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Low Power Compact Size Complex Permittivity sensor for Biomedical applications in 22nm FDSOI CMOS Technology

Low Power Compact Size Complex Permittivity Sensor for Biome...

IEEE International conference on Microwaves, Communications, Antennas, Biomedical Engineering and Electronic systems (COMCAS)

作者： Dossanov, Adilet Issakov, Vadim Tech Univ Carolo Wilhelmina Braunschweig Inst CMOS Design Braunschweig Germany

ISBN: (纸本)9798350348194;9798350348187

This paper presents a compact, low-power, complex permittivity sensor design in 22nm FDSOI CMOS technology. The design allows for measuring both the real and imaginary parts of the permittivity of the material under test that is exposed to the sensor. The sensor is integrated into the resonant tank of an oscillator circuit, where the output results are frequency-dependent oscillator frequency and output power. To convert the frequency information to DC voltage, a frequency discriminator consisting of a RC polyphase filter, a voltage-driven double-balanced passive mixer, and an operational amplifier acting as buffer and active low-pass filter are used. The functionality of the sensor is demonstrated by placing a small piece of fat tissue on top of the resonant tank. The chip has a miniature size and occupies only 0.56 mm(2) area. It consumes 6.4 mW of power from a 0.8 V supply which is much lower compared to the state-of-the-art.

关键词： Complex Permittivity Dielectric sensor Oscillator Phase Shift RC Polyphase Filter Passive Mixer

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High-Performance n-type Organic Thermoelectric Aerogels Toward Flexible Energy Harvesting and Sensing Devices

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advanced ELECTRONIC MATERIALS 2025年第0期

作者： Zhang, Chan Liu, xi Han, Shaobo Wu, Menxing xiao, Runfeng Chen, Shangzhi Chen, Guangming Wuyi Univ Coll Text Sci & Engn Jiangmen 529020 Peoples R China Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 610054 Peoples R China Shenzhen Univ Coll Mat Sci & Engn Shenzhen 518055 Peoples R China

Thermoelectric generators are one type of energy device widely used for wearable and flexible electronics to provide power to other devices. Organic aerogels with excellent thermoelectric and mechanical properties are promising candidates for such applications, but most of high-performance organic aerogels are made of p-type materials. It remains a great challenge to develop a low-cost and air-stable n-type organic aerogels with comparable performance with the state-of-the-art p-type counterparts to form an efficient thermoelectric power generator. In this study, a novel strategy based on a cellulose nanofiber skeleton is developed to form a high-performance n-type organic aerogel. The obtained n-type organic aerogels possess a Seebeck coefficient of -17 mu V K-1 and can combine with their p-type counterparts to form a generator outputting 1 mu W with a temperature difference of 50 K. Using the n-type organic aerogels, dual-parameter pressure and temperature sensing with high precision and reproducibility can be realized. The n-type aerogel will find its applications not only for outdoor self-powered systems, but also for human health diagnosis systems with real-time monitoring of multiple parameters without crosstalk.

关键词： energy harvesting flexible sensor n-type aerogel thermoelectric power generator wearable electronic device

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Virtual sensor for door opening detection and anomaly detection using machine learning 22

Virtual sensor for door opening detection and anomaly detect...

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22nd International conference on Intelligent systems applications to Power systems

作者： Neto, Almir Gomes, Luis Vale, Zita Fed Inst Educ Sci & Technol Maranhao IFMA Sao Luis Maranhao Brazil Polytech Porto P PORTO GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal

ISBN: (纸本)9798331531768;9798331531751

Currently, several studies are being developed using machine Learning with the aim of replacing real sensors with virtual sensors. One of the biggest challenges is obtaining quality data to enable the system modeling. This article proposes the replacement of a light dependent resistor sensor, applied to a refrigerator, which detects whether the door is open or closed and an anomaly test when the door is forgotten open for too long. The use of tiny machine learning is applied to ESP32 to enable the use of regression and classification models to detect the door opening and anomaly. The tested metrics for the regression were the root mean squared error. The comparative results between the virtual and real sensors are satisfactory with an accuracy of 99.59% for classification and a root mean squared error value of 0.01 for regression. Furthermore, a prototype was developed, and the model was embedded in the ESP32 microcontroller.

关键词： Tiny Machine Learning virtual sensors internet of things intelligent devices

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Two-dimensional material-assisted paper substrate-based strain sensor for motion signals measurement 13

Two-dimensional material-assisted paper substrate-based stra...

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advanced sensor systems and applications xIII 2023

作者： Khan, Danial Atif Khan, Muhammad Goyal, Amit Kumar Massoud, Yehia Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9781510667914

In this paper, we demonstrate the operation of flexible and highly sensitive MxENE-based capacitive strain sensor fabricated on a paper substrate. The use of common printing paper as a substrate not only makes the fabrication facile and inexpensive but also makes the sensor eco-friendly and biodegradable. The presented sensor has been mounted on the human body to monitor the movements of various joints like the wrist and the elbow. Upon application of strain, a noticeable change of more than 30% in the total capacitance of the sensor is observed. By measuring the change in the capacitance of the sensor, the movements of human joints can be monitored and used for applications like exercise and therapy. © 2023 SPIE.

关键词： Capacitance

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Latency Analysis for Real-Time sensor Sharing Using 4G/5G C-V2x Uu Interfaces

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IEEE ACCESS 2023年 11卷 35197-35206页

作者： Choi, Sinuk Kwon, Dongyoon Choi, Ji-Woong Daegu Gyeongbuk Inst Sci & Technol DGIST Dept Elect Engn & Comp Sci Daegu 42988 South Korea

With the development of communications, various applications of communication technologies, such as remote driving, delivery drones, and telesurgery, are emerging. In particular, in many cases, these applications need real-time video transmission services, and they should support low latency for operation reliability and quick response in emergencies. sensor sharing is required to support advanced communication services, but the latency analysis of device-to-remote users or remote servers with high data traffic is insufficient. Most related works have device-to-device communication or low data traffic messages for basic device status sharing. However, the latency analysis of sensor sharing between a device and a remote server or remote user is essential to support advanced communication services such as autonomous driving utilizing data offloading and device operation by remote users via the base station and server. Therefore, in this paper, we analyze the end-to-end latency and latency elements for video sharing, which is the most representative sensor in 4G long-term evolution (LTE) and 5G new radio (NR) Uu interfaces. In addition, we derive the supportable video resolution according to the raw video and encoded video transmission in each communication system. For each video resolution level, we analyze which latency elements have a significant effect on the end-to-end latency. Depending on each communication system, we investigate the number of users for the real-time sensor-sharing system that can be supported at the same time. Simulation results show that the LTE Uu interface supports up to full high definition (FHD) video resolution, and the 5G Uu interface supports up to ultrahigh definition (UHD). Additionally, the results show that only a single user can be supported with the FHD resolution level in the LTE Uu interface, whereas up to 19 users can be supported in the 5G Uu interface.

关键词： Vehicle-to-everything Real-time systems Streaming media Long Term Evolution Communication systems 5G mobile communication Servers Remote driving sensor sharing cellular communication system end-to-end latency vehicle-to-everything cellular network latency

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Using estimation to optimize electric pump flow rates for spraying applications 33

Using estimation to optimize electric pump flow rates for sp...

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conference on Signal Processing, sensor/Information Fusion, and Target Recognition xxxIII

作者： Appuhamy, Raveen McCafferty-Leroux, Alex Sicard, Brett Gadsden, S. Andrew McMaster Univ Dept Mech Engn Hamilton ON Canada

ISBN: (纸本)9781510674332;9781510674325

Electric pumps are widely used in applications such as sanitation, manufacturing and agriculture. Electric current is supplied to the pumps, which translates into a corresponding flow rate and therefore output pressure. This relationship between a pump's pressure and flow rate is described as its performance curve. This conference paper uses estimation theory and cognitive system techniques to improve the efficiency of electric pumps. Specifically, using the perception-action cycle to observe the states, predict the system behaviour and then optimize it. The system states are estimated using sensor measurements and system dynamics, where the control system uses the states to find the optimal flow rate based on the performance curve and adjust the system accordingly. This methodology is validated using simulations. The simulation models a sprayer that is powered by a DC motor where the ideal spray angle is maintained based on the distance to the surface. Optimizing the electric pump performance, reduces energy consumption and optimizes fluid usage, which can provide savings in many industries and systems.

关键词： Estimation theory Cognitive systems Electric pumps Optimizing electric pumps for spraying

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Recycled silicon solar cell-derived nanostructured p-black silicon device for high performance NO₂ gas sensor applications

RSC Applied Interfaces

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RSC Applied Interfaces 2024年第1期2卷 220-229页

作者： Aleem, Mahaboobbatcha Vishnuraj, Ramakrishnan Pullithadathil, Biji Nanosensors & Clean Energy Laboratory Department of Chemistry & Nanoscience and Technology PSG Institute of Advanced Studies Coimbatore 641 India Advanced Self-Powered Systems of Integrated Sensors and Technology Center Department of Electrical and Computer Engineering North Carolina State University Raleigh 27695 NC United States Center of Excellence in Advanced Materials and Green Technologies Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India Department of Chemical Engineering and Materials Science Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

Nitrogen dioxide (NO2) is a toxic gas that can cause respiratory problems, and sensing its presence is crucial for environmental monitoring and industrial safety. This investigation presents a novel approach towards s...

Nitrogen dioxide (NO₂) is a toxic gas that can cause respiratory problems, and sensing its presence is crucial for environmental monitoring and industrial safety. This investigation presents a novel approach towards sensing NO₂ gas by utilizing partially completed/recycled silicon solar cells employing a metal-assisted etching process to fabricate a high-performance p-black-silicon based sensor. Structural and morphological analyses using x-ray diffraction patterns, Raman spectroscopy and cross sectional FESEM characterization confirm the integrity of the p-B-silicon sensor. By combining recycling techniques with advanced fabrication methods, the resulting sensor exhibits exceptional sensitivity, a low detection limit of 1 ppm, and rapid response times (12-14 s) when exposed to NO₂ gas concentrations ranging from 1 to 5 ppm. The enhanced sensitivity is attributed to the unique nanostructured comb-like morphology of the sensor material, which facilitates fast charge transport mechanisms, and a plausible sensing mechanism has been proposed and explained using a depletion model diagram and energy model diagram. This eco-friendly and cost-effective solution not only addresses electronic waste concerns but also highlights the potential of sustainable practices in scientific research. The findings emphasize on the importance of environmental consciousness and innovation, showcasing a promising future for gas sensing technology. By utilizing recycled materials and advanced fabrication techniques, this study contributes to the development of efficient, eco-friendly sensors for environmental monitoring applications, paving the way for a more sustainable and technologically advanced future in the field of gas sensors. © 2025 RSC.

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Dual-Mode Pressure sensor Integrated with Deep Learning Algorithm for Joint State Monitoring in Tennis Motion

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JOURNAL OF sensorS 2023年第1期2023卷

作者： Gao, Jianhui Li, Zhi Chen, Zhong Huazhong Univ Sci & Technol Sch Phys Educ Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China

The precise capture and identification of movement features are important for numerous scientific endeavors. In this work, we present a novel multimodal sensor, called the resistance/capacitance dual-mode (RCDM) sensor, which effectively differentiates between compression and stretchable strains during tennis motion;meanwhile, it can also accurately identify various joint movements. The proposed wearable device features a seamless design, comprising two separate components: a resistive part and a capacitive part. The resistive and capacitive components operate independently and utilize a resistance-capacitance mechanism to measure pressure and strain signals, respectively. The RCDM sensor demonstrates remarkable sensitivity to strains (GF=7.84, 0%-140%) and exceptional linear sensitivity (S=4.08kPa(-1)) through capacitance. Utilizing machine learning algorithms, the sensor achieves a recognition rate of 97.21% in identifying various joint movement patterns. This advanced production method makes it feasible to manufacture the sensors on a large scale, offering tremendous potential for various applications, including tennis sports systems.

关键词： Tennis

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advanced RSS-Based Multisource Localization: Sequential Hypothesis Testing for Robust Location Estimation

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IEEE sensorS JOURNAL 2024年第22期24卷 37324-37331页

作者： Ketabalian, Hamid Biguesh, Mehrzad Sheikhi, Abbass Shiraz Univ Sch Elect & Comp Engn Dept Commun & Elect Engn Shiraz *** Iran

Accurate estimation of the number, locations, and transmit powers of wireless signal sources is crucial for various applications, including surveillance and monitoring. In this article, we propose a novel algorithm based on received signal strength (RSS) measurements to address this problem. Our approach utilizes sequential binary hypothesis testing, offering a computationally efficient solution without prior knowledge of the number of sources. Through extensive simulations, we demonstrate the superior performance of our algorithm compared with the existing methods, such as exhaustive search and multiresolution (MR) search, in terms of accuracy and computational complexity. Notably, our algorithm exhibits robustness in scenarios with multiple sources and close proximity between them. We also conduct performance analysis to evaluate its sensitivity to noise variance and false alarm probability, showcasing its reliability under different conditions. Our work contributes to advancing wireless signal processing techniques and offers promising implications for enhanced surveillance and monitoring capabilities in wireless communication systems. Overall, our proposed algorithm presents an efficient and accurate solution for estimating wireless signal sources, with potential for significant impact on practical applications.

关键词： Location awareness sensors Vectors Testing Wireless sensor networks Wireless communication Extraterrestrial measurements Location fixing maximum likelihood (ML) multisource localization received signal strength (RSS) sequential hypothesis test source enumeration

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Thermal imagers with boost: Range prediction with the Johnson Criteria 20

Thermal imagers with boost: Range prediction with the Johnso...

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conference on Electro-Optical and Infrared systems - Technology and applications xx

作者： Adomeit, Uwe Fraunhofer IOSB Gutleuthausstr 1 D-76275 Ettlingen Germany

ISBN: (数字)9781510667044

ISBN: (纸本)9781510667037

Range prediction for thermal imagers applying advanced signal processing is still in its infancy. Boost filters are such an advanced signal processing and here it was assessed if the achieved range when using them is in correspondence with predictions based on the Johnson criteria. Equipment in test was an under-sampled MWIR imager operating with and without five different boost filters, four different Laplace- and one Wiener-filter. Range of this imager using the different boost filter was estimated by perception experiments for identification of numbers. These ranges were compared with limiting frequencies derived from Minimum Temperature Difference Perceived (MTDP) measurements including the boost filters. The comparison showed identification range and limiting frequency derived from the MTDP in good correspondence. Thus, the Johnson Criteria should be able to correctly predict range for thermal imagers including boost-filtering. Further work includes extending the comparison to low contrast and to real targets.

关键词： MRTD MTDP sensor Performance Boost Filter Identification Range Imager Performance Assessment Perception Experiment

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