"IEEE Sensors Alert" is a pilot project of the IEEE Sensors Council. Started as one of its new initiatives, this monthly digest publishes teasers and condensed versions of our journal papers in layman's language.
Articles Posted in the Month (December 2023)
Smart Healthcare: RL-Based Task Offloading Scheme for Edge-Enable Sensor Networks
Author: Rahul Yadav, Weizhe Zhang, Ibrahim A. Elgendy, Guozhong Dong, Muhammad Shafiq, Asif Ali Laghari, Shiv Prakash
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Anupama
Smart healthcare systems produce massive data, which is challenging to manage. The Internet of Medical Things (IoMT) and Artificial intelligence (AI) based smart healthcare systems and applications have shown potential in intelligent and accurate data management and support healthcare. While the edge-enabled network provides necessary computational resources to deal with enormous data, the proposed Computation Offloading using Reinforcement Learning (CORL) algorithm minimizes total latency and energy consumption.
A Radar-Based Human Activity Recognition Using a Novel 3-D Point Cloud Classifier
Author: Zheqi Yu, Ahmad Taha, William Taylor, Adnan Zahid, Khalid Rajab, Hadi Heidari, Muhammad Ali Imran, Qammer H. Abbasi
Published in: IEEE Sensors Journal (Volume: 22, Issue: 19, October 2022)
Summary Contributed by: William Taylor (Author)
Wearable sensors for human activity recognition (HAR) have many uses, especially in health, surveillances and man-machine conversation. Technological advancements have enabled non-invasive, contactless sensing methods to detect human activities. However, insufficient training data severely affects the performance of HAR applications. The paper discusses the dataset collection using 3-D cloud point technology and deep learning algorithms to classify the dataset, which will enable a transition from wearable to contactless sensing.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 8, April 2021)
Summary Contributed by: Laxmeesha Somappa
Origami is the art of paper folding to create a two-dimensional and three-dimensional sculpture. Inspired by this art, the researchers developed a flexible pressure sensor, which finds various applications in wearable devices and healthcare products. The origami structure inherently offers higher sensitivity and measurement range. These pressure sensors can easily be fabricated with 3-D printing technology, making them low-cost and enabling mass production.
Data Fusion Based on Temperature Monitoring of Aquaculture Ponds With Wireless Sensor Networks
Author: Haohui Chen, Xinyuan Nan, Sibo Xia
Published in: IEEE Sensors Journal (Volume: 23, Issue: 1, January 2023)
Summary Contributed by: Haohui Chen (author)
Aquaculture is the farming of aquatic animals and plants in a controlled environment. The water temperature is a vital environmental factor that affects the water quality and life of the aquatic species. The paper proposes an effective real-time aquaculture temperature monitoring method through a layered and clustered wireless sensor networks (WSNs) framework. It is more effective in temperature monitoring with improved accuracy in comparison to the traditional monitoring methods.
Image-Based Force Estimation in Medical Applications: A Review
Author: Ali A. Nazari, Farrokh Janabi-Sharifi, Kourosh Zareinia
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Anupama
Precise, real-time force estimation is still an ongoing challenge in minimally invasive robotic surgical (MIRS) interventions. The applied force depends on the size and deformity of the tissue. Advanced imaging techniques and deep-learning algorithms provide efficient object recognition and force estimation in MIRS. The researchers present a comprehensive review of image-based force estimation techniques for MIRS haptic force feedback.
Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron
Author: Umer Saeed, Syed Yaseen Shah, Adnan Zahid, Jawad Ahmad, Muhammad Ali Imran, Qammer H. Abbasi, Syed Aziz Shah
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Summary Contributed by: Kamalesh Tripathy
The COVID-19 pandemic highlighted the need for contactless respiration monitoring systems. A software-defined radio frequency sensing technique integrated with a deep learning algorithm was proposed for the non-invasive monitoring of various breathing patterns. The system used variations in channel state information produced by human motions to identify six distinct respiratory patterns. The prototype could classify these respiratory patterns with up to 99% accuracy.
On the Detection of Unauthorized Drones—Techniques and Future Perspectives: A Review
Author: Muhammad Asif Khan, Hamid Menouar, Aisha Eldeeb, Adnan Abu-Dayya, Flora D. Salim
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Muhammad Asif Khan (Author)
The increasing number of commercial drones poses severe threats to the security of critical infrastructure and people’s privacy. A drone detection system thus becomes inevitable to detect unauthorized drones in the low altitude airspace. This paper delves into the various aspects of an efficient, reliable, robust, and scalable drone detection system by investigating the four fundamental technologies and the associated challenges and limitations.
Inkjet-Printed, Nanofiber-Based Soft Capacitive Pressure Sensors for Tactile Sensing
Author: Riikka Mikkonen, Anastasia Koivikko, Tiina Vuorinen, Veikko Sariola, Matti Mäntysalo
Published in: IEEE Sensors Journal (Volume: 21, Issue: 23, December 2021)
Summary Contributed by: Anupama
Soft electronics enable lighter and more flexible human-machine interfaces. Learn about an inexpensive, additive approach to fabricating flexible, soft electronics using inkjet printing. Inkjet-printed micro-structured dielectric layers were sandwiched between conductive mesh electrodes to form the capacitive tactile pressure sensors. The sensor exhibits high sensitivity, long-term repeatability, and low hysteresis. The proposed approach can fabricate inexpensive, customizable soft electronics human-machine interfaces.
Precise Detection and Quantitative Prediction of Blood Glucose Level With an Electronic Nose System
Author: Zhenyi Ye, Jie Wang, Hao Hua, Xiangdong Zhou, Qiliang Li
Published in: IEEE Sensors Journal (Volume: 22, Issue: 13, July 2022)
Summary Contributed by: Zhenyi Ye (Author)
Monitoring blood glucose levels after exercise, diet, and medication is vital, especially in people with diabetes. A low-cost, no-pain glucose measurement method outside clinical settings for diabetes patients is essential. The work presents a non-invasive glucose measurement method using a novel electronic nose (E-Nose) device enabled by the machine learning algorithm. The proposed method is capable of precise qualitative glucose identification and quantitative analysis.
Towards Precision Agriculture: IoT-Enabled Intelligent Irrigation Systems Using Deep Learning Neural Network
Author: Pankaj Kumar Kashyap, Sushil Kumar, Ankita Jaiswal, Mukesh Prasad, Amir H. Gandomi
Published in: IEEE Sensors Journal (Volume: 21, Issue: 16, August 2021)
Summary Contributed by: Vinay S Palaparthy
Smart and precise irrigation planning plays a crucial role in preventing excess water usage and waste. Various machine learning-based irrigation models have been proposed. However, the proposed models should consider unpredictable climate changes. The researchers propose an intelligent neural network model considering the historical temporal dynamics of soil and climate. The prototype efficiently predicts volumetric water demand one day in advance.
Toward a Bio-Inspired Acoustic Sensor: Achroia grisella’s Ear
Author: Lara Díaz-García, Andrew Reid, Joseph C. Jackson-Camargo, James F. C. Windmill
Published in: IEEE Sensors Journal (Volume: 22, Issue: 18, September 2022)
Summary Contributed by: Lara Díaz García (Author)
Taking inspiration from nature can be advantageous when facing challenges in engineering and technology. The researchers overcame one such challenge of manufacturing miniature directional acoustic sensors by studying Achroia grisella, a small moth capable of directional hearing using one ear. Inspired by the shape of the moth eardrum, equations, simulations, and passive directional 3D printed samples were developed and examined with Laser Doppler Vibrometry.
An Implantable Antenna Sensor for Medical Applications
Author: Wei Wang, Xiu-Wei Xuan, Wan-Yi Zhao, Hong-Kuai Nie
Published in: IEEE Sensors Journal (Volume: 21, Issue: 13, July 2021)
Summary Contributed by: Payal Savani
Emerging technologies have led to the development of implantable medical devices, providing new methods for diagnosing and treating diseases. The researchers present a sensor prototype with an S-shaped monopole antenna with a closed-loop design. The prototype outperforms concurrent implantable devices concerning size, radiation gain, and sensitivity. The proposed sensor offers a minimally invasive way to monitor and diagnose cancer tumors and can save countless lives.
Smart bandages can accelerate healing, avoiding infections of severe injuries or surgical wounds by real-time wound assessments. The wound’s healing state can be predicted by tracking parameters like temperature, pressure, pH, and acidity. A smart bandage prototype embedded with wireless temperature and pressure sensors based on a conductive polymer, PEDOT: PSS (poly(3,4-ethylenedioxythiophene) polystyrene sulfonate), and an NFC (Near-field communication) tag is proposed. This battery-less system provides a cost-effective alternative for medical applications.
Metal-Organic Framework Materials Coupled to Optical Fibers for Chemical Sensing: A Review
Author: Chen Zhu, Rex E. Gerald, Jie Huang
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Summary Contributed by: Dayarnab Baidya
Metal-Organic Frameworks (MOFs) are crystalline nano-porous materials composed of inorganic metal nodes incorporated with organic ligands. Their remarkable structural and physicochemical tunability makes them superior to conventional chemo-sensory materials. The researcher presented a review of MOF-Optical fiber (OF) sensors based on a change in refractive index induced by adsorbed guest molecules. It demonstrated the promising potential of MOFs as dielectric coatings on OF for highly sensitive and selective chemical sensing.
Wireless Characterization and Assessment of an UWB-Based System in Industrial Environments
Author: Imanol Picallo Guembe, Peio Lopez-Iturri, Hicham Klaina, Guillermo Glaria Ezker, Félix Sáez De Jauregui Urdanoz, José Luis Zabalza Cestau, Leyre Azpilicueta, Francisco Falcone
Published in: IEEE Access ( Volume: 9)
Summary Contributed by: Francisco Falcone (Author)
Novel Ultra-Wideband (UWB)-based wireless communication system offers precision location and tracking in industrial settings. The electromechanical interference and heavy machinery can cause severe degradation of signal. The researchers present a hybrid deterministic 3D-RL approximation algorithm for wireless channel characterization of UWB systems in industrial indoor application. The proposed methodology enables optimal system planning and implementation of UWB-based indoor tracking systems in industrial environments.
Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements, and Challenges
Author: Praveen Kumar Reddy Maddikunta, Saqib Hakak , Mamoun Alazab, Sweta Bhattacharya, Thippa Reddy Gadekallu, Wazir Zada Khan, Quoc-Viet Pham
Published in: IEEE Sensors Journal (Volume: 21, Issue: 16, August 2021)
Summary Contributed by: Kamalesh Tripathy
Smart agriculture is the future to meet the growing food demand. Implementing information and communication technology (ICT) with unmanned aerial vehicles (UAVs) gives a better way to monitor farming under challenging conditions. Smart and precision agriculture demand knowledge of IoT (Internet of Things) applications, design architecture, protocols, etc. This paper explores different aspects of UAV implementations, Bluetooth-based wireless communication, agricultural sensors, design architecture, etc., and their future trends.
A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges
Author: Patrick McEnroe, Shen Wang, Madhusanka Liyanage
Published in: IEEE Sensors Journal (Volume: 9, Issue: 17, September 2022)
Summary Contributed by: Patrick McEnroe (Author)
Unmanned aerial vehicles (UAV) applications are often heavily dependent on artificial intelligence (AI) methods. Traditional cloud-based AI can find it hard to meet various UAV requirements, such as low latency and energy consumption. Edge AI, where AI is run on-device or at edge servers, is a viable solution. The researchers present an in-depth review of the convergence of edge AI and UAVs.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 1, January 2022)
Summary Contributed by: Anupama
Currently available 3D object classifiers combine point clouds and color images. They use complex models requiring an enormous memory to store their parameters. An efficient alternative method is proposed that utilizes information solely from point clouds. The point cloud objects are converted into bearing angle (BA) images and then classified by convolutional neural networks. This method achieves high accuracy while using significantly less time and memory.
The researchers present a novel target classification technique incorporating mmWave radar and deep learning models to classify moving objects. The system provides a wide field of view by orienting the antenna in elevation and rotating it in the horizontal field. With 97 – 99 % accuracy, the proposed classification technique is a cost-effective and dependable system for a wide range of autonomous applications.
The Machine Learnings Leading the Cuffless PPG Blood Pressure Sensors Into the Next Stage
Author: Paul C.-P. Chao, Chih-Cheng Wu, Duc Huy Nguyen, Ba-Sy Nguyen, Pin-Chia Huang, Van-Hung Le
Published in: IEEE Sensors Journal (Volume: 21, Issue: 11, June 2021)
Summary Contributed by: E.V.V. Hari Charan
Regular blood pressure (BP) monitoring helps in managing Cardiovascular diseases. Recent works on machine learning based on measured photoplethysmogram (PPG) waveforms have shown a strong possibility of estimating blood pressure by cuffless devices, such as recursive neural networks (RNN), long short-term memory (LSTM), etc. The challenge lies in the successful commercialization of cuffless BP sensors.
A Nanometer Resolution Wearable Wireless Medical Device for Non Invasive Intracranial Pressure Monitoring
Author: Rodrigo de A. P. Andrade, Helder Eiki Oshiro, Caio Kioshi Miyazaki, Cintya Yukie Hayashi, Marcos Antonio de Morais, Rodrigo Brunelli, João Paulo Carmo
Published in: IEEE Sensors Journal (Volume: 21, Issue: 20, October 2021)
Non-invasive intracranial pressure monitoring (NIICP) by measuring skull deformation has been studied extensively for assessing intracranial pressure and compliance. The researchers used this principle to design a novel wireless sensor. The proposed sensor is small, portable, cost-effective, and highly sensitive. It offers a more accurate clinical evaluation of intracranial dynamics and has the potential for a wide range of applications.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Summary Contributed by: Anupama
3D printing has emerged as a novel fabrication process for producing customized sensors at low cost. A uniaxial Ti6Al4V alloy accelerometer prototype was designed and fabricated using the Laser Powder Bed Fusion (L-PBF) technique. With micro dimensions and comparable differential sensitivity, the proposed prototype showcases a new genre of 3D-printed metal sensors which are low-cost, customizable, efficient, and durable.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 11, June 2021)
Summary Contributed by: Sheng-Kai Yeh (Author)
The tactile force sensor is the key enabling device for machines to interact with humans and objects. Due to the growing demand for smart-machine, metaverse, gaming, etc., miniaturized tactile force sensing chips have attracted attention and have also been developed through different detection and process technologies. The paper summarizes various tactile force sensors designed and fabricated based on the semiconductor CMOS processes.
Epilepsy is one of the most prevalent neurological diseases among humans. It can lead to severe brain injuries, strokes, and brain tumors. Early detection of seizures is critical to improving the day-to-day lives of patients. The researchers propose two deep learning approaches, using EEG data as input, which can detect epileptic seizures one hour before they occur.
Colon Cancer Detection by Designing and Analytical Evaluation of a Water-Based THz Metamaterial Perfect Absorber
Author: Zohreh Vafapour, William Troy, Ali Rashidi
Published in: IEEE Sensors Journal (Volume: 21, Issue: 17, September 2021)
Summary Contributed by: Anupama
Early detection of colon cancer is vital for patient survival. The researchers propose a novel device for the detection of colon cancer using terahertz electromagnetic waves. The device detects differences in water concentration within healthy and cancerous colon tissues by using surface plasmon polaritons (SPP). It shows potential as a less invasive, safer, faster, and early detection procedure for colon cancer.
IoT Enabled, Leaf Wetness Sensor on the Flexible Substrates for In-Situ Plant Disease Management
Author: Kamlesh S. Patle, Riya Saini, Ahlad Kumar, Sandeep G. Surya, Vinay S. Palaparthy, Khaled N. Salama
Published in: IEEE Sensors Journal (Volume: 21, Issue: 17, September 2021)
Summary Contributed by: Margi Hingrajia
Early detection of plant diseases can prevent crop failure. The Leaf wetness duration (LWD) that leads to fungal infections is a major concern among farmers. Using LWD as a parameter, researchers developed disease detection models with an Internet of Things (IoT)-enabled leaf wetness sensor (LWS) prototype fabricated on flexible substrates. Researchers tested the prototypes on medicinal plants. The prototype made comparatively accurate, precise, and early disease predictions.
Graphene and graphene derivative-based field effect transistor (FET) gas sensors are the most recent inclusion in the gas sensor family, having enormous potential to detect a wide variety of oxidizing and reducing target species with high sensitivity. The researchers adopted various strategies to improve the different performance index of the sensor either at the fabrication/device stage or at the operational/measurement technique level.
Determination of Salinity and Sugar Concentration by Means of a Circular-Ring Monopole Textile Antenna-Based Sensor
Author: Mariam El Gharbi, Marc Martinez-Estrada, Raúl Fernández-García, and Ignacio Gil
Published in: IEEE Sensors Journal (Volume: 21, Issue: 21, November 2021)
Summary Contributed by: Kamalesh Tripathy
Excessive sugar and salt in the diet are harmful to health. A wearable antenna sensor with real-time sugar and salt monitoring could help monitor salt and sugar intake. The researchers here propose an e-textile-based monopole antenna sensor prototype for it. The simple fabrication process, compact size, and high sensitivity make the prototype ideal for a blood sugar or sodium sensor.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 13, July 2021)
Summary Contributed by: Vahid Khojasteh Lazarjan (Author)
The portable Point-of-care (POC) devices that can detect diseases will revolutionize healthcare. The researchers propose a miniature wireless cell fiber-spectrophotometer prototype for real-time bio-markers detection and diagnostic support outside the laboratories. The low-power and lightweight spectrometer can identify biomarkers, such as tagged proteins or genetic materials, even in small samples. It promises effective point-of-care solutions for rapid testing of infectious diseases like SARS-CoV-2 or cancer.
False-Alarm-Controllable Radar Detection for Marine Target Based on Multi Features Fusion via CNNs
Author: Xiaolong Chen, Ningyuan Su, Yong Huang, Jian Guan
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Shradha Makhija
Sea surface target detection is vital for maritime security, surveillance, and rescue operations. The complexity of the marine environment makes it difficult to achieve robust, reliable, and adaptive target detection. Deep learning methods show better feature extraction ability and classification accuracy. The study proposes a new approach to marine target detection in complex background conditions using marine dual-channel convolutional neural networks (MDCCNN) with a false-alarm controllable classifier (FACC).
Multiplexed Silicon Nanowire Tunnel FET-Based Biosensors With Optimized Multi-Sensing Currents
Author: Sihyun Kim, Ryoongbin Lee, Daewoong Kwon, Tae-Hyeon Kim, Tae Jung Park, Sung-Jin Choi, Hyun-Sun Mo, Dae Hwan Kim, Byung-Gook Park
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Sihyun Kim (author)
Multiplexed sensing is an efficient approach for diagnosing and monitoring progressive diseases like cancer. This paper implements the independent detection of two different biomolecules in a novel single tunnel field-effect transistor (TFET) sensor. Since this new sensor can be perfectly co-integrated with complementary metal–oxide–semiconductor (CMOS) read-out circuits by state-of-art industry CMOS process, the mass production of CMOS-based biochips for multiplexed sensing is possible.
Micro-Doppler Based Target Recognition With Radars: A Review
Author: Ali Hanif, Muhammad Muaz, Azhar Hasan, Muhammad Adeel
Published in: IEEE Sensors Journal (Volume: 22, Issue: 4, February 2022)
Summary Contributed by: Anupama
Radar detection of smaller targets requires lowering the radar cross-section and velocity thresholds. With it, an abundance of target signatures gets generated, making it necessary to classify only relevant targets. Micro-motions of targets are significant characteristics. Micro-Doppler signatures have emerged as an effective method of classifying such targets. The study presents a systematic review of various micro-Doppler-based radar target signature analysis and classification techniques.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Sidrah Liaqat (Author)
Posture detection is important for monitoring health status. Incorrect postures may cause muscle weaknesses and body pain. The novel hybrid remote posture detection method developed by integrating machine learning (ML) and deep learning (DL) has produced promising results with 98% accuracy. Remote posture monitoring has the edge over camera-based, and wearable devices due to its privacy preserved feature.
Application of Physiological Sensors for Personalization in Semi-Autonomous Driving: A Review
Author: Edric John Cruz Nacpil, Zheng Wang, Kimihiko Nakano
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Summary Contributed by: Kamalesh Tripathy
With the increasing popularity and demand of autonomous vehicles, the safety, privacy, and comfort of the occupants have become prime concerns. The vehicle system can use various sensors to monitor the occupants' physical and mental health and collect behavioral data for further research and improvisation. The researchers present a detailed study on physiological sensors incorporated into the autonomous vehicle for emergencies or non-emergency circumstances.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 1, January 2022)
Summary Contributed by: Hongmin Zhu (author)
Butanone is an organic compound found in nature in traces and produced industrially on a large scale. It is extensively used in household products, industries, and labs. However, prolonged exposure to butanone is harmful, making its sensing and detection important. The researchers present an investigation on the butanone sensing properties of ZnO sensors and the effect of particle size on the detection of butanone by ZnO nanocrystals.
Online Wear Particle Detection Sensors for Wear Monitoring of Mechanical Equipment?A Review
Author: Ran Jia, Liyong Wang, Changsong Zheng, Tao Chen
Published in: IEEE Sensors Journal (Volume: 22, Issue: 4, February 2022)
Summary Contributed by: Laxmeesha Somappa
Mechanical equipment with moving parts is prone to wear that may lead to mechanical failures, damage, or even accidents. Monitoring the machinery to check its health and alert of any probable wear status is essential. The researchers here review the pros and cons of online wear particle detection sensors for real-time wear monitoring of the wear state of mechanical equipment.
Current Sensing Front-Ends: A Review and Design Guidance
Author: Da Ying, Drew A. Hall
Published in: IEEE Sensors Journal (Volume: 21, Issue: 20, October 2021)
Summary Contributed by: Drew A. Hall (Author)
Sensors have become a part of everyday life, seamlessly connecting the physical and electronic worlds. The paper focuses on the current-output sensing technique, providing information and analytical study of various sensors and design guidance of current readout circuits. Additionally, state-of-the-art current-sensing frontends are analyzed concerning gain, bandwidth, stability, and noise. The paper presents insights into general design architectures and their performance tradeoffs.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, January 2022)
Summary Contributed by: Pranjali Maru
Wearable gait recognition systems incorporating MEMS (micro-electromechanical systems) sensors are in demand because of their pivotal use in disease prevention, robotics, and identity recognition. Data pre-processing, filtering, and segmenting can successfully assist in detecting human gait. The patterns of the gaits are then analyzed to derive meaningful results. This exciting new domain has proven to be a lifesaver time and again.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Takuya Sakamoto (Author)
Early detection and diagnosis of Cardiovascular diseases save lives. The arterial pulse wave velocity (PWV) is one of the essential parameters to diagnose and monitor cardiovascular risk and condition. In the emerging trends of noncontact monitoring, the researchers experimentally demonstrated the accuracy of contactless technology for measuring arterial pulse wave propagation using an array radar system and laser displacement sensors that could replace contact monitoring.
Soft Biomimetic Optical Tactile Sensing With the TacTip: A Review
Author: Nathan F. Lepora
Published in: IEEE Sensors Journal (Volume: 21, Issue: 19, October 2021)
Summary Contributed by: Dayarnab Baidya
The sense of touch has a different significance in the human body than other senses, like hearing, sight, smell, and taste. The dexterous use of our hands for touch depends on the intelligent use of tactile perception. However, robotic hands lack the same level of dexterity as human hands. The researchers are working to develop methods to simulate the capabilities of the human sense of touch in machines.
Wireless Power and Data Transmission for Implanted Devices via Inductive Links: A Systematic Review
Author: Mohammad Javad Karimi, Alexandre Schmid, Catherine Dehollain
Published in: IEEE Sensors Journal (Volume: 21, Issue: 6, March2021)
Summary Contributed by: Mohammad Javad Karimi (Author)
Implantable medical devices (IMD) are developed to control and report acquired biological data from an implanted device in the body or brain to an external stage for biomedical purposes. They receive power from batteries or wireless power transmissions (WPT). Due to their simplicity and safety, magnetic waves are extensively studied and developed for powering in biomedical applications.
Multi-Sensor Complex Network Data Fusion Under the Condition of Uncertainty of Coupling Occurrence Probability
Author: Xianfeng Li, Sen Xu
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Payal Savani
Complex multi-sensor networks face challenges in storage management, data processing and resource optimization. Data fusion methods analyze and integrate diverse sensor information to produce coherent and accurate information. Researchers propose an adaptive weighted fusion algorithm on grouped sensor data that can efficiently reduce data redundancy, optimize resources, and lower network congestion. It showed higher accuracy and energy efficiency than other fusion algorithms.
Swin-Depth: Using Transformers and Multi-Scale Fusion for Monocular-Based Depth Estimation
Author: Zeyu Cheng, Yi Zhang, Chengkai Tang
Published in: IEEE Sensors Journal (Volume: 21, Issue: 23, December 2021)
Summary Contributed by: Zeyu Cheng (Author)
Depth estimation using monocular sensors is an important and challenging task in computer vision. The paper proposes a monocular depth estimation network Swin-Depth, which estimates the depth of a scene from only a single image. The proposed method achieved state-of-the-art results on challenging datasets based on hierarchical representation learning in Transformer-based monocular depth estimation networks and multi-scale fusion attention. It provides an accurate and efficient solution to the depth estimation problem.
Chipless RFID Sensors for Wearable Applications: A Review
Author: Santanu Kumar Behera
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, December 2022)
Summary Contributed by: Anupama
RFID-a radio-frequency identification technology, is gaining popularity as a wireless sensor for track and trace applications. The high cost of chipped-RFID tags makes them unsuitable for mass production. The Chipless-RFID tag is lightweight, durable, reliable, and energy-sufficient and can be mass-produced using inexpensive conductive inks or yarns. Improving range and data capacity in chipless-RFID tags could make them indispensable as wearables.
Realistic LiDAR With Noise Model for Real-Time Testing of Automated Vehicles in a Virtual Environment
Author: Juan P. Espineira, Jonathan Robinson, Jakobus Groenewald, Pak Hung Chan, Valentina Donzella
Published in: IEEE Sensors Journal (Volume: 21, Issue: 8, April 2021)
Summary Contributed by: Juan P. Espineira (Author)
The advancement in the automotive industry has made connected automotive solutions a reality. However, real-time testing and evaluating the solutions in the virtual environment is crucial to validate their safety and reliability. The paper presents a simulated LiDAR model with a rain model that runs in real-time in a high-fidelity simulated environment. It enables real-time testing using LiDAR data to be completed in a virtual environment.
Design and Realization of Wide Field-of-View 3D MEMS LiDAR
Author: Chia-Hsing Lin, Hao-Sheng Zhang, Chia-Ping Lin, Guo-Dung J. Su
Published in: IEEE Sensors Journal (Volume: 22, Issue: 1, January2022)
Summary Contributed by: Dayarnab Baidya
The usual MEMS mirror-based Light detection and ranging (LiDAR) systems are suitably lightweight and accurate but have a narrow field of view (FOV). The proposed LiDAR prototype with a customized wide-angle lens in front of the MEMS mirrors could successfully scan a large FOV to produce a 3D image with negligible distortion. Successful integration may increase its potential use in autonomous vehicles, drones, mobile robotic devices, disaster prediction etc.
Polymer Optical Fiber Liquid Level Sensor: A Review
Author: Runjie He, Chuanxin Teng, Santosh Kumar, Carlos Marques, Rui Min
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, January 2022)
Summary Contributed by: Rui Min (Author)
Polymer optical fibers (POFs) are compact, flexible, and resistant to chemical corrosion and electromagnetic interference. POFs are an excellent choice for high accuracy liquid level sensing. The materials like polymethyl methacrylate (PMMA) and perfluorinated polymer (CYTOP) are selected based on their bandwidth, chemical, and absorption characteristics. POFs with intensity modulation and wavelength modulation show better performance in liquid-level sensing.
Recent Applications of Different Microstructure Designs in High Performance Tactile Sensors: A Review
Author: Xuguang Sun, Tiezhu Liu, Jun Zhou, Lei Yao, Shuli Liang, Ming Zhao, Chunxiu Liu, Ning Xue
Published in: IEEE Sensors Journal (Volume: 21, Issue: 9, May2021)
Summary Contributed by: E.V.V. Hari Charan
The Internet of Things, robot hands, and smart living has increased the demand to develop flexible tactile sensors. The tactile sensors have perspective applications in healthcare monitoring, electronic skin, and artificial intelligence. The microstructure of the sensing unit is an essential factor in developing and improving the tactile sensor's sensitivity, response time, resolution, and robustness.
Fundamentals and Advancements of Topology Discovery in Underwater Acoustic Sensor Networks: A Review
Author: Yuan Liu, Haiyan Wang, Xiaohong Shen, Ruiqin Zhao, Lin Cai
Published in: IEEE Sensors Journal (Volume: 21, Issue: 19, October 2021)
Summary Contributed by: Yuan Liu (Author)
Underwater acoustic sensor networks (UANs) are an enabling technology to explore and uncover the mysterious oceans, a vast unknown territory on Earth. The first and often neglected challenge to building a UAN is to discover network topology. The study presented here provides a comprehensive review of existing approaches for UAN topology discovery, the challenges, and the opportunities beckoning further research.
Susceptibility of Stimuli-Responsive Hydrogels With Embedded Magnetic Microparticles for Inductively Wireless Chemical Sensing
Author: J. H. Park, S. H. Song, M. Ochoa, H. Jiang
Published in: IEEE Sensors Journal (Volume: 22, Issue: 2, January 2022)
Summary Contributed by: Abhishek Srivastava
Understanding the role of pH value in clinical diagnostic and drug delivery has recently gained research interest. Measuring pH value helps diagnose and assess different medical conditions, like skin structure and wound status, during a healing process. pH sensing is also used to control the release of the drug at the site of its measurement. The paper presents the susceptibility characterization of magnetic microparticles for sensing pH values for biomedical applications.
Neglecting quality monitoring can lead to contamination and degradation of packaged food. Temperature variation during storage encourages the growth of microorganisms and bacteria, making supervision essential for quality control. Smart packaging with inbuilt temperature and strain sensors can detect these anomalies caused by microbial contamination. The sensor also incorporates an NFC (near field communication) tag and an LED (light emitting diode) indicator for user-friendly notification.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Pranjali Maru
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.
In autonomous systems, mmWave radar sensors are highly reliable for target localization and tracking. However, due to the limited number of transceivers, they cannot accurately estimate the angle of arrival (AoA) of the targets. The researchers developed a novel machine learning-based AoA estimation and field of view (FoV) enhancement techniques for mmWave FMCW radars operating in the frequency range of 77-81 GHz. It has an improved field of view in both azimuth and elevation.
Textile-Based Pressure Sensors for Monitoring Prosthetic-Socket Interfaces
Author: Jordan Tabor, Talha Agcayazi, Aaron Fleming, Brendan Thompson, Ashish Kapoor, Ming Liu, Michael Y. Lee, He Huang, Alper Bozkurt, Tushar K. Ghosh
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Jordan Tabor (Author)
Transtibial amputees face many challenges while wearing prosthetic devices, including chronic discomfort. The commercially available rigid sensors are often used to understand the inner prosthetic environment better. It causes amputees additional discomfort during use. Here, the researchers propose a flexible, textile-based sensing method for prosthetic monitoring and a systematic approach to testing and integrating the sensors within prosthetics.
Early-stage lung cancer is difficult to detect. High-accuracy lung cancer diagnostic methods have previously been reported by measuring the concentration of nonanal gas in exhaled breath. Here, the researchers used alkaline catalysts in nonanal detection reactions inside a suitable glass with nanoscale pores by developing an alkali-resistant porous glass, thus fabricating a simple and highly sensitive nonanal gas sensor.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 13, November 2021)
Summary Contributed by: Kamalesh Tripathy
The recent COVID outbreaks highlighted the need for breathing rate monitoring and increased the demand for hospitalized patients. Monitoring breathing rate is vital for diagnosing diseases and observing patients with pulmonary conditions. The pros and cons of different techniques are studied and categorized under contact and remote modes of respiratory monitoring systems. Various Radar-based methods found to be more suitable for respiration monitoring are discussed.
A Low-Noise Instrumentation Amplifier With Built-in Anti-Aliasing for Hall Sensors
Author: Robbe Riem, Johan Raman, Jonas Borgmans, Pieter Rombouts
Published in: IEEE Sensors Journal (Volume: 21, Issue: 17, September 2021)
Summary Contributed by: Robbe Riem (author)
A silicon validation of an In-the-Loop Sampling Amplifier (ILSA) was proposed as a Hall sensor's core pre-conditioning analog interface circuit. It has the advantages of high one-step gain, low noise, low offset, and inherent anti-aliasing. It can be connected directly to any analog-to-digital converter. The resultant Hall system is a compact, low-noise readout architecture with a digital output.
Dielectrics for Non-Contact ECG Bioelectrodes: A Review
Author: Alhassan Haruna Umar, Mohd Afzan Othman, Fauzan Khairi Che Harun, Yusmeeraz Yusof
Published in: IEEE Sensors Journal (Volume: 21, Issue: 17, September 2021)
Summary Contributed by: Alhassan Haruna Umar (Author)
After years of existence and research efforts, dielectric materials in non-contact bioelectrodes guarantee the hope and survival of patients with heart abnormalities. Without painful skin abrasion, cardiac monitoring devices could reliably ensure constant care and well-being of patients. The researchers provide invaluable insights into the influence of dielectric materials that could change the future of ECG monitoring systems.
Portable Tools for COVID-19 Point-of-Care Detection: A Review
Author: Elga F. Saki, Samuel A. Setiawan, Dedy H. B. Wicaksono
Published in: IEEE Sensors Journal (Volume: 21, Issue: 21, November 2021)
Summary Contributed by: E.V.V. Hari Charan
The Global pandemic, COVID-19, surged the demand for easy-to-use, low-cost, portable, sensitive, and quick diagnostic devices with accurate detection probability for SARS-CoV-2 diagnosis. The researchers responded fast by developing various detection methods based on the target biomarkers. The focus is on the new approach using sensing arrays combined with artificial intelligence (AI) analysis to develop portable tools for reliable, inexpensive, and sensitive COVID-19 point-of-care detection.
A Hybrid Camera System for High-Resolutionization of Target Objects in Omnidirectional Images
Author: Chinthaka Premachandra, Masaya Tamaki
Published in: IEEE Sensors Journal (Volume: 21, Issue: 9, May 2021)
Summary Contributed by: Pranjali Maru
The growing use of cameras in crucial applications such as surveillance demands intensive research in image capturing and processing. Capturing a high-quality comprehensive view of a site is required. A hybrid camera platform consisting of an omnidirectional camera for a wide angle of images and a pan-tilt camera for handling the resolution of images is proposed. Multiple experiments demonstrated its ability to capture high-resolution images with a 360-degree panorama.
Blockchain-Federated-Learning and Deep Learning Models for COVID-19 Detection Using CT Imaging
Author: Rajesh Kumar, Abdullah Aman Khan, Jay Kumar, Zakria, Noorbakhsh Amiri Golilarz, Simin Zhang, Yang Ting, Chengyu Zheng, Wenyong Wang
Published in: IEEE Sensors Journal (Volume: 21, Issue: 14, October 2021)
Summary Contributed by: Anupama
COVID-19, the global pandemic, highlighted the need for global collaboration. Massive real-life COVID-19 patients' data were required for identifying positive cases and understanding the nature and spread of the rapidly evolving Coronavirus. A collaborative capsule-based deep-learning model was built to segment and classify COVID-19 infections using Computed Tomography (CT) imaging. The privacy concerns of the organizations, data authentication and normalization were addressed using a blockchain-based federated learning process. It resulted in rapid and accurate detection of COVID-19 symptoms without compromising privacy concerns.
Multifunctional Electronic Skin With a Stack of Temperature and Pressure Sensor Arrays
Author: Yogeenth Kumaresan, Oliver Ozioko, Ravinder Dahiya
Published in: IEEE Sensors Journal (Volume: 21, Issue: 23, December 2021)
Summary Contributed by: Ravinder Dahiya (author)
The rapid advancements in flexible electronics, nanotechnology and material science have enabled engineers and scientists to realise a flexible electronic skin (e-skin) with human-like sensing capabilities. The multifunctionality of such e-skin is proposed to enable robots with human-like dexterity, cognitive skills and abilities. This is anticipated to significantly advance interesting areas such as healthcare, robotics, and human–machine interfaces.
NO2 Gas Sensor Using Iodine Doped Graphene at Room Temperature with Electric Field Enhanced Recovery
Author: Monica Jaiswal, Robin Kumar, Jagjiwan Mittal, and Pika Jha
Published in: IEEE Sensors Journal (Volume: 22, Issue: 7, April 2022)
Summary Contributed by: Kamalesh Tripathy
Sensing NO2 gas in the air is an upcoming field of study due to its increased presence as an environmental pollutant and adverse effect on human health. Researchers developed a novel NO2 gas sensor using a synthesized material called the Iodine-doped Multilayer Graphene (I-MLG) to detect NO2 at its minimum concentration in air. The small doping of iodine in multi-layered graphene and the field effect transistor (FET) structure of the sensor makes the fabricated sensor rapid, reversible, compact and a good NO2 gas sensor.
Using Adaptive Wireless Transmission of Wearable Sensor Device for Target Heart Rate Monitoring of Sports Information
Author: Zhenyong Han
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Pranjali Maru
The growing consciousness for health and fitness supported by technological advancements has made smart wearable sensor devices for health monitoring popular. A target heart rate monitoring system, extracting clean heart signals from a polluted source, is proposed for effective micro-monitoring using an adaptive optimization algorithm. The adaptive wireless transmission of sports information and detection system for smart wear is then integrated with a smartphone to display the analysis to the user in a readable format.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 7, April 2022)
Summary Contributed by: Dayarnab Baidya
The humidity sensors are in massive demand for widespread applications in modern industries and agriculture. The novel differential humidity sensor designed by integrating air-filled substrate integrated waveguide (SIW), metal grid holes (METGH) and loaded with humidity sensitive (HS) materials boosted humidity sensing response. The longitudinally stacking of sensing and referencing resulted in a compact design, anti-temperature-interference ability, and enhanced sensitivity and resolution that could detect minor variations in environmental humidity.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, October 2021)
Summary Contributed by: Anupama
In vascular interventional surgery, experienced physicians rely on proximal force sensing to detect collisions and reduce vascular injury caused by surgical tools. However, in robot-assisted tele-interventional surgery (RATIS), providing high-precision force feedback to the physician is still the main challenge. The researchers developed a haptic robot-assisted catheter operating system with a novel spring-based haptic force interface. With a closed loop force adjustment system, the haptic force interface can provide accurate force feedback. Moreover, a collision protection function with a proximal-force-based collision detection algorithm was proposed to improve surgical safety. In case of no collision, transparency of the teleoperated system is realized; in case of collision, the provided haptic force will be amplified. The results demonstrated the usability of the developed haptic robot-assisted catheter operating system with collision protection function.
Self-Powered Cardiac Monitoring: Maintaining Vigilance With Multi-Modal Harvesting and E-Textiles
Author: Luis Javier Lopez Ruiz, Matthew Ridder, Dawei Fan, Jiaqi Gong , Braden Max Li, Amanda C. Mills, Elizabeth Cobarrubias, Jason Strohmaier, Jesse S. Jur , and John Lach
Published in: IEEE Sensors Journal (Volume: 21, Issue: 2, January 2021)
Summary Contributed by: Pranjali Maru
The advancements in sensors and circuits have led to the development of self-powered wearable sensing systems. Among many it could be used for uninterrupted active and vigilant cardiac monitoring by means of sensing and streaming electrocardiogram (ECG) and motion data to a smartphone. It enables effective care in a non-intrusive manner. Multi-modal energy harvesting from natural sources and integration with e-textiles make these sensing systems a considerable success.
Respiratory Monitoring During Physical Activities with a Multi-Sensor Smart Garment and Related Algorithms
Author: Carlo Massaroni , Joshua Di Tocco, Marco Bravi, Arianna Carnevale, Daniela Lo Presti, Riccardo Sabbadini, Sandra Miccinilli, Silvia Sterzi, Domenico Formica, Emiliano Schena
Published in: IEEE Sensors Journal (Volume: 20, Issue: 4, February 2020)
Summary Contributed by: Anupama
Wearable devices for continuous monitoring of physiological parameters have acquired significance for their usage in healthcare and sports science. Among other vital parameters, the measurement of respiration rate is crucial since it could be used to detect physiological abnormalities and health status changes and even help predict cardiac arrest. The multi-sensor smart garments made of conductive yarns show great potential in developing efficient, noninvasive, and unobtrusive respiration rate monitors.
Optimization of Sports Training Systems Based on Wireless Sensor Networks Algorithms
Author: Jun Yang and Wu Lv
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Anupama
Sports trainers traditionally use vision-based motion recognition technology and qualitative analysis to develop personalized training strategies for each athlete. Wireless Sensor Network-based smart monitoring system can track an athlete’s performance and biometrics in real-time and analyze it on cloud-based platforms. The results can help the trainers develop an informed training strategy for the athletes.
A Linear Slope Analyzing Strategy of GMR Sensor Transfer Curve for Static Detection of Magnetic Nanoparticles
Author: Shuai Yuan , Yimeng Du, and Philip W. T. Pong
Published in: IEEE Sensors Journal (Volume: 21, Issue: 21, November 2021)
Summary Contributed by: Pranjali Maru
Magnetic Nanoparticles (MNPs) have found promising applications in various upcoming technologies. The quantity of MNPs helps detect the biomolecules of the magnetic bio-detection platform marked by magnetic labels. Compared to the traditional subtraction method, a new linear slope analyzing strategy based on giant magnetoresistance (GMR) platform shows impressive performance.
Electronic Waste Reduction through Devices and Printed Circuit Boards designed for Circularity
Author: Moupali Chakraborty; Jeff Kettle; Ravinder Dahiya
Published in: IEEE Journal on Flexible Electronics (Volume: 1, Issue: 1, Jan. 2022)
Summary Contributed by: Ravinder Dahiya (author)
The extensive use of electronic goods has accelerated the threat of the rise in electronics waste (e-Waste). Its unregulated disposal causes environmental and health issues. Despite international policies and associated legalization, the exponential growth in production of waste Printed Circuit boards (WPCBs), use of poor raw material and energy-hungry manufacturing processes have spiked this problem as unsustainable. The use of emerging eco-friendly materials, resource-efficient manufacturing processes, and new technologies are needed to improve the industry's sustainability.
Summary Contributed by: Nauman Ali Choudhry (author)
Electronic textiles (E-textiles) have recently emerged as a promising technology and will soon transform the wearable industry. Due to its flexibility and ease of embedding in garments, wearable sensing has become a favourite choice for continuous health monitoring of athletes and medical patients. Advancements in textile-based sensors significantly impact the quality of life and will play an important role in the field of Internet of Things (IoT).
Though still not widespread in clinical applications, the detection of circulating tumor cells (CTC) attracts researchers' interest as a technique to diagnose and monitor cancer patients. They have been working on developing a miniaturized, portable, low cost, mass-producible device with the potential for automated and non-invasive diagnostics of CTCs in blood samples at point-of-care locations.
Portable Sensing Devices for Detection of COVID-19: A Review
Author: Deniz Sadighbayan, Ebrahim Ghafar-Zadeh
Published in: IEEE Sensors Journal (Volume: 21, Issue: 9, May 2021)
Summary Contributed by: Deniz Sadighbayan, Ebrahim Ghafar-Zadeh (authors)
Portable biosensing systems are crucial in deterrence, timely detection, and intensive care of pandemic-causing diseases like the disastrous COVID-19. The Global emergency led researchers to accelerate the development of portable diagnostic devices for recognizing SARS-CoV-2 and advancing the existing biosensor technology such as electrochemical, optical, and electrical for detecting other viruses and low viral loads.
A PCA-based method to select the number and the body location of piezoresistive sensors in a wearable system for respiratory monitoring
Author: Luigi Raiano, Joshua Di Tocco, Carlo Massaroni, Giovanni Di Pino, Emiliano Schena, Domenico Formica
Published in: IEEE Sensors Journal (Volume: 21, Issue: 5, March 2021)
Summary Contributed by: Leena Jha
The optimal number and body location of piezoresistive sensors to design wearables for monitoring respiratory rate are still debated. A Principal Component Analysis (PCA) based method developed to address this challenge considered different references (i.e., at rest and during walking/running). Trials demonstrated that real-time situations strongly influence the number of sensors and their location to optimize wearable performances.
A Wearable, Multimodal Sensing System to Monitor Knee Joint Health
Author: Caitlin N. Teague, J. Alex Heller, Brandi N. Nevius, Andrew M. Carek , Samer Mabrouk , Florencia Garcia-Vicente, Omer T. Inan , Mozziyar Etemadi
Published in: IEEE Sensors Journal ( Volume: 20, Issue: 18, September 2020)
Summary Contributed by: Anupama
Knee injuries and other minor or chronic knee conditions are prevalent. Monitoring rehabilitation or medication progress in knee treatment is time-consuming, expensive, and requires regular imaging, follow-ups, and several tests. However, knee health can be monitored and “joint health score” calculated remotely with wearable sensors that pick up sound, swelling, temperature and motion. Packaging these sensors into a wearable brace is vital for monitoring the knee.
Janus: A Combined Radar and Vibration Sensor for Beehive Monitoring
Author: Herbert M. Aumann; Margery K. Aumann; Nuri W. Emanetoglu
Published in: IEEE Sensors Letters (Volume: 5, Issue: 3, March 2021)
Summary Contributed by: Anupama
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.
Author: Ernie W. Hill, Aravind Vijayaragahvan, Kostya Novoselov
Published in: IEEE Sensors Journal (Volume: 11, Issue: 12, December 2011)
Summary Contributed by: Anupama
Graphene is often called a ‘miracle material’ due to its exceptional mechanical, electrical and chemical properties. It is a highly conductive, thinnest yet strongest, transparent and non-porous layer of pure carbon atoms in a honeycomb structure. Graphene has immense potential for fabricating various types of flexible sensors like mechanical, magnetic, electrochemical, biosensors, optical sensors etc.
Author: Anuj Kumar, Hiesik Kim, and Gerhard P. Hancke
Published in: IEEE Sensors Journal (Volume: 13, Issue: 4, April 2013)
Summary Contributed by: Jayraj Mulani
Humans are paying a heavy price for economic growth and overall development, whether infrastructure or industrial growth. The pollution and greenhouse gas emissions have led to environmental concerns and climate change, affecting health and life’s quality. However, a rise in environmental awareness created a demand for Environment monitoring systems (EMS) to detect the source and quantify the pollution level by providing a real-time data monitoring and alarm system.
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.
Author: Anindya Nag, Subhas Chandra Mukhopadhyay, Jürgen Kosel.
Published in: IEEE Sensors Journal (Volume: 17, Issue: 13, July 2017)
The use of sensors in the application world has drastically improved the human life. Sensors have reduced the time required to study events from hours, to a few seconds or minutes. Nowadays sensing systems are being used in gas sensing, environmental monitoring, as well as the food industry. Monitoring of physiological parameters is being done through Wearable Flexible Sensors (WFS). Tremendous scientific research is going on to develop sensors with better sustainability and sensitivity and to overcome challenges regarding handling of the generated data, comfort of the person concerned, and the power consumed by the devices. Better manufacturing techniques will help develop newer sensors encompassing all income categories in the near future.
Technologies for Printing Sensors and Electronics Over Large Flexible Substrates: A Review
Author: Saleem Khan, LeandroLorenzelli, Ravinder S. Dahiya
Published in: IEEE Sensors Journal (Volume: 15, Issue: 6, June 2015)
Printed sensors and electronics have attracted greater interest as printing facilitates low cost fabrication. With the advent of increased research and demonstration of printed sensors and electronics, we are not far from enabling large area electronics on flexible substrates through cost effective printing technologies on a wide scale. The cost- effectiveness of printing technologies and employing them for flexible electronics will open up new classes of applications, and dramatically change the electronics industry landscape.
Published in: IEEE Sensors Journal (Volume: 13, Issue: 10, October 2013)
Research in the field of flexible sensor skins has progressed significantly in last few decades. With patch antenna technology, these sensors can be wirelessly interrogated with very simple and low-power sensor circuitries for strain sensing, crack detection, shear measurement, bio-chemical sensing etc. Since the information is encoded as frequency, frequency division multiplexing can be exploited to form a large sensor array, hence making the antenna sensor an excellent candidate for flexible sensor skin implementation.
Author: Vladimir J. Lumelsky, Michael S. Shur, and Sigurd Wagner
Published in: IEEE Sensors Journal (Volume: 1, Issue: 1, June 2001)
Sensitive skin is a large array of sensors embedded in a flexible, stretchable, and/or foldable substrate that might cover the surface of a moving machine. It will make possible the use of machines in unsupervised environments by making them ‘cautious’ and find impressive applications in service industry, health industry, bioengineering, space exploration, and many more.
Published in: IEEE Sensors Journal (Volume: 2, Issue: 3, June 2002)
Pattern Analysis constitutes a critical building block in the development of gas sensor array instruments, which are potential substitutes to the human olfactory system. The process of analysis can be split into signal pre-processing, dimensionality reduction, prediction and validation. The design for successful pattern recognition for human olfactory system requires careful consideration and critical evaluation of various methods.
Author: MalithMaheepala, Abbas Z. Kouzani, Matthew A. Joordens
Published in: IEEE Sensors Journal (Volume: 20, Issue: 8, April 2020)
It’s impossible to imagine the modern lifestyle without positioning systems and navigation technologies. The widely used Global positioning system (GPS) and navigation technologiesare ineffective in indoor environments. The emergence of indoor positioning technologies came as a boon for the indoor. Indoor positioning using light signals have immensepotential to provide a reliable and more accurate solution to the indoor positioning systems.
Utilizing Blockchain to Overcome Cyber Security Concerns in the Internet of Things
Author: Bandar Alotaibi
Published in: IEEE Sensors Journal (Volume: 19, Issue: 23, December 2019)
The Internet of Things (IoT), a wide network of internet connected objects to exchange data, has found impressive solutions in the last two decades which improved people’s lives. To maximise the benefit of IoT applications, blockchain technology has been explored and utilized to enhance the security limitations of the IoT technology.
Published in: IEEE Sensors Journal (Volume: 20, Issue: 8, April 2020)
The emerging application of consumer grade EEG measuring sensors and advancement in technology, which had made it portable and affordable, has made it accessible in the general market. EEG devices now have a broader use other than medicine. The researchers, educationists, game developers, engineers, and psychiatrists are enthusiastic about the consumer grade EEG device, which has made the study of the brain accessible and its application quite convenient.
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 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.
The emerging application of consumer grade EEG measuring sensors and advancement in technology, which had made it portable and affordable, has made it accessible in the general market. EEG devices now have a broader use other than medicine. The researchers, educationists, game developers, engineers, and psychiatrists are enthusiastic about the consumer grade EEG device, which has made the study of the brain accessible and its application quite convenient.
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