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22nd ACM conference on Embedded Networked sensor systems, SenSys 2024

作者： Liu, Kaiwei Yang, Bufang Xu, Lilin Guo, Yunqi Ling, Neiwen Zhao, Zhihe Xing, Guoliang Shuai, Xian Ren, Xiaozhe Jiang, Xin Yan, Zhenyu The Chinese University of Hong Kong Hong Kong Hong Kong Noah's Ark Lab Huawei Technologies Hong Kong Hong Kong

ISBN: (纸本)9798400706974

Despite the extensive use of sensors enabling intelligent applications, the complementary potential of co-existing sensor systems is often not fully utilized, limiting more advanced applications. This paper introduces a novel solution using Large Language Models (LLMs) to coordinate sensor systems for handling complex user queries. It defines a sensor language for sensor systems, including vocabulary set and grammar rules, analogous to natural language components, enabling LLMs to translate user intentions into sensor coordination plans. Preliminary results show that our approach significantly outperforms the existing solution at plan generation, execution and response generation stages. © 2024 Copyright held by the owner/author(s).

关键词： Context sensitive grammars

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Adaptive Neuro-Fuzzy Inference systems for Cognitive sensor Communication in Smart Cities

Adaptive Neuro-Fuzzy Inference Systems for Cognitive Sensor ...

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2024 IEEE International conference on Intelligent systems and advanced applications, ICISAA 2024

作者： Pradhan, Rahul Prathiba, Ch. Kholmukhamedov, Timur Patil, B.N. Mary, S. Suma Christal Raj, I Infant GLA University Department of Computer Engineering and Applications Mathura India Vignana Bharathi Institute of Technology Department of CSM Ghatkesar Hyderabad India Turin Polytechnic University Automatic Control and Computer Engineering Department Tashkent Uzbekistan Yeshwantrao Chavan College of Engineering Department of Applied Physics Nagpur India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of CSE Tamil Nadu Trichy India

ISBN: (纸本)9798331539948

Modern urban development depends on optimizing cognitive sensor communications in smart cities, which is the focus of this investigation. In the era of expanding sensor networks, efficient data transmission is paramount for the success of smart city initiatives. The current state of sensor communication faces challenges like suboptimal adaptability, inefficient energy usage, and limited fault detection. This study proposes a solution through the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS), identifying these challenges as opportunities for improvement. The novelty lies in ANFIS's introduction as an intelligent and adaptive solution. Its ability to learn from sensor data, adapt to changing conditions, and optimize communication parameters sets it apart in enhancing cognitive sensor communication. The research methodology involves a systematic approach, encompassing data collection, pre-processing, and ANFIS model development. The model is rigorously trained, validated, and tested for real-world effectiveness. Integration into the smart city communication system is explored, emphasizing applications in context-aware communication, energy-efficient protocols, and fault detection. Performance is evaluated using metrics like accuracy, reliability, and efficiency, demonstrating the model's efficacy in addressing drawbacks and enhancing overall sensor communication in smart cities. The findings contribute to advancing intelligent systems for urban infrastructure and services. © 2024 IEEE.

关键词： Fuzzy neural networks

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Research on a Bipolar Structure Voltage sensor Based on Capacitive Coupling Principle 5

Research on a Bipolar Structure Voltage Sensor Based on Capa...

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5th IEEE International conference on advanced Electrical and Energy systems, AEES 2024

作者： Luo, Bofeng Li, Shijie Hou, Tianyu Hu, Siyu Zhang, Chuyan China Southern Power Grid Company Limited Guangzhou China China University of Geosciences Beijing Beijing China

ISBN: (纸本)9798331517724

This paper investigates a bipolar structure voltage sensor based on the principle of capacitive coupling. The non-contact voltage sensor, based on electric field coupling, offers advantages such as simple structure, excellent insulation performance, and fast response. A bipolar differential electrode structure was designed for the sensor, and by reducing the internal resistance of the voltage follower circuit, the measurement stability and accuracy were improved. Simulation and experimental results indicate that the sensor can effectively detect electric field variations in a uniformly distributed field and exhibits good linear response in both low-frequency and power-frequency signal measurements, showing great potential for future applications. © 2024 IEEE.

关键词： Capacitor bank

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sensor Ontology Matching With Compact Firework Algorithm

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IEEE sensorS JOURNAL 2024年第20期24卷 33751-33762页

作者： Xue, Xingsi Lin, Jerry Chun-Wei Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Fujian Peoples R China Silesian Tech Univ Dept Distributed Syst & IT Devices PL-44100 Gliwice Poland

sensor ontology provides a standardized and conceptual framework for the Internet of Things (IoTs), but their practical applications are often hampered by the ontology heterogeneity issue, emerging from varying development contexts and semantic discrepancies. sensor ontology matching (SOM) addresses this issue by mapping semantically identical entities within sensor ontologies, whose foundation is the utilization of similarity measure (SM). Although SM can quantify the similarities of entities, the complex nature of entity heterogeneity precludes any single SM from consistently excelling across diverse scenarios, therefore combining different SMs becomes essential to enhance the accuracy of matching results. The swarm intelligence (SI) technique, particularly the firework algorithm (FA), shows promising results in SM combination, but its application in matching sensor ontologies is hampered by efficiency issues. To overcome this limitation, this article proposes an innovative compact FA (cFA) for SOM. First, we present an iterative framework for SM combination to optimize the quality of SOM results. Second, we develop a compact encoding mechanism that can increase the overall efficiency of the SOM. Finally, we design a new fitness function that is able to autonomously gauge individual quality and obviate expert intervention. The experiments use the Benchmark and conference datasets for the ontology alignment evaluation initiative (OAEI) and ten real SOM tasks to evaluate the performance of the designed approach. Comparisons with advanced matching techniques show the effectiveness and the efficiency of the developed method, which consistently achieves high-quality matching results with an average f-measure of 0.80.

关键词： Ontologies sensors Intelligent sensors Optimization sensor systems Accuracy sensor phenomena and characterization Compact firework algorithm (cFA) Internet of Things (IoTs) sensor ontology matching (SOM) similarity measure (SM) combination

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Ultrasensitive Textile Strain Sensing Choker for Diverse Healthcare applications

Ultrasensitive Textile Strain Sensing Choker for Diverse Hea...

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2nd IEEE Biosensors conference (Biosensors)

作者： Yi, Wentian Tang, Chenyu Xu, Muzi Occhipinti, Luigi G. Univ Cambridge Cambridge Graphene Ctr OcchipintiGrp Cambridge England

ISBN: (纸本)9798350395143;9798350395136

We designed a ultrasensitive textile-based strain sensing choker to accurately monitor the slight strain changes caused by activities such as speech and breathing at the throat. The ordered cracks, which are induced by the textile structure, endow the strain sensor with superior sensitivity and repeatability. This sensor can utilize advanced machine learning algorithms to decode signals from speech into corresponding words and sentences for integration into silent speech interface systems, or link signals from sleep to various sleep conditions like sleep apnea for integration into sleep monitoring systems.

关键词： Printed textile electronics crack-based strain sensor machine learning healthcare

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Review of Non-invasive, Wearable Biomedical sensor and Imaging IC

Review of Non-invasive, Wearable Biomedical Sensor and Imagi...

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2024 Biomedical Circuits and systems conference

作者： Jang, Jaeeun Yoo, Hoi-Jun Kwangwoon Univ Sch Semicond Syst Engn Seoul South Korea Korea Adv Inst Sci & Technol Dept Elect Engn Daejeon South Korea

ISBN: (纸本)9798350354966;9798350354959

Technological innovation in biomedical science, driven by semiconductor circuit and system engineering, has enabled faster diagnosis, continuous health monitoring, and advanced treatment approaches. Recent advances in non-invasive, wearable biosensor interfaces and imaging have significantly improved performance and reduced costs, enhancing accessibility to medical technology. These sensors, benefiting from semiconductor technology, offer convenience, low infection risk, and cost-effective solutions for medical monitoring. This paper explores the principles, challenges, and advancements in non-invasive sensor technology, including electrodes, optical elements, and Electrical Impedance Tomography (EIT). The integration of semiconductor technology in these applications is paving the way for personalized medicine and point-of-care solutions, with promising potential to improve patient care and healthcare outcomes.

关键词： Biomedical Diagnosis Electrical Impedance Tomography EIT Electrode Sensitivity Non-invasive Optical sensor Tissue Imaging Wearable

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2nd International conference on advanced Nanomaterials and applications, ICANA 2024

2nd International Conference on Advanced Nanomaterials and A...

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2nd International conference on advanced Nanomaterials and applications, ICANA 2024

ISBN: (纸本)9789819608270

The proceedings contain 10 papers. The special focus in this conference is on advanced Nanomaterials and applications. The topics include: GO/ZnO—Intensified Hybrid Nanomaterial as an Electrochemical sensor for Formaldehyde Detection in Environmental applications;synthesis of 4-Substituted 2,2′;6′,2″-Terpyridine Copper Complexes and Study of Their Anti-cancer Activities;synthesis of Cobalt Complexes and Study of Their Catalytic Activities in Various Organic Transformations;Recent Developments in Doped TMO and TMO-Based Composites for Energy Harvesting and Pollutant Removal systems;recent Progress in Multiferroics and Its Composites;dilute Magnetic Semiconductors and Its applications—An Overview;study of Melting Phenomenon of a Palladium Nanocluster Using Molecular Dynamics Simulations.

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Narrow Space Warning and Slope Control System compatible with ADAS 31

Narrow Space Warning and Slope Control System compatible wit...

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31st IEEE conference on Signal Processing and Communications applications (SIU)

作者： Toy, Ibrahim Yusefi, Abdullah Durdu, Akif Konya Tech Univ Res & Dev Dept Elect & Elect Engn MPG Machinery Prod Grp Inc CoRAC LAB Konya Turkiye

ISBN: (纸本)9798350343557

The number of studies on autonomous vehicle systems is increasing day by day. Autonomous vehicles can perform various tasks without human intervention. However, in the environment where these tasks are performed, there are locations that can pose a danger in terms of width and height. These locations are generally referred to as narrow spaces. The autonomous vehicle must detect these narrow spaces from the front with the sensors on the vehicle to minimize the accident rate. In this study, a narrow space detection algorithm is created by including width detection, height detection, positive and negative obstacle detection in autonomous vehicle algorithms. LiDAR sensor data is utilized in the conducted studies, utilizing a 16-layered, 100-meter range product manufactured by Velodyne. When the width and height measurements obtained from the sensor data did not match the vehicle dimensions, the user is informed. This notification is conveyed to the user as a visual warning message on an interface. In addition, the incline of the hills that the vehicle cannot climb (positive obstacle) and the cliffs that it cannot descend (negative obstacle) were determined by measuring the slope. According to the results of the study, the average error rate is calculated as 2.7% for width measurements, 1.84% for height measurements, and 2.22% for slope measurements for positive and negative obstacle detection. The outputs of this study can also be included in advanced driver assistance systems (ADAS).

关键词： advanced Driver Assistance systems Narrow space detection algorithm Autonomous vehicle LiDAR Negative obstacle Positive obstacle

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An improved efficiency of all-PMOS charge pump circuit 31

An improved efficiency of all-PMOS charge pump circuit

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31st conference on Electronics Circuits and systems

作者： Coustans, Mathieu FHNW Inst Sensor & Elect Windisch Switzerland

ISBN: (纸本)9798350377217;9798350377200

This paper presents an all-PMOS charge-pump cell that enhances efficiency using advanced bulk-bias techniques. Traditional designs struggle with switching losses and threshold voltage effects, especially under low voltage or high-frequency conditions. Our design mitigates these issues by optimizing charge transfer through improved bulk management. The proposed architecture shows significant efficiency gains, validated through theoretical analysis and experimental results, making it a robust solution for efficient DC-DC conversion applications.

关键词： Charge-pump bulk-biasing DC-DC conversion switching losses power management low-power design

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IoT-based automatic road accident detection systems: A review 4

IoT-based automatic road accident detection systems: A revie...

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4th International conference on Soft Computing for Security applications, ICSCSA 2024

作者： Prabu, C.R. Namitha, Kalakunnath Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798331515720

With the increasing number of vehicles on roads, the occurrence of road accidents has become a major concern globally. Automatic road accident detection systems based on Internet of Things (IoT) technologies have emerged as a promising solution to improve emergency response times and reduce the severity of accidents. The review encompasses various aspects including the underlying technologies, sensor networks, data processing algorithms, communication protocols, and system architectures used in these systems. Furthermore, the paper discusses the challenges and limitations of current approaches such as sensor accuracy, system scalability, and real-Time data processing. It also identifies future research directions including the integration of advanced sensor technologies, machine learning algorithms for accident prediction, and the development of standardized communication protocols for interoperability among different systems. To improve road safety, researchers and practitioners can use the ideas to help build IoT-based autonomous road accident detection systems that are more effective and efficient. © 2024 IEEE.

关键词： Interoperability

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