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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 (Jan 2022)
Lock-in Time-of-Flight (ToF) Cameras: A Survey
Author: Sergi Foix, Guillem Alenyà, and Carme Torras
Published in: IEEE Sensors Journal (Volume: 11, No: 9, September 2011)
Summary Contributed by: Pranjali Maru
Time of Flight (ToF) camera sensor has emerged as a promising technology. Depth intensity pixel associated higher frame rate images, lightweight, compact design, and reduced power consumption and errors in the output have built great potential for ToF imaging in various domains. Despite its limitations like low resolutions and high noise, the ToF cameras are extensively used in computer graphics, machine vision, and robotics.
Published in: IEEE Sensors Journal (Volume: 1, No: 4, December 2001)
From mechanical to automatic to self-driven cars, the emerging sensors are revolutionizing the automobile industry. Sensors have emerged as essential components of the automotive electronic control system. The three major areas of automotive systems application–powertrain, chassis, and body are all controlled by arrays of sensors. Advancing automotive sensor technologies have a significant impact on the present with immense scope for the future development of automotive systems.
Published in: IEEE Sensors Journal (Volume: 1, Issue: 4, December 2001)
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.
A Wireless, Passive Carbon Nanotube-Based Gas Sensor
Author: Keat Ghee Ong, Kefeng Zeng, and Craig A. Grimes
Published in: IEEE Sensors Journal (Volume: 2, Issue: 2, April 2002)
Multiwall carbon nanotube-silicon dioxide (MWNT-SiO2) coated composite surface has been developed as a linear, responsive, sensitive gas sensors for O2, CO2 and NH3 gases. The presence of gas concentration is measured by measuring corresponding changes in permittivity and conductivity of MWNT which consequently changes its resonant frequency. The advent of MWNT-SiO2 offers an enormous potential to build low cost, highly sensitive, linear, passive, portable, low power wireless gas sensors.
Multi-Sensor Chip for Monitoring Key Parameters in Bioprocesses
Author: Nurul IzniRusli, Irene Pia Vincentini, Frederik Ceyssens, Michael Kraft
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Wearable electronics, mobile applications, the Internet of Things (IoT) technology, and remote monitoring have revolutionized the health care system. The technological advancement in microfabrication techniques has enabled miniaturization and multi-sensing biosensors devices to monitor vital parameters in bioprocesses. Along with its multiple benefits like compact size, low cost, low power consumption, it can also monitor Cell’s density, oxygen, lactate, glucose, temperature, and pH in real-time.
Experimental Environments for the Internet of Things: A Review
Author: Luis Eduardo Lima, Bruno Yuji Lino Kimura, Valério Rosset
Published in: IEEE Sensors Journal (Volume: 19, Issue: 9, MAY 2019)
The Internet of Things (IoT) connects different objects embedded with sensors, software and state-of-the-art technologies through the internet, enabling them to communicate in real-time through the wired or wireless communication system. Its application requires validation before actual implementation to reduce the risk involved, especially in security and privacy. The development of experimental environment (testbeds) provides an efficient platform for conducting practical IoT experiments under real conditions and precise testing techniques for wireless sensor networks (WSN) and IoT applications before implementation.
Author: Adam T. Hayes, Alcherio Martinoli, Rodney M. Goodman
Published in: IEEE SENSORS JOURNAL (VOL. 2, NO. 3, JUNE 2002)
Humans have expertise in using animal’s evolved olfactory senses to their benefit. With the emergence of chemical sensors, efforts are made to make mobile odor-source sensing robots. However, odors cannot be sensed or measured by a single parameter such as wavelength or frequency. Studies show that a group of autonomous mobile robots using suitable algorithms performs superior to a single complex robot in odor localization tasks.
Author: Yazan Qiblawey, Muhammad E. H. Chowdhury, Farayi Musharavati, Erfan Zalnezhad, Amith Khandakar, and Mohammad Tariqul Islam
Published in: IEEE Sensors Journal (Volume: 21, Issue: 6, March 2021)
With fast growing older population, the need for knee or hip implants has grown tremendously. These implants have short lifetime due to implant wear, loosening, and misalignment. Therefore it becomes imperative to monitor the implants to avoid unexpected failure and unnoticed deterioration. Smart, instrumented implants can provide accurate monitoring of the implant, delaying the revision surgeries and its consequences.
Silicon piezoresistive stress sensors and their application in electronic packaging
Author: J.C. Suhling, R.C. Jaeger
Published in: IEEE Sensors Journal (Volume: 1, Issue: 1, June 2001)
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.
Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review
Author: E. Ramanujam, Thinagaran Perumal, S. Padmavathi
Published in: IEEE Sensors Journal (Volume: 21, Issue: 12, June 2021)
Human Activity Recognition (HAR) is a field that recognizes human activities from raw time-series signals acquired through embedded sensors of smartphones and wearable devices among others. Deep learning networks modeled after neural network of human brain are widely used in HAR system to retrieve and classify distinct activities. AT present they can accurately recognize simple human activities which make them very useful in Smartphone HAR systems.
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.
Fetal movement monitoring is vital for fetal health. The accuracy of the maternal perception in monitoring fetal movement varies. In this work, a wearable device with two accelerometers and machine learning algorithms was developed for accurate and continuous fetal movement monitoring. It aims for accuracy comparable to ultrasound. The device showed promising results in fetal movement monitoring, potentially providing valuable insights into the fetal biological profile during the perinatal period.
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