing one-stage architecture and long-range dependency capture for reliable crack detection. The network's performance is further improved using test time augmentation (TTA) for crack detection. An efficient solution for urban pavement damage detection, it paves the way for expanding datasets to tackle diverse pavement issues.
Emotion recognition has garnered interest from researchers because of its importance in affective computing. Facial expressions can mask human emotions. However, studies show that electroencephalogram (EEG) signals can recognize and identify human emotions. Hence, EEG has emerged as an alternate method for emotion recognition. The paper proposes a novel approach through a reduced number of EEG electrode channels and a normalization method, demonstrating its promising applications in real-time emotion recognition.
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.