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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications IV"

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advanced Integration of 3D Optomechanical sensor Microsystems with Optical Fibers

Advanced Integration of 3D Optomechanical Sensor Microsystem...

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2024 IEEE sensors conference

作者： Chandrahalim, Hengky Williams, Jeremiah C. Air Force Inst Technol Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9798350363524;9798350363517

The ever-increasing demand for affordable, compact, and integrated sensors necessitates innovations that outperform traditional, bulkier counterparts. This paper introduces an advanced integration of 3D optomechanical sensor microsystems with optical fibers, using a two-photon nanomachining process. This technique enables the fabrication of complex 3D structures, including dynamic and movable features, unattainable through conventional photolithography. We present sensor microsystems incorporating resonant and non-resonant cavities, demonstrating exceptional sensitivity and operational range. The resonant microsensors offer heightened sensitivity to environmental conditions, while the non-resonant counterparts use rotating reflective microblades for precise flow sensing. Utilizing optical fiber as the substrate, these sensors transmit detected information in real-time to remote locations with minimal loss, eliminating the need for additional packaging, amplifiers, signal processing, and data transmission components. This innovative integration promises a new generation of highly sensitive, compact, and versatile sensor systems, ideal for contemporary engineering applications.

关键词： 3D optomechanical sensors optical fiber sensors optical fiber integration 3D microfabrication two-photon nanomachining resonant and non-resonant sensors

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A 32×32 SPAD LiDAR sensor with In-pixel Spatial-temporal Coincidence and Per-SPAD Pulse Delay for Resolution-lossless Imaging

A 32×32 SPAD LiDAR Sensor with In-pixel Spatial-temporal Co...

引用

2024 IEEE Asian Solid-State Circuits conference, A-SSCC 2024

作者： Chen, Bu Huang, Zhangcheng Wang, Jingyi Shang, Hongyang Lv, Hankun Liu, Qi Liu, Ming State Key Lab of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University China

ISBN: (纸本)9798350376326

Single-photon Avalanche Diode (SPAD)-based LiDAR technology finds significant applications in advanced driver assistance systems, etc. Extracting distance information necessitates creating a histogram from enormous frames to filter out the overwhelming background light (BGL) data. As the formats of SPAD pixel arrays scaling up [1], the processing, storage, and transmission of extensive data result in ultra-high power consumption and increased layout area. In order to reduce BGL, previous studies [2][3] [4] have leveraged spatial coincidence and histograms in pixels, and [5] utilized external double pulses to enhance the signal-to-noise ratio. However, a significant amount of data still needs to be processed within the sensor. To address these challenges, this paper presents a 32 × 32 SPAD LiDAR sensor that incorporates in-pixel spatial-temporal coincidence to effectively compress random background light and a per-SPAD pulse delay method to realize resolution-lossless imaging. This approach achieves an impressive 98.3% compression rate of background light under 100 klux illumination while maintaining a low power consumption of 14.6 μW per pixel. © 2024 IEEE.

关键词： advanced driver assistance systems

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A review on recent techniques developed for energy conservation in Wireless sensor Networks

A review on recent techniques developed for energy conservat...

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2023 International conference on Intelligent systems, advanced Computing and Communication, ISACC 2023

作者： Basumatary, Habila Chowdhuri, Rajib Deb Barma, Mrinal Kanti Tezpur University Department of Computer Science and Engineering Assam India National Institute of Technology Department of Computer Science and Engineering Agartala India

ISBN: (纸本)9798350399387

In modern days, with the fastest growing technology trends, the benefits of Wireless sensor Networks (WSNs) are also increasing rapidly. In these networks, very small-sized wireless sensor nodes are used widely which are capable of sensing and doing computations. These sensor nodes are resource-limited in nature i.e., they have limited storage capacity, power supply, computation capability, bandwidth, etc. WSNs are mostly used in outdoor application areas like environmental monitoring, land mines detections or different military applications where the power supply to the sensor nodes does the major role. In these applications, without any external power supply, the sensor nodes run the whole network by collecting data from its surroundings and also communicate these data to the end-user. Hence, conserving energy for the sensor nodes is one of the most challenging tasks in WSNs. In this paper, we have done detailed study on the existing literature which are proposed with the objective to improve the energy efficiency issue in WSNs. Here, we have selectively highlighted some of the recently proposed methodologies to understand the present research scenario. We have also shown comparative analysis on the techniques and tools which are used to propose these works and their variation of the results are discussed accordingly. © 2023 IEEE.

关键词： Energy efficiency

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BIBLIOMETRIC REVIEW OF SMART sensor FOR HEALTH MONITORING

BIBLIOMETRIC REVIEW OF SMART SENSOR FOR HEALTH MONITORING

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International conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Halim, Christian V. Marinah, Murti Shafira, Dinda A.I. Dwiyantara, Muhammad Y. Abadi, Imam Department of Physics Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9781837242689

Smart sensors and medical health technologies are becoming increasingly popular due to their potential for real-time, noninvasive health monitoring and diagnostics. With the integration of Artificial Intelligence (AI), these devices can track vital signs and important biomarkers, supporting the management of chronic diseases. This study employs bibliometric analysis using tools like VOSviewer to map research trends in this domain, identifying collaborations, emerging keywords, and contributions from institutions and countries. Findings indicate a significant increase in publications and citations, especially after 2010, highlighting influential journals such as IEEE sensors Journal. The primary focus is on health monitoring applications and advancements in sensor technology, with an increasing use of terms like "machine learning" and "data analytics." These findings provide insights into future research directions and technological innovations that impact medical health applications. It is recommended that future development integrate advanced data processing techniques and apply sensors in infrastructure and smart city environments, aiming to create systems that are more responsive, efficient, and sustainable. © The Institution of Engineering & Technology 2024.

关键词： Electronic health record

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Machine Learning for sensor-Based Handwritten Character Recognition: A Brief Survey 21st

Machine Learning for Sensor-Based Handwritten Character Reco...

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21st International conference on Distributed Computing and Intelligent Technology

作者： Singh, Shashank Kumar Chaturvedi, Amrita IIT BHU Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9783031814037;9783031814044

Handwriting recognition technologies have evolved significantly, with recent advancements incorporating wearable devices such as smartpens, smartwatches, and smartphones to capture motion and gesture data. This paper reviews various efficient handwriting recognition models that utilize inertial sensors, visual sensors, EMG sensors, and acoustic and Wi-Fi signals. Inertial sensor-based approaches often use accelerometers and gyroscopes to collect three-dimensional data during handwriting, with models achieving high accuracy in recognizing digits and alphabets. Visual sensor-based techniques, leveraging cameras and image processing, have been fundamental in developing Optical Character Recognition (OCR), further enhanced by deep learning algorithms. EMG sensors have been explored for their potential to capture muscle activity for gesture recognition. At the same time, acoustic and WiFi signal-based methods offer innovative ways to recognize handwriting through sound and signal variation. Despite the progress, challenges such as sensor drift, data generalization, and computational requirements persist. Integrating multi-modal sensors and advanced machine learning techniques holds promise for overcoming these limitations and improving the accuracy and usability of handwriting recognition systems across diverse applications.

关键词： Inertial sensor Machine Learning Visual sensors

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Application of big data analysis in improving the efficiency of sensor reliability testing

Application of big data analysis in improving the efficiency...

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2024 International conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Wan, Wangjun Zhao, Minghua Song, Weijie Dong, Chunfa Ling, Zhixiang State Grid Jinan Power Supply Company Shandong Jinan250000 China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

In modern technological applications, the reliability of sensors plays a crucial role in ensuring the proper functioning of systems. Therefore, sensor reliability testing has become an important aspect of quality control and system maintenance. However, traditional testing methods often face challenges in terms of efficiency and accuracy, especially when dealing with large-scale sensor data. In order to address these challenges, this paper proposes an innovative approach to improving sensor reliability testing efficiency by leveraging big data analytics, particularly through the application of neural networks. The method involves extracting features from different scales and abstraction levels using a multi-scale neural network architecture. Subsequently, the extracted detailed information is fused with high-level semantic features to minimize information loss, enhance feature utilization, and obtain advanced features, thereby improving the performance of the network. Additionally, a spatial attention module is introduced into the network to extract critical information and enhance overall network performance, effectively detecting sensor faults. Through comprehensive experiments conducted on real-world sensor data, the effectiveness and efficiency of the proposed method have been demonstrated, highlighting its significant potential in enhancing sensor reliability testing processes. This research not only contributes to the advancement of sensor reliability testing but also underscores the broader potential of big data analytics in improving the performance and reliability of complex technological systems. © 2025 SPIE.

关键词： Data reliability

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A Hybrid Optimization Strategy for k-Coverage Maximization in Wireless sensor and IoT Networks 3

A Hybrid Optimization Strategy for k-Coverage Maximization i...

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3rd International conference on Intelligent systems, advanced Computing, and Communication, ISACC 2025

作者： Manna, Prithwish Majumder, Sudipta Singh, N. Hemarjit Dibrugarh University Dept. of CSE DUIET Assam Dibrugarh India Dibrugarh University Dept. of ECE DUIET Assam Dibrugarh India

ISBN: (纸本)9798331523893

In this paper, we propose a combination of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to create a hybrid optimization technique which meets k-coverage criteria in Wireless sensor Network (WSN) and Internet of Things (IoT). The goal of this approach is to increase the coverage area alongside minimizing the deployment cost of the sensors. Another aim is to reduce the power consumption. This technique is helpful to determine the optimal position of the sensors. It helps to ensure that each target point in the network is getting the coverage of at least k sensors. In this way we can enhance the reliability and robustness of the network. From experimental results, we can conclude that with optimal sensor utilization and minimized redundancy, our proposed approach achieves 97.14% coverage ratio with k-coverage equals 3. According to performance metrics, it is clear that there is consistent energy efficiency through the cycles. The approach converges in less than 3 second. So, this approach is applicable for real time applications. It is a hybrid metaheuristic approach which is very efficient in managing various challenges associated with sensor deployment. From this approach we can get solutions of coverage enhancement, energy efficiency and improved sensor utilization. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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Real-Time Indoor Target Tracking Using IoT and Wireless sensor Networks 4

Real-Time Indoor Target Tracking Using IoT and Wireless Sens...

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4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Katakwar, Sachin R. Jajulwar, Kapil K. Tadas, Surekha M. Tech Communication Engineering G H Raisoni College of Engineering Nagpur India G H Raisoni College of Engineering Department of Electronics and Telecommunication Engineering Nagpur India

ISBN: (纸本)9798331523923

Indoor target tracking presents significant challenges across various fields such as security surveillance, industrial automation, and healthcare. This research paper outlines the design and implementation of a reliable direction monitoring system aimed at achieving accurate indoor target tracking using IoT and wireless sensor networks. By utilizing advanced sensor technologies and sophisticated data processing algorithms, the proposed system enables real-time monitoring and precise localization of targets within indoor spaces. The combination of IoT devices and wireless sensor networks facilitates effective data collection, analysis, and visualization, thereby improving the overall performance of the monitoring system. The results indicate that the developed system is effective in accurately tracking and localizing targets, fulfilling the essential requirement for efficient indoor direction monitoring solutions. The paper concludes with a discussion on the practical implications and potential applications of this system, emphasizing its importance in enhancing indoor target localization across diverse sectors. © 2025 IEEE.

关键词： Indoor positioning systems

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Energy Efficiency Optimization of Wireless sensor Networks with K-Means Integration 7

Energy Efficiency Optimization of Wireless Sensor Networks w...

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7th International conference on advanced Communication Technologies and Networking, CommNet 2024

作者： Hilmani, Adil Sabri, Yassine Maizate, Abderrahim Aouad, Siham Koundi, Mohammed Ayoub, Fouad Mohammed v University LASTIMI High School of Technology Salé Rabat Morocco FacuIty of Sciences Agadir Morocco University Hassan II RITM ESTC/CED-ENSEM Casablanca Morocco Mohamed v University Smart Systems Laboratory ENSIAS Rabat Morocco Ibn Tofail University ASE-Lab ENSA Kenitra Morocco ERATIC Team LaREAMI Lab CRMEF-K Kenitra Morocco

ISBN: (纸本)9798350367027

In wireless sensor networks (WSNs), optimizing energy consumption and ensuring efficient data transmission are crucial for network longevity and performance. This paper introduces an enhanced clustering technique for wireless sensor networks that aims to extend network lifetime and ensure reliable data delivery. Instead of regular K-Means clustering, we integrate the Silhouette score method to evaluate cluster quality and decide the optimal number of clusters. This improves how nodes are grouped together in the network. Additionally, we strategically select routing paths from cluster heads to the base station that minimize energy drainage. Comprehensive simulations show our dual optimization approach outperforms standard K-Means in terms of energy efficiency, stable network organization and effective data transmission and overall, the proposed improvements to clustering and routing significantly advance energy-constrained wireless sensor networks toward more sustainable and dependable real-world applications. © 2024 IEEE.

关键词： Energy efficiency K-Means clustering Power consumption Routing protocol Silhouette Score Wireless sensor network

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Optimized Routing protocol for Enhanced Quality of Service in 6G Wireless sensor Networks 2

Optimized Routing protocol for Enhanced Quality of Service i...

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2nd IEEE International conference on Networking and Communications, ICNWC 2024

作者： Shanmathi, S. Kumar, S. Praveen Lingaraja, D. Aravind, T. Ramya, S. Ram, G. Dinesh Saveetha Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350365269

In order to increase Quality of Service (QoS) in 6G Wireless sensor Networks (WSNs), QoS-aware routing protocols have been proposed as a solution in the study. Existing systems have limitations such as inadequate performance and insufficient support for the different requirements of upcoming 6G applications. To overcome these restrictions, the proposed system employs novel routing protocols designed specifically for 6G WSNs. The protocols efficiently manage network resource use, minimize latency, and improve reliability by utilizing advanced algorithms and adaptive mechanisms. The outcomes of comprehensive experimental research show considerable increases in QoS measures including throughput, packet delivery ratio (PDR), and end-to-end latency (ETL). The results illustrate the usefulness of the proposed QoS-aware routing protocols, establishing them as critical enablers for the smooth integration of 6G WSNs into a variety of applications encompassing from smart cities to industrial automation. © 2024 IEEE.

关键词： Wireless sensor networks

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