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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

共 9386 条记录，以下是51-60 订阅

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A Comprehensive Review of sensor Fusion Techniques in SLAM: Trends, Challenges and Future Directions

A Comprehensive Review of Sensor Fusion Techniques in SLAM: ...

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AIML-applications for Engineering & Technology (ICAET), international conference on

作者： Veerendra Dhaigude Anagha Kulkarni Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Information Technology Cummins College of Engineering for Women Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Simultaneous Localization and Mapping (SLAM) equips machines with the capability to map and navigate unfamiliar environments autonomously. By employing sensor fusion, SLAM's precision and dependability are significantly improved as data from a variety of sensors are combined. This review delves into the core principles of SLAM, explores diverse methods of sensor fusion, and examines the incorporation of artificial intelligence in SLAM systems. Additionally, it addresses the technical hurdles and environmental factors that affect SLAM's performance. Future research directions are also identified, emphasizing the promising role of interdisciplinary approaches and emerging technologies in enhancing SLAM's development.

关键词： Deep learning Simultaneous localization and mapping Reviews Navigation Autonomous systems sensor fusion Market research Environmental factors Kalman filters Artificial intelligence

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Effective Node Deployment in Wireless sensor Networks Using Reinforcement Learning

Effective Node Deployment in Wireless Sensor Networks Using ...

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international conference on Communication Systems and Network technologies (CSNT)

作者： Rahul Priyadarshi Panduranga Ravi Teja Anish Kumar Vishwakarma Rakesh Ranjan Faculty of Engineering and Technology ITER SOA Bhubaneswar India School of Computer Science UPES Dehradun Uttarakhand India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Wireless sensor Networks (WSNs) are vital for applications like environmental monitoring and smart cities, but effective node deployment remains challenging. Traditional methods often fail in dynamic scenarios. This paper proposes a Reinforcement Learning (RL)-based framework to optimize WSN node deployment, maximizing coverage while minimizing energy use and extending network lifetime. The RL model adapts to environmental changes and varying network conditions, ensuring robust performance in static, dynamic, and high-density environments. Experimental results show the RL approach outperforms conventional methods, achieving better coverage, lower energy consumption, and improved network longevity. The study demonstrates RL’s adaptability and effectiveness in addressing WSN deployment challenges, enabling intelligent, self-optimizing networks for dynamic real-world applications.

关键词： Wireless sensor networks Energy consumption Adaptation models Smart cities Reinforcement learning Energy efficiency Environmental monitoring Optimization

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Deep Learning Utility for Gas/Odor sensor Signature Analysis

Deep Learning Utility for Gas/Odor Sensor Signature Analysis

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Machine Learning and Autonomous Systems (ICMLAS), international conference on

作者： Yashasvi Raut Shiv Nath Chaudhri Department of Computer Science and Engineering Faculty of Engineering and Technology DMIHER (DU) Maharashtra India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Gas/odor sensors are integral components of sensor systems used in diverse applications such as food quality control, environmental monitoring, medical diagnostics, odor profiling, industrial safety, agriculture, explosives detection, wine tasting, pharmaceutical quality control, and toxic gas detection. Traditional approaches in this domain of gas/odor sensing technologies face challenges related to accuracy, cross-sensitivity, and drifted real-time performance. The integration of deep learning techniques with gas sensors has shown promise in overcoming these limitations. Moreover, this amalgamation of gas sensing and deep learning strategies enables accurate identification of gases/odors, handling complex patterns, and leading optimal consumption of resources. In this paper, an overview of advancements in deep learning-enabled gas sensing has been presented that focused on methodologies, sensor types, and applications. This review also highlights the state-of-the-art techniques and identifies gaps for future directions for research.

关键词： Deep learning Accuracy Hydrogen Quality control Real-time systems sensor systems sensors Protection Gas detectors Petroleum

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Analysis of sensor technologies for Structural Health Monitoring in Civil Engineering applications

Analysis of Sensor Technologies for Structural Health Monito...

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3rd IEEE international conference on Automation and Computation, AUTOCOM 2025

作者： Agarwal, Trapty Gandhi, Ayush Mohapatra, Yogomaya Singh, Jagtej Bahri, Dimple Reddy, V. Venkata Ramesh Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Department of Civil Engineering Karnataka Bangalore India Presidency University Sponsored Research Karnataka Bangalore India

ISBN: (纸本)9798331542375

Civil engineering is considered complete with structural health monitoring SHM, a continuous process in which structures are tested for their health and integrity, ensuring they remain safe and reliable. Recent advancements in sensor technologies for SHM have improved the empirical side of structural performance. The advancement of sensor technologies for SHM is largely related to implementing wireless and smart sensors. It is easily fixable and provides real-time information on the strain, temperature, vibration, etc. Wireless and smart sensors can also be deployed in difficult-to-access or non-safe areas, allowing for an increased size of monitored structures. In addition, the emergence of sensor technologies has resulted in smart algorithms and data analytics methods suitable for SHM. Such algorithms process huge amounts of data and detect potential structural problems or anomalies before any expected maintenance intervention. © 2025 IEEE.

关键词： Structural Mechanics

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Analysis of sensor technologies for Structural Health Monitoring in Civil Engineering applications

Analysis of Sensor Technologies for Structural Health Monito...

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Automation and Computation (AUTOCOM), international conference on

作者： Trapty Agarwal Ayush Gandhi Yogomaya Mohapatra Jagtej Singh Dimple Bahri V. Venkata Ramesh Reddy Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India Department of Civil Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Sponsored Research Presidency University Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

关键词： Temperature sensors Wireless communication Temperature measurement Vibrations Wireless sensor networks Real-time systems Maintenance Monitoring Civil engineering Intelligent sensors

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Design, Fabrication, and Characterization of Paper-Based Flexible sensor for Wearable applications

Design, Fabrication, and Characterization of Paper-Based Fle...

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international conference on Computer, Electrical & Communication Engineering (ICCECE)

作者： Raunak Das Madhurima Chattopadhyay Debjyoti Chowdhury Dept. of AEIE Heritage Inst. of Technology Kolkata India

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

This study presents the design, fabrication, and evaluation of a cost-effective paper-based flexible sensor for wearable applications, specifically motion detection. Utilizing filter paper as a substrate, the sensor is coated with graphite for conductivity and enhanced with sodium chloride (NaCl) to boost ionic dissociation and sensitivity. The fabrication process employs low-cost and sustainable materials and methods, yielding a sensor with high responsiveness, repeatability, and durability. Comparative analysis with commercial silicon-based sensors demonstrates the paper sensor’s superior sensitivity to small angular changes, albeit with slightly lower stability. Optimal dimensions of $6 \mathbf{c m} \times 1 \mathrm{~cm}$ are identified by balancing sensitivity and mechanical stability. Integration with a microcontroller facilitates real-time data acquisition, showcasing the potential of assistive devices, gesture recognition, and healthcare monitoring. This work highlights the feasibility of paper-based sensors as accessible alternatives to conventional silicon-based technologies, aligning with environmental sustainability goals, and cost-effectiveness.

关键词： Fabrication Chlorine compounds Sensitivity Flexible printed circuits Graphite Robot sensing systems Stability analysis Biomedical monitoring Sustainable development Testing

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Prospectivity Mapping of Minerals Based on PRISMA Shortwave Infrared Imaging sensor and Machine Learning in the Bhilwara District, India 8th

Prospectivity Mapping of Minerals Based on PRISMA Shortwave ...

引用

8th international conference on Intelligent technologies, ICIT 2023

作者： Agrawal, Neelam Govil, Himanshu Mishra, Gaurav Janghel, Rekh Ram Department of Computer Applications National Institute of Technology Raipur Raipur India Department of Applied Geology National Institute of Technology Raipur Raipur India Department of Information Technology National Institute of Technology Raipur Raipur India

ISBN: (纸本)9789819738588

Spaceborne satellite images offer consistent and frequent information about surface objects, which can be utilized to explore mineral resources over a vast geographical area. To map valuable mineral resources, narrowband hyperspectral images are more efficient and accurate than broadband multispectral images. Moreover, machine learning (ML) has received remarkable attention in various fields. The spaceborne hyperspectral remote sensing and ML can improve and automate the mineral prospectivity mapping process. The present study is an attempt to map the prospectivity of hydrothermally altered and weathered minerals using a hyperspectral image captured by the recently launched PRISMA spaceborne hyperspectral sensor and various ML algorithms. The study was performed over the area of Jahazpur, Bhilwara district, India (75° 06′ 23.17′′ E, 25° 25′ 23.37′′ N). To generate the mineral distribution map for various mineral deposits, the Spectral Angle Mapper (SAM) algorithm was employed. The prepared dataset contained 173 spectral features;therefore, principal component analysis (PCA) was applied to reduce the dimension of the dataset. The generated mineral distribution map was verified through the validation survey in the study area. Various supervised classification models were developed, which were evaluated using the measures such as overall accuracy, precision, recall, F1-score, and kappa coefficient. The results revealed that the SVM model outperformed among all the classification models in terms of all the measures and it achieves overall accuracy of 99.38%. In general, the employed PRISMA hyperspectral dataset has good application prospects in the mapping of hydrothermally altered and weathered minerals using machine learning in a mountainous area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mineral exploration

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Plasmonic sensor with Interconnected Dual Ring Resonator for Refractive Index Sensing

Plasmonic Sensor with Interconnected Dual Ring Resonator for...

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Device Intelligence, Computing and Communication technologies, (DICCT), international conference on

作者： Rahul Pandey Kamal Kishor Choure Manisha Prajapat Ghanshyam Singh Rajendra Mitharwal Department of ECE Malviya National Institute of Technology Jaipur Jaipur India Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

This study proposes a highly sensitive plasmonic sensor utilizing a Metal-Insulator-Metal (MIM) waveguide incorporating a stub-connected circular dual-ring resonator. The sensor consists of two rectangular waveguides coupled with a stub-connected double ring resonator, where the electromagnetic (EM) wave appears at the output port only when resonance occurs within the resonator at a specific wavelength. The sensor's performance is assessed through computational modeling using the Finite-Difference Time-Domain (FDTD) technique. The results reveal four distinct sensitivity peaks across the visible and near-infrared wavelength ranges. By refining geometrical parameters such as the radius of the ring, the optimized sensor achieves a peak sensitivity of 2063 nm/RIU around peak 4 in the near-infrared region. It's remarkable ability to identify even the tiniest shift in refractive index makes it highly effective for biosensing applications.

关键词： Sensitivity Rectangular waveguides Refractive index Plasmons Resonance sensors Biosensors Time-domain analysis Optical ring resonators Finite difference methods

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Electrode Polarization-Based sensor for Real-Time Monitoring of Salt and Sugar Concentrations in Beverages

Electrode Polarization-Based Sensor for Real-Time Monitoring...

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Device Intelligence, Computing and Communication technologies, (DICCT), international conference on

作者： Anamika Lata Praveen Maurya M.K. Singh School of Electronics Engineering (VIT AP University) India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

An electrode polarization impedance-based sensor was developed due to the increasing demand for accurate and non-invasive methods to monitor the level of sugar and salt in drinks. This sensor is based on the description of a reliable process of using a four-electrode system for measuring the levels of sugar and salt in various drinks. There are two pairs of electrodes in the system: the inner pair senses voltage, and the outer pair delivers a regulated AC signal. Ionic (salt) and non-ionic (sugar) molecules in the solution both affect the electrode polarization impedance (Z P ), and changes in voltage mirror these effects. As per experimental data, there exists a clear inverse relationship between the output voltage and sugar and salt content, which makes this method suitable for real-time monitoring of beverage composition. Sensitivity analysis of the sensor offers similar results for various beverages with increased sensitivity observed at increasing salt concentrations. The proposed method is a good tool for industry and research applications, as it presents a non-invasive, reliable, and cheap alternative to food safety management, health monitoring, and the soft drink industry.

关键词： Electrodes Salt Voltage fluctuations Sensitivity analysis Sugar industry Real-time systems Impedance Voltage control Monitoring Sports

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UWSN: A Novel Artificial Intelligence (AI) enabled Scheme to Improve Security and Energy Efficiency over Underwater Wireless sensor Networks

UWSN: A Novel Artificial Intelligence (AI) enabled Scheme to...

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Advances in Electrical, Computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： P. Shyamala Bharathi M Jaya Bharatha Reddy Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Underwater Wireless sensor Networks (UWSNs) are critical for monitoring and managing marine environments, supporting applications in environmental science, defense, and resource exploration. This study presents an innovative AIenabled scheme for improving security and energy efficiency in Underwater Wireless sensor Networks (UWSNs). By incorporating artificial intelligence, the proposed AI-UWSN protocol dynamically adapts to environmental and network conditions, enhancing key performance metrics like energy consumption, packet delivery ratio (PDR), latency, and network lifetime. The AI-UWSN achieved an average energy consumption of 146J, which is 24% lower than conventional protocols, extending the network lifetime to 1067 hours, compared to 722 hours in existing methods. Additionally, the protocol's intelligent routing increased PDR to 89%, significantly reducing data loss, and maintained an average latency of 108ms, 15% lower than alternative protocols. These improvements result from AI-based routing and clustering strategies, which optimize data aggregation and power usage, extending the network's functionality even in high-density, high-traffic environments.

关键词： Wireless sensor networks Energy consumption Protocols Environmental science Data aggregation Routing Energy efficiency Security Artificial intelligence Monitoring

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