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

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advanced Modeling of Sodium-Ion Batteries for Electric Vehicles: Enabling Wireless Communication and Intelligent Transportation systems

Advanced Modeling of Sodium-Ion Batteries for Electric Vehic...

引用

Wireless Africa conference (WAC)

作者： Khanyisile Masemola Cuthbert Nyamupangedengu David G. Dorrell School of Electrical and Information Engineering University of the Witwatersrand Johannesburg South Africa Department of Mechanical & Material Engineering University of Turku Turku Finland

ISBN: (数字)9798331517588

ISBN: (纸本)9798331517595

Sodium-ion batteries (SIBs) have emerged as a viable substitute for lithium-ion batteries (LIBs) in electric vehicles (EVs) due to the growing need for sustainable energy solutions. A comprehensive modeling framework for SIBs designed especially for electric vehicle applications is presented in this paper, with a focus on how these batteries integrate with wireless communication and intelligent transportation systems (ITS). The thermal and electrochemical models of SIBs, their possible use in vehicle-to-everything (V2X) systems, and the wireless state-of-charge (SoC) monitoring via real-time communication protocols are investigated. Simulation results demonstrated the efficiency of SIBs in vehicular applications, their compatibility with wireless data transfer protocols, and their contribution to energy optimization in ITS. The paper concludes with insights into the future of SIBs in EVs and wireless transportation ecosystems.

关键词： Wireless sensor networks Protocols Simulation Transportation Real-time systems Batteries Dedicated short range communication Vehicle-to-everything Optimization Testing

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Leveraging Machine Learning Models for Proactive Disaster Forecasting

Leveraging Machine Learning Models for Proactive Disaster Fo...

引用

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

作者： Daimi Syed Affan Askari Arslaan Ahmed Ahmed Syed Maaz Iqbal Asma Computer Science and Engineering Muffakham Jah College of Engineering and Technology Hyderabad India Electronics and Communication Engineering Deccan College of Engineering and Technology Hyderabad India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

The increasing frequency and intensity of natural disasters, such as earthquakes, tsunamis, floods, and forest fires, necessitate the development of advanced early warning systems. Current disaster prediction systems are hampered by limitations in sensor technology, which is often expensive and primarily effective for large-scale disasters. This project aims to enhance disaster prediction accuracy and timeliness by utilizing real-time data and advanced machine learning algorithms, including XGBoost, Voting classifier, and Random Forest classifier. Additionally, recognizing the long-term health impacts of poor air quality, the project extends its scope to predict the Air Quality Index (AQI). The project seeks to enable proactive risk management and effective disaster response by integrating real-time environmental data and machine learning models. We aim to improve proactive risk management and disaster response by employing real-time data. The outcomes of this project promise significant advancements in disaster preparedness, ultimately safeguarding human lives and infrastructure.

关键词： Disasters Forestry Air quality Tsunami Real-time systems Risk management Indexes Floods Forecasting Random forests

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IoT based Real Time and Remote Fuel Tank and CNG Gas Tank Monitoring System

IoT based Real Time and Remote Fuel Tank and CNG Gas Tank Mo...

引用

Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： Arulkarthick E K Srivarshini S Suvathi K Yazhini S Department Of ECE Nandha Engineering College (Autonomous) Erode India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Efficient and safe monitoring of fuel and gas levels is critical in modern systems, particularly for vehicles and industrial applications. This project, titled "Fuel and Gas Level Monitoring," introduces an advanced IoT-enabled system that tracks fuel and Compressed Natural Gas (CNG) levels in real-time. By utilizing a combination of sensors—including a level sensor, pressure sensor, and gas sensor— integrated with an Arduino microcontroller, the system ensures accurate measurements and robust safety features. The primary objectives are twofold: real-time monitoring to prevent unexpected shortages and optimize refueling schedules, and enhanced safety by detecting gas leaks or abnormal pressure levels to mitigate potential hazards. Data from the sensors is displayed on an LCD for local monitoring and uploaded to the cloud via Wi-Fi for remote access and analytics. Alerts, both visual and audible, are triggered through the LCD and buzzer for immediate attention in case of critical *** to existing systems that rely on basic fuel-level tracking and limited connectivity, this proposed solution incorporates IoT capabilities for seamless cloud integration, making it more reliable and scalable. It leverages wireless communication for real- time data accessibility, enhancing operational efficiency and safety standards. This innovative system has significant implications for ensuring safety, efficiency, and proactive maintenance in fuel and gas monitoring applications.

关键词： Wireless communication Cloud computing Schedules Fuel storage Real-time systems Liquid crystal displays Hazards Fuels Monitoring Wireless fidelity

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Reinforcement Learning for Mobile Robot's Environment Exploration

Reinforcement Learning for Mobile Robot's Environment Explor...

引用

Robotics and Technologies for Industrial Automation (ROBOTHIA), IEEE International conference on

作者： Saif Alahdal Nasr Abdalmanan Kamarulzaman Kamarudin Muhammad Aizat Abu Bakar Mohd Rizal Manan Ahmad Shakaff Ali Yeon Syed Muhammad Mamduh Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Arau Malaysia Center of Excellence for Advanced Sensor Technology Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Arau Malaysia Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Perlis Malaysia Center of Excellence for Advanced Sensor Technology Universiti Malaysia Perlis Arau Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

The field of mobile robotics has become increasingly significant in today's technology-driven world, with applications ranging from autonomous vehicles to automated delivery systems. This project aims to enhance the capabilities of mobile robots in navigating and exploring unfamiliar environments by developing and implementing a Reinforcement Learning (RL) model. The core objective is to enable these robots to autonomously explore, navigate, and adapt to new surroundings efficiently. By integrating the RL model into a mobile robot using the Robot Operating System (ROS), the project evaluates the system's efficiency through comprehensive ground experiments. The research compares the RL-based approach with established exploration methods, emphasizing the effectiveness of the Value Iteration algorithm, a dynamic programming algorithm for Markov Decision Processes (MDPs). Controlled experiments conducted in a 6×3 meter flat space with static obstacles and a 2D lidar sensor provide valuable insights into the RL model's performance and potential real-world applications. The findings highlight the advantages of the Value Iteration algorithm over traditional exploration methods, demonstrating its potential for improving autonomous robotic navigation and exploration.

关键词： Adaptation models Accuracy Service robots Heuristic algorithms Reinforcement learning Robot sensing systems Robustness Dynamic programming Mobile robots Robots

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A Self-Assembled Flexible Strain and Temperature sensor based on the Microstructure of Pyramids with High Elasticity, Temperature Sensitivity and Wide Range

A Self-Assembled Flexible Strain and Temperature Sensor base...

引用

IEEE International conference on Micro Electro Mechanical systems

作者： Yangtao Yu Bo Yan Wenbo Cui Mengqiu Li Chenyuan Li Faheng Zang Zhuoqing Yang National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong University Shanghai China Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

Polymers have been extensively studied in the field of flexible sensors for wearable electronics. However, polymer-based flexible sensors still face great challenges in terms of sensitivity, sensing range and stretchable properties. This paper reports a novel self-assembled flexible strain and temperature sensor, constructed from NiO molecular spheres assembled between MXene flakes. This sensor exhibits exceptional temperature sensitivity, with a sensitivity up to -15.11%°C −1 . It operates a broad temperature range(-20~60°C) and boasts a high measurement gauge factor(GF) of 6.57, along with a significant elongation at break exceeding 572%. Additionally, the sensor demonstrates an ultrahigh tensile strength of over 45 MPa. The microstructure of the sensor, featuring pyramidal formations, facilitates rapid testing capabilities. Furtherly, breathing cycle test under 0°C was performed, showing robust reliability. Furthermore, an array sensing circuit has been developed and designed to precisely measure spatial temperature distributions, enhancing utility of the sensor in various applications.

关键词： Temperature sensors Temperature measurement Temperature distribution Sensitivity sensor systems sensors Microstructure Wearable sensors sensor arrays Strain

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Nanostructure-Based Highly Sensitive and Reliable Piezo-Transmittance Strain sensor and Integrated System

Nanostructure-Based Highly Sensitive and Reliable Piezo-Tran...

引用

IEEE International conference on Micro Electro Mechanical systems

作者： Myung-Kun Chung Su-Min Jeon Jae-Soon Yang Jae-Young Yoo Min-Uk Kim Beom-Jun Kim Tae-Yeon Lee Min-Seung Jo Jun-Bo Yoon School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan University (SKKU) Republic of Korea Center for Bio-Integrated Electronics Northwestern University Evanston IL USA

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

Advancements in human-machine interaction, health monitoring, and robotics have led to increasing demand for reliable strain sensors. Of the various flexible sensors, piezo-transmittance strain sensors adjust their optical transmittance in response to strain and can overcome limitations seen in other sensor types. However, current piezo-transmittance strain sensors face challenges related to controllability and applicability, as well as constraints from bulky designs and complex wired connections. This paper reports a highly sensitive, reliable, and mechanically durable piezo-transmittance strain sensor that addresses these challenges. In addition, we propose a simple, wireless integrated sensor system that eliminates the need for bulky and complex wiring, offering a practical solution for human motion detection applications.

关键词： Wireless communication Micromechanical devices Human computer interaction Wireless sensor networks Materials reliability Capacitive sensors sensor systems Optical sensors Monitoring Strain

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Machine Learning-Enhanced Dual Axis Solar Tracking with Weather Monitoring for Rural Electrification

Machine Learning-Enhanced Dual Axis Solar Tracking with Weat...

引用

advanced Computing Technologies (ICoACT), International conference on

作者： Logesh S Jeevashree J Arun Kumar P Jeevitha Kandasamy Jaisiva S Harish R Electrical and Electronics Engineering Sri Krishna College of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

The proposed dual-axis solar tracking system integrates real-time weather monitoring and machine learning to enhance solar energy efficiency. Machine learning algorithms analyze historical weather data alongside real-time sensor readings, which is crucial for optimizing solar energy capture, as demonstrated in various studies on solar tracking systems. The integration of a mobile application interface allows users to access real-time data and receive alerts, facilitating immediate adjustments to the system settings. This aligns with advancements in remote monitoring technologies, such as those used in microalgal productivity prediction, which leverage real-time sensor data for operational forecasting. Furthermore, the use of the Blynk IoT platform for remote control enhances user engagement and system responsiveness, reflecting a growing trend in smart energy management solutions. Overall, this project exemplifies the convergence of renewable energy technology, machine learning, and IoT, promising improved operational reliability and energy efficiency.

关键词： Renewable energy sources Machine learning Solar energy Solar tracking Market research Real-time systems Energy efficiency Mobile applications Remote monitoring Meteorology

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Interactive Effects of Water Molecules Across A Suspended Double-Layer Graphene with Electro-Modulation

Interactive Effects of Water Molecules Across A Suspended Do...

引用

IEEE International conference on Micro Electro Mechanical systems

作者： Yu-Xuan Lu Wei-Yu Long Cheng-Yu Lin Chih-Ting Lin Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Graduate School of Advanced Technology National Taiwan University Taipei Taiwan

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

Numerous graphene-based applications correspond with the graphene-water interface. However, limited researches focus on the impact of water molecules across the graphene interface in mechanistic perspective. This work first reports experimental investigations of surface water molecular configuration and water-water interaction across double-layer suspended graphene. It is achieved by carrier transportation measurement of suspended graphene in water environment with electro-modulation. This investigation shows the relationship between interfacial molecular arrangement and electrical properties of the graphene-water interface. It also reveals the fundamental mechanisms of conductivity improvement and highlights the potential for graphene-based applications in aqueous environments.

关键词： Water Micromechanical devices Mechanical sensors Graphene Transportation Interference Logic gates sensor systems Mechanical factors Transistors

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Research on Intelligent Early Fire Warning System Using Adaptive Neuro-Fuzzy Inference System in Green Seaport

Research on Intelligent Early Fire Warning System Using Adap...

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Smart systems for applications in Electrical Sciences (ICSSES), International conference on

作者： Thach Nguyen Dinh Hung Nguyen Van Tuan Dinh Anh Faculty of Navigation Vietnam Maritime University Hai Phong Vietnam Faculty of Electrical - Electronics Engineering Vietnam Maritime University Hai Phong Vietnam

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

Transportation and storage in warehouses and seaports are increasingly popular and have increased sharply in recent years. Strict fire and explosion prevention requirements must be met with the diversity of goods, incredibly flammable and explosive goods during transportation. Therefore, fire and explosion monitoring and early warning systems in these areas are increasingly developed with innovative technology and artificial intelligence applied in general alarm systems. This paper proposes and tests an early warning system for fire and explosion at seaports based on advanced fire alarm technology. Traditional addressable fire alarm systems integrating stations for collecting real-time gas concentration quality are being studied. At the same time, an early warning system for fire and explosion is built based on the Adaptive Neuro-Fuzzy Interference System (ANFIS) model and data processing algorithms from fire alarm cabinets. The system results were tested in the laboratory and deployed in practice, reaching 92%, and they strongly supported fire prevention and fighting at smart seaports in Vietnam.

关键词： Adaptive systems Prevention and mitigation Interference Alarm systems Seaports Smart systems Real-time systems sensor systems Artificial intelligence Monitoring

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Comparative Analysis of Power Consumption in Electric and Autonomous Vehicles

Comparative Analysis of Power Consumption in Electric and Au...

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Mechanical Engineering and Robotics Research (ICMERR), International conference on

作者： Fay Alzahrani Dhay Alzahrani Omar D. Mohammed Jamal F. Nayfeh Mechanical Engineering Department Prince Mohammad bin Fahd University PMU Khobar Saudi Arabia

ISBN: (数字)9798331509262

ISBN: (纸本)9798331509279

Electric vehicles (EVs) and autonomous vehicles (AVs) are subject to increasing demands for sustainable transportation. In the current paper, a model design is developed that can fit both EV and AV applications. A comparative analysis is studied for power consumption between EVs and AVs, focusing on how the integration of autonomous systems influences energy efficiency. While both EVs and AVs contribute to sustainable transportation, the power demands of AVs are heightened due to the additional computational and sensor systems required for real-time decision-making and navigation. The study evaluates power consumption across several factors, including propulsion, sensor and onboard computation, and HVAC systems, under similar driving conditions. Results indicate that even when Avs and EVs have the same weight, AVs consume more power due to their advanced sensor suites and computational systems, leading to noticeable differences in power consumption across both urban and highway driving scenarios. The findings highlight the impact of automation on vehicle efficiency and provide insights into future design considerations for energy-efficient autonomous transportation. This paper aims to bridge existing gaps in the literature by offering a direct comparison of power usage between EVs and AVs, ultimately contributing to the development of more sustainable vehicle technologies.

关键词： Power demand HVAC Navigation Transportation Focusing Propulsion Robot sensing systems Electric vehicles Energy efficiency Real-time systems

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