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

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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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Enhanced Model Predictive Controller Utilizing Kalman Filter for Dual Active Bridge Converter in More Electric Aircraft 27

Enhanced Model Predictive Controller Utilizing Kalman Filter...

引用

27th International conference on Electrical Machines and systems, ICEMS 2024

作者： Wu, Han Li, Bingqiang Wang, Dongheng Riaz, Saleem Deng, Yuening School of Automation Northwestern Polytechnical University Xi'an710129 China

ISBN: (纸本)9784886864406

Dual Active Bridge (DAB) converters, widely employed in more electric aircraft (MEA) systems, face considerable stability challenges due to uncertain loads and external disturbances. This paper presents an advanced Model Predictive Controller (MPC) integrated with a Kalman Filter (KF) to address these issues. The proposed control strategy leverages the KF for accurate state and disturbance estimation, combined with an enhanced Euler's method to improve the discrete-time modeling of the DAB converter. Simulation results demonstrate the efficacy of the proposed approach in stabilizing DAB systems and enhancing their dynamic performance under various operational conditions, highlighting its potential for improving control robustness and system reliability in MEA applications. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Kalman filters

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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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Sun-Powered Tactical Uniforms for Soliders in Military applications 10

Sun-Powered Tactical Uniforms for Soliders in Military Appli...

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10th International conference on advanced Computing and Communication systems, ICACCS 2024

作者： Anila, Chowdam Ashokkumar, N. Vittan, Eduru Joel Chowdary, Bheemaneni Uma Maheswara Subramani, Dhanya Sree Bala Balamanikandan, A. Electronics and Communication Engineering Andra Pradesh Tirupati517102 India

ISBN: (纸本)9798350384369

This endeavor presents an innovative Solar-Powered Tactical Uniform for Military use, incorporating Arduino technology along with an array of sensors and communication modules. The configuration includes an Arduino ATmega16a microcontroller, LCD display, a 70x70 solar panel, a 12V battery, a heart rate sensor, a temperature sensor, dual relays, a CPU fan, a Peltier module, a DHT11 humidity and temperature sensor, GPS, a GSM module, and push-button switches. The renewable energy captured by the solar panel is utilized to recharge the 12V battery, ensuring a constant power supply for the electronic components of the uniform. Real-time data on the LCD display is derived from the soldier's vital signs, which are monitored by the heart rate and temperature sensors. To improve soldier comfort, the Peltier module actively regulates temperature. During crucial scenarios, the system initiates the cooling process by activating the CPU fan and engages the GPS and GSM modules for both location tracking and communication purposes. Manual control is facilitated through push-button switches. This intelligent E-uniform seamlessly integrates energy-efficient features, health monitoring, and communication capabilities, showcasing its ability to improve soldier well-being and enhance situational awareness in field operations. © 2024 IEEE.

关键词： Liquid crystal displays

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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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Fine-tuning of LLMs for Hexie Management Theory 24

Fine-tuning of LLMs for HeXie Management Theory

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6th International conference on Pattern Recognition and Intelligent systems, PRIS 2024

作者： Tang, Lisirui Wang, Chengyu Li, Gangmin Liu, Peng School of Artificial Intelligence and Advanced Computing Xi'an Jiaotong-Liverpool University China HeXie Management Research Centre College of Industry-Entrepreneurs Xi'an Jiaotong-Liverpool University China

ISBN: (纸本)9798400718250

Hexie Management Theory (HXMT) has been used in many applications. Those applications have demonstrated the effectiveness of the theory in responding to management challenges by integrating oriental and occidental wisdom. With its adoption's complexity, dynamics, and flexibility, a revolutionary method needs to be developed to simplify it more broadly. Large Language Models (LLMs) have shown their compelling ability to generate human-like content with their chat-based paradigm. Many specifically trained LLMs have demonstrated success in their dedicated application domains. This paper reports the study of fine-tuning LLMs using a specialized dataset derived from the Hexie management theory. Two models were built on Baidu's Qianfan platform and were adapted for Chinese text. Four criteria were used to evaluate the performances. This study provides an example of fine-tuning LLMs for a Chinese text-based specific theory and building a domain-specific intelligent agent using LLMs or HXMT, which is available at https://***/chat/ © 2024 ACM.

关键词： Chatbots

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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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