"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 (Nov 2020)

Fire Sensing Technologies: A Review

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.

2 min read

November 9, 2020

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IEEE Xplore Version

Articles Posted in the Month (Oct 2020)

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.

2 min read

October 5, 2020

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IEEE Xplore Version

Inertial Sensor Technology Trends

The human desire for accuracy in exploration and guided navigation has brought inventive changes in inertial sensors technology. Integrating inertial sensors with external aids like Doppler, star tracker, or Global Positioning Systems (GPS) improves their accuracy, enhances reliability, and helps overcome inertial drift. Its vast applications in autonomous vehicles, military and space technology, etc., demand the need for extremely low-cost, small size, efficient and batch-producible sensors.

An Improved YOLOv5 Crack Detection Method Combined With Transformer

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.