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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 (Mar 2021)
Visual Sensors Hardware Platforms: A Review
Author: Daniel G. Costa.
Published in: IEEE Sensors Journal (Volume: 20, Issue: 8, April 2020)
The embedded sensors in camera-enabled devices like the drones and smartphones have opened immense opportunities of bringing imaging capabilities to sensor networks. The networks of connected cameras using 5G, Zigbee, WiFi, Bluetooth protocols result in an advanced technology of visual sensors platforms. Very soon we expect on-board Artificial Intelligence and Machine Learning enabled System-on-Chip wireless visual sensor network (WVSN) platforms for IoT applications.
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.
The integrated circuits are known for high circuit densities that raise concerns for thermal, mechanical and low-cost packaging material induced stresses. All these put together either cause the chip to fail or perform against the design. Study of such stresses is mandatory before rolling out the chips from a Fab lab. Silicon Piezoresistive Stress Sensors have shown great potential for understanding and detecting stress distributions in electronic packages. It eventually helps in calibrating the IC parameters, selecting wafer planes and packaging materials, etc.
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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