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Flexible PEDOT:PSS/PVA Temperature sensor for Cost-Effective Wearable Medical Devices

Flexible PEDOT:PSS/PVA Temperature Sensor for Cost-Effective...

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Applied Research in Electrical Engineering (AREE), National and International conference on

作者： Jaefar Teymourmoghadam Ebrahim Chegini Hezare Sevom Co. 7-Niloofar Sq. 1533-874-417 Tehran Iran Electrical Engineering Department Shahid Sattari Aeronautical University of Science and Technology Tehran Iran

ISBN: (数字)9798350377170

ISBN: (纸本)9798350377187

The development of flexible and biocompatible temperature sensors is critical for wearable healthcare applications, enabling continuous and non-invasive body temperature monitoring. This paper presents a temperature sensor based on a PEDOT:PSS/PVA composite fabricated using a straightforward drop-casting method encapsulated with polydimethylsiloxane (PDMS) for enhanced durability and biocompatibility. The device is based on the negative temperature coefficient (NTC) charateristics of the fabricated composite polymer, facilitating accurate measurement of temperature alterations. The fabricated sensor demonstrates consistent performance across a physiological temperature range $\left(32^{\circ} \mathrm{C}-40^{\circ} \mathrm{C}\right)$, achieving a temperature coefficient of resistance (TCR) of $0.68 \%{ }^{\circ} \mathrm{C}$. Measurements show a stable decrease in resistance when the sensor is in touch with human skin, reflecting its sensitivity to skin temperature changes. Experimental results show that the resistance returned to its initial baseline; highlighting the repeatability of the sensor and its reliability for dynamic monitoring. The encapsulation with PDMS further enhances the flexibility of the sensor and protects it against environmental hazards while maintaining its electrical and mechanical performance intact. Compared to existing flexible temperature sensors, this device offers a practical balance of sensitivity, flexibility, and ease of fabrication. Its simple design and scalable fabrication make it suitable for various wearable medical applications, including fever detection, thermal mapping, and integration into advanced health monitoring IoT systems. This study contributes to the advancement of flexible electronics for personalized healthcare solutions.

关键词： Temperature sensors Temperature measurement Performance evaluation Fabrication Sensitivity Medical services Skin Electrical resistance measurement Biomedical monitoring Immune system

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Advancing Patient Care: A WBAN-Based Sustainable Health Monitoring System for Stress Assessment

Advancing Patient Care: A WBAN-Based Sustainable Health Moni...

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International conference on Future Internet of Things and Cloud (FiCloud)

作者： Ghada Said Rezk Maria Al Bacha Deema Saber Al Madhoun Shaima Saeed Saleh Abdalla Gad Maha Yaghi Taimur Hassan Jawad Yousaf Mohammed Ghazal Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (数字)9798331527198

ISBN: (纸本)9798331527204

Wireless body area networks (WBANs) have recently gained immense popularity for their potential in various growing healthcare applications. This study presents an advanced sustainable patient care system that continually tracks and monitors patient vital signs such as heart rate, body temperature, and muscle electrical activity using a WBAN system for stress level assessment. Three integrated wearable sensors (an NTC temperature sensor, a pulse oximeter, and an EMG sensor) are attached to a patient’s arm to furnish real-time health monitoring data. The wireless data acquisition is achieved by integrating the portable sensor network with an ESP32 module. A mobile application is developed to enhance data visualization and provide stress-level indications, thus enabling more informed healthcare decisions. The system’s efficiency is demonstrated with real-time testing of accurate stress-level predictions on various adult patients based on recorded, accurate vital signs.

关键词： Temperature sensors Temperature measurement Wireless sensor networks Medical services Body area networks Real-time systems Mobile applications Biomedical monitoring Monitoring Stress

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Low Noise Uncooled 2.0⁺ μm APD for Photon Counting Imaging and LIDAR applications 48

Low Noise Uncooled 2.0<SUP>+</SUP> μm APD for Photon Counti...

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conference on Infrared Technology and applications XLViii Part of SPIE Defense and Commercial Sensing conference

作者： Oduor, Patrick Haddadi, Abbas Choi, Kwong-Kit Bank, Seth Campbell, Joe C. Dhar, Nibir K. Woods, Jack Dutta, Achyut K. Banpil Photon Inc Santa Clara CA 95054 USA Univ Texas Austin Austin TX 78712 USA Univ Virginia Charlottesville VA USA Virginia Commonwealth Univ Richmond VA USA Air Force Res Lab Wright Patterson AFB OH USA

ISBN: (纸本)9781510650916;9781510650909

State-of-art detectors having response over 2.0+ mu m wavelengths require cryogenic coolers to improve SNR and achieve high sensitivity. Next generation detectors are required to operate at room temperature (300 K) to fit small form factor sensor modules for SWaP-efficient space instruments and defense applications. iii-V materials-based p-i-n detectors (e.g. InGaAs) over 2.0+ mu m wavelengths suffer from lattice mismatch with substrate, resulting in high dark currents, low sensitivity (low SNR), and needing cooling. An avalanche photodiode (APD) with high gain will significantly increase sensitivity above p-i-n detector solutions;however, dark current also multiplies under high gain, leading to increased noise. An APD's material system dictates noise associated with gain process and depends on ratio of ionization coefficient (hereinafter mentioned as k or k-factor) which dictate the APD excess noise. In APDs, dark current and excess noise limit useful gain and hence the SNR of detection systems. Therefore, it is essential to reduce k-factor and dark current of an APD. We present a first in the world low-noise, high-gain, and high bandwidth 2.0+ mu m uncooled APD having k factor of <0.01 enabling low excess noise at a given gain. The APD uses a novel structure and a bandstructure-engineered multiplication region based on iii-V material system to reduce k-factor to near zero. We present the APD SACM device design, their simulations, and experimental results of fabricated APD devices. The uncooled 2.0+mu m APD matches advantages offered by HgCdTe APDs having k similar to zero, but with low dark currents at near room-temperature operation, and also mitigates both HgCdTe APDs and standard LEI-V p-i-n deficiencies to become an ideal solution benefiting to extend short-wave IR band to 2.0 + mu m for imaging applications.

关键词： APD Photodetector Array Linear Mode Geiger Mode Photon Detection LIDAR

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advanced Spectral Sensing Methods for Process Monitoring applications

Advanced Spectral Sensing Methods for Process Monitoring App...

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China Semiconductor Technology International conference (CSTIC)

作者： Ray Saupe Jörg Martin Ronny Otto Alexander Weiß Volker Stock Yuichiro Shimizu Fraunhofer Institute for Electronic Nano Systems Chemnitz Germany TQ Systems GmbH Chemnitz Germany Shinko Electric Industries CO. LTD. Nagano Japan

ISBN: (数字)9798350362190

ISBN: (纸本)9798350362206

Analytical measurement to determine the quantitative composition of sample mixtures is gaining in importance alongside the widespread measurement of basic physical parameters such as level, temperature or pressure. It is becoming a key factor in the safe operation and control of chemical processes in a wide range of applications. miniaturized analytical systems and spectral sensors based on molecular absorption in the near or mid-infrared range are suitable in many cases to meet specific user requirements such as cost-effectiveness, integrability and reliability. [1]. The paper provides a brief overview of spectral technologies in the near infrared region for chemical process monitoring, in particular on the measurement of liquids. We focus on two measurement systems with different spectral selection principles and performance capabilities. One of the systems is based on the use of Micro Electro Mechanical System (MEMS), the other one uses light emitting diodes for spectral selection. Their design and principles, with respect to the sample implementation, will be described. Furthermore, aspects of calibration development will be pointed out.

关键词： Temperature measurement Temperature sensors Process monitoring Temperature Production Gain measurement sensor systems

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Recent Advances in Human Activity Recognition Techniques: A Comprehensive Review

Recent Advances in Human Activity Recognition Techniques: A ...

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International Symposium on advanced Computing and Communication (ISACC)

作者： Sukanya Saha Debapriya Banik Department of Computer Science and Engineering ICFAI University Tripura Agartala India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Human Activity Recognition (HAR) interprets data from healthcare, security surveillance, human-computer interaction (HCI), and sensors to recognize and categorize human actions. The rapid development of artificial intelligence (AI) and the widespread use of sensors have drawn great interest and demonstrated the immense application potential of HAR systems based on non-invasive ambient sensors. Various methods for performing HAR have been reported by researchers. In this survey, it has been noticed that data can be collected in vision and sensor-based formats. The goal of video-based HAR is to automatically identify actions in video clips. Smart wearable sensors are the most popular kind of sensor-based HAR. Surveys have identified HAR tendencies across many contexts and applications. The researchers classified HAR techniques into three categories: online versus offline, multimodal versus unimodal, and feature-based versus learning-based approaches. This survey has focused on the recognition of different activities like sports, yoga, different dance poses, human interaction, and human actions. This survey also concentrated on single-view and multiview datasets. This study compares and contrasts the most recent HAR techniques with a discussion of widely used datasets. Various criteria, including dataset size and assessment metrics, were used to categorize and analyze the chosen studies. This survey also focused on different dataset availability.

关键词： Surveys Reviews Surveillance Medical services sensor systems Human activity recognition Security Intelligent sensors Wearable sensors Sports

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TEDCTSSA: Trust Enabled Data Collection Technique Based Sparrow Search Algorithm for WSN-Based applications 1

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22nd International conference on Next Generation Teletraffic and Wired/Wireless advanced Networks and systems, NEW2AN 2022

作者： Osamy, Walid Khedr, Ahmed M. Salim, Ahmed Aziz, Ahmed Computer Science Department Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Unit of Scientific Research Applied College Qassim University Qassim Unaizah Saudi Arabia Computer Science Department University of Sharjah Sharjah27272 United Arab Emirates Department of Computer Science College of Sciences and Arts Al-methnab Qassim University P. O. Box 931 Al-mithnab Buridah51931 Saudi Arabia Faculty of Science Zagazig University Zagazig Egypt Tashkent State University of Economics Tashkent Uzbekistan

ISBN: (数字)9783031302589

ISBN: (纸本)9783031302572

Wireless sensor networks (WSNs) are typically used to monitor and detect diverse objects in realistic environments, where security remains a major concern. Estimating the trust between WSN nodes increases the security of the network, and so enhances node-to-node communication. Here, we introduce a Trust Enabled Data Delivery Technique based Sparrow Search Algorithm (SSA) for WSN-based applications (TEDCTSSA). In TEDCTSSA, a nature-inspired based SSA and secure cluster head (CH) selection method based on node’s trust value and energy is proposed. For the efficient selection of CH, our fitness function takes into account node remaining energy and trust value. The simulation results reveal that the suggested method is more energy-efficient, provides a longer average network lifetime, and selects the most trustworthy nodes than other works in the literature. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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Application of Deep Learning Based on Edge Computing of Wireless sensor Networks

Application of Deep Learning Based on Edge Computing of Wire...

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advanced Algorithms and Control Engineering (ICAACE), International conference on

作者： Huaqiao Duan Qijing Wang Nanjing University Suzhou China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

With the rapid advancement of the Internet of Things (IoT) technology, Wireless sensor Networks (WSN) have become a fundamental component of contemporary society. Nevertheless, the surge in complex application scenarios coupled with an exponential increase in data volumes has rendered the traditional cloud computing processing model insufficient. The edge computing-based deep learning framework can effectively handle these large-scale image datasets without compromising privacy and security, facilitating intelligent analysis and decision-making. This study,through experimental design, we developed a deep learning model grounded in edge computing, tailored for addressing specific challenges in image data processing within wireless sensor networks, such as image recognition, classification, and analysis. For concrete metrics, consider a scenario where edge computing-based deep learning models were deployed for real-time traffic flow analysis. These models, by processing data locally, can reduce data transmission times by up to 70%, enhancing response times from seconds to milliseconds. Furthermore, in privacy-sensitive applications such as wildlife monitoring, edge computing ensures data is processed on-site, reducing the risk of sensitive data exposure by over 80%. Lastly, in terms of energy consumption, edge devices operating on optimized deep learning algorithms can achieve a reduction of up to 40% compared to traditional cloud-based processing methods, underlining the significant efficiency and performance gains achievable with this technology integration.

关键词： Deep learning Wireless sensor networks Cloud computing Computational modeling Image edge detection Data processing Data models Real-time systems Time factors Edge computing

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Study of a liquid level sensor based on a tilted long period grating imprinted on a plastic optical fiber 11

Study of a liquid level sensor based on a tilted long period...

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conference on advanced sensor systems and applications XI

作者： Bao, Haiyang Wu, Bingcheng Liu, Yuan Zhou, Yanfei Zheng, Jie Jilin Univ Coll Elect Sci & Engn State Key Lab Integrated Optoelect Changchun 130012 Peoples R China

ISBN: (数字)9781510646520

ISBN: (纸本)9781510646520;9781510646513

A tilted long period grating (LPG) fabricated on a commercial plastic optical fiber (POF) by a simple mechanical die-press-print method was proposed for liquid-level sensing. The liquid level sensing performances of the sensor with different structural parameters were studied theoretically and experimentally. The LPG fabricated on the POFs with different diameters (0.25, 0.50, and 1.00mm) were evaluated. And the liquid-level sensing performances of the so-obtained LPGs imprinted on a thinner POF with a diameter of 0.25mm, and with the period of 300 mu m, the tilted angle of 0-30 degrees and the groove depth of 30-75 mu m were investigated. The results show that when the LPG with the tilted angle of 30 degrees and the groove depth of 75 mu m, the highest sensitivity of -0.4631dB/mm was obtained in the level range of 20mm. In addition, the influence of temperature on the liquid level sensing performances of sensors was also studied. It was found that the sensitivity of the sensor was decreased with the increase of temperature.

关键词： Fiber Optic sensor Plastic Optical Fiber Long Period Grating Corrugated Surface Grating Liquid level Sensing

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IoT Aroma sensor Module to Determine Beverage Alcohol Grade 11

IoT Aroma Sensor Module to Determine Beverage Alcohol Grade

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and applications (IDAACS)

作者： Mendoza Montoya, Jorge Javier Torregrosa Penalva, German Avila Navarro, Ernesto Huanca Zea, Kevin Rivera Suana, Javier Alvaro Chilo, Jose Univ Tecnol Peru Dept Syst & Informat Arequipa Peru Miguel Hernandez Univ Dept Signal Theory & Commun Elche Spain Miguel Hernandez Univ Dept Mat Sci Opt & Mat Technol Elche Spain Andina Nestor Caceres Velasquez Univ Dept Elect & Telecom Juliaca Peru Univ Gavle Dept Elect Engn Math & Sci Gavle Sweden

ISBN: (纸本)9781665426053

Industry 4.0 is the technology of the future, which is based, among other things, on the Internet of Things (IoT) and sensors that provide online information about the production processes. Electronic noses (E-noses) are gas sensor technologies expanding IoT, contributing to better alcohol production performance and providing important information about production process parameters. In this work, we have developed a low-cost, wireless, and compactness aroma sensor module applied to the alcohol industry. We use four metal oxide sensors, MQ-2, MQ-3, MQ-4, and MQ-135, embedded in the E-nose headspace and controlled by a 32-bit ESP32 WROOM microcontroller. The alcohol grade measurements were performed on beer and wine samples. MQ-3 sensor was stable till 20% alcohol grade, and MQ-2, MQ-4, and MQ-135 sensors were regular only until 5% alcohol. Our experiments let us determined alcohol grade with precision above 92%.

关键词： E-Nose IoT Alcohol grade Industry 4.0

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Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network

Cognitive Congestion Alleviation Framework in IoT-Enabled WS...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International conference on

作者： R. Mohandas Sudha Y Narmatha P P.Venkata Prasad N. Manikandan Department of Electronics & Communication Engineering Chennai Institute of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Presidency University Bangalore Karnataka India Department of Computer Science and Engineering Sri Sairam College of Engineering Bangalore Karnataka India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad Telangana India Department of Business Administration Kalasalingam Academy of Research and Education Kalasalingam Business School Krishnankoil Viruthunagar India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The rapid advancement of Intelligent Transportation systems (ITS) has heightened the importance of reliable, real-time data transmission in Wireless sensor Networks (WSNs). However, congestion in data-heavy Internet of Things (IoT)-enabled networks remains a critical challenge, impacting communication efficiency and decision-making in ITS. In high-density IoT-ITS applications, traditional congestion control methods are insufficient to address the complexity and dynamics of data flows. Existing solutions often fail to adapt in real time to varying traffic loads, leading to delays and data loss. There is a strong need for a congestion alleviation framework capable of intelligently prioritizing data while dynamically managing network resources to ensure seamless information exchange in large-scale deployments. This study presents a Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network (V-CapMiAN-Parr), which combines the Vectorized Adaptive Capsule Neural Network (V-AdCapNet) and Multi-instance Attention Network (MAN), fine-tuned by the Parrot Optimizer (ParrOpt). This integration aims to effectively detect, mitigate, and prevent congestion through an advanced capsule-based attention mechanism with adaptive optimization. The suggested V-CapMiAN-Parr framework demonstrated significant improvements in congestion control, achieving data throughput efficiencies above 99.7%, packet delivery rates above 99.5%, and network reliability reaching 99.2% under high traffic loads. The model's adaptive weighting mechanism ensures real-time responsiveness and reliability, crucial for next-gen ITS applications. The V-CapMiAN-Parr framework effectively addresses congestion issues in IoT-enabled WSNs, providing a robust, scalable solution for ITS applications. This cognitive framework's advanced data prioritization and adaptive optimization capabilities are well-suited for enhancing the performanc

关键词： Wireless communication Wireless sensor networks Adaptive systems Transportation Telecommunication traffic Real-time systems Internet of Things Data communication Optimization Next generation networking

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