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

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Multi-Coil-Based Inductive Power Transfer System For Insitu Soil Sensing Application

Multi-Coil-Based Inductive Power Transfer System For Insitu ...

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Micro and Nanotechnology for Power Generation and Energy Conversion applications (PowerMEMS)

作者： Sheng Ding John Sanchez Shad Roundy Ramesh Goel Cody Zesiger Darrin J. Young University of Utah USA Utah State University USA

ISBN: (数字)9798350380200

ISBN: (纸本)9798350380217

A 3-coil-based inductive power transfer system was designed and demonstrated for energizing a 20 mW underground battery-free soil moisture sensor with an improved efficiency and voltage gain compared to a 2-coil-based implementation. The 3-coil-based design employs an intermediate tuned coil, which is critically coupled to the last-stage coil interfacing the sensor, thus effectively mitigating the loading effect from the sensor to ensure an enhanced performance provided certain design conditions are met. The prototype system achieves an inductive power transfer efficiency and a voltage gain of 4.2% and 4.6, respectively, over a 30 cm distance in air. The system further demonstrates an efficiency of 3.2% and a voltage gain of 4 across a 30 cm depth of soil. The prototype system is also capable of wirelessly transferring 40 mW of power over the same distance with an efficiency of 4.8%, limited by the input stage power driving capability. The multi-coil-based system design approach is desirable for enabling advanced, wireless, and battery-free underground soil monitoring systems, which may demand high power dissipation.

关键词： Coils Wireless communication Wireless sensor networks Soil moisture Prototypes Moisture Voltage sensors Monitoring System analysis and design

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AI-Driven Insights: Enhancing Personality Type Prediction with advanced Machine Learning Algorithms

AI-Driven Insights: Enhancing Personality Type Prediction wi...

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International conference on Contemporary Computing and Informatics (IC3I)

作者： Rajeev Semwal Nandita Tripathi Ajay Rana Udit Kumar Pandey Shilpa Parihar Mahesh Kumar Bairwa Amity Institute of Psychology and Allied Sciences Amity University Uttar Pradesh Greater Noida Campus Uttar Pradesh India Amity School of Engineering and Technology Amity University Uttar Pradesh Greater Noida Campus Uttar Pradesh India Department of Management Graphic Era Hill University Haldwani India Jai Narain Vyas University Jodhpur Rajasthan India Principal Incharge Hospitality and Tourism Department State Institute of Hotel Management Jhalawar Rajasthan India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Artificial intelligence (AI) and Internet of Things (IoT) technology together present transformative possibilities in the field of personality type prediction, with applications in psychology, human resources, marketing, and personal development. This work presents an in-depth investigation of IoT systems, such as sensor networks and data aggregation platforms, and advanced machine learning algorithms, including neural networks, support vector machines (SVM), and decision trees. It also proposes a conceptual system design leveraging these technologies to enhance the accuracy and efficiency of personality forecasts. Through a comprehensive literature review and conceptual system design, the paper identifies key challenges and constraints, including data quality, computational complexity, and ethical considerations. Additionally, it introduces hypothetical implementation scenarios to demonstrate the anticipated benefits and practical applications of the system, such as personalised insights and real-time data processing. The paper concludes with a discussion of future directions, emphasising the potential of emerging IoT technologies, like edge computing and 5G, and AI advancements to improve predictive capabilities and expand research opportunities. This study contributes to the growing body of knowledge at the intersection of AI, IoT, and psychology by providing crucial insights for developing innovative approaches across various domains.

关键词： Support vector machines Ethics Machine learning algorithms Accuracy Psychology systems architecture Transforms Real-time systems Internet of Things Artificial intelligence

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A Deep Learning-based Multi-Path Routing Protocol for Improving Security using Encryption in Underwater Wireless sensor Networks

A Deep Learning-based Multi-Path Routing Protocol for Improv...

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Electronics and Sustainable Communication systems (ICESC), 2020 International conference on

作者： K. Prakash S. Sathya Department of Computer Science VELS Institute of Science Technology & Advanced Studies(VISTAS) Chennai India Sri Sarada Mahavidyalayam Arts and Science College for Women’s Ulundurpet Department of Information Technology VELS Institute of Science Technology & Advanced Studies(VISTAS) Chennai India

Underwater Wireless sensor Networks (UWSN) is an interesting topic today in both scientific research and commercial applications. Major challenges of UASN design constraints are unreliable network lifetime and low battery power of underwater sensor nodes. In addition, sensor nodes may generate sensitive data that needs to be hidden. Therefore, encryption ciphers maintain security by encrypting the data before sending it. However, encryption methods require more computation and energy, and network lifetime is reduced. A key issue in this research area is that due to the complexity of underwater environments and slow transmission rates, inefficient architectures for multi-path variable data transmission are a security measure combined with encryption to prevent overate attacks with high delay tolerance. To overcome these issues, in this work proposed the method Multi-path Routing Protocol (MRP) based on Spectral Social Spider optimization (SSSO) feature selection. Initially, collected the sensor network dataset from standard repository using for classification to avoid the delay and improving the transmission using best features. The first step is to remove redundant data for each cluster head by applying a pre-processing step that uses data redundancy elimination techniques to reduce unbalanced data and missing values. Second-stage feature selection is based on the maximum weightage features using maximum threshold limits based on Spectral Social Spider optimization(SSSO). SSSO algorithm for analysis relay method for dependable packet delivery. After feature selection to sending and receiving the data based on the features using Improved Data Encryption Standard (I-DES) by analysing the cipher text to identify the encryption algorithm, focused cryptanalysis methods can be used. Before classification evaluating the features metrics based on Softmax Neuron Classifier (SNC) using for estimating the features weights validation. The final classification stage using Recurs

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Design and Implementation of Internet of Things and Cloud Technology in Flood Risk Mitigation 3

Design and Implementation of Internet of Things and Cloud Te...

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3rd International conference on Cybernetics and Intelligent System (ICORIS)

作者： Siek, Michael Larry, Laurensius Bina Nusantara Univ Business Informat Syst Program Informat Syst Dept Fac Comp & Media Jakarta 11480 Indonesia

ISBN: (纸本)9781665425803

In the last decade, floods have frequently occurred in many big cities due land use mismanagement, and poor water management and control. With the climate change, the flood disaster becomes more intensive and frequent causing a lot of damages on public infrastructure and human casualties. The rapid development of advanced information technology has contributed on how to manage and control the flood events through integrated information system and advanced flood modelling techniques. This paper focuses on designing and implementing Internet of Things (IoT) and Cloud Technology (CT) for supporting the flood risk mitigation system in the area of Jabodetabek. The IoT based water sensor network with automated data acquisition system were implemented and simulated in the upstream and downstream water gates at Katulampa and Manggarai, respectively. The integration of IoT system based on Arduino and Raspberry Pi, and AWS Cloud allows for better real-time data collection and management that could be used for accurate flood model forecasting with data assimilation and machine learning techniques. The presentation and dissemination of flood data and modelling results using IoT and CT systems through web/mobile application could support the flood risk mitigation and preparedness.

关键词： real time sensor network data acquisition flood risk management and monitoring database information system on cloud infrastructure

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Optimized VLSI Architecture of Integrated Bi-Phase Space Encoding with Manchester Encoding Protocol for Lo-RA applications

Optimized VLSI Architecture of Integrated Bi-Phase Space Enc...

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Frontier Technologies and Solutions (ICFTS), International conference on

作者： C. Nithiya M. Jasmin M. Sneha Attar Fazooq Hussain N. Nalini B. Thiyaneswaran Department of ECE R.M.K. College of Engineering and Technology Chennai Department of Electronics and Communication Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai Department of AI & DS Rajalakshmi Institute of Technology Chennai Department of ECE K.L.M college of Engineering for Women Kadapa Andhra Pradesh Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Department of ECE Sona college of Technology Salem

ISBN: (数字)9798331502768

ISBN: (纸本)9798331502775

Low-power and long-range communication systems are critical for modern applications such as loT, sensor networks, and remote monitoring. This study proposes an optimized VLSI architecture integrating Bi-Phase Space Encoding and Manchester Encoding protocols for low-power, long-range communication (Lo-RA) applications. The architecture achieves significant improvements in power efficiency, signal integrity, and throughput by employing advanced techniques such as dynamic voltage scaling, clock gating, and error correction mechanisms. The system's performance was evaluated across multiple parameters. The total power consumption was reduced by 21.43%, with jitter and clock skew improvements of 62.5% and 50%, respectively. Throughput increased by up to 33.33% for Bi-Phase Encoding and 32.86% for Manchester Encoding, ensuring reliable and efficient data transmission at clock frequencies up to 50 MHz. The system's bit error rate (BER) was reduced by up to 5x with error correction, achieving nearly error-free communication at high signal-to-noise ratios (SNR). The final architecture achieves an accuracy of 96.8% in maintaining data integrity across varying environmental conditions. These results demonstrate the robustness of the proposed design, making it suitable for Lo-RA applications such as loT, sensor networks, and remote monitoring. The integration of Bi-Phase and Manchester Encoding ensures seamless compatibility with existing communication standards while meeting the stringent requirements for low power and long-range communication.

关键词： Protocols Very large scale integration Throughput Encoding Dynamic voltage scaling Error correction Signal integrity Remote monitoring Clocks Signal to noise ratio

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Creating A Web-Based Platform For Programming Humanoid Robots

Creating A Web-Based Platform For Programming Humanoid Robot...

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International conference on High Technology for Sustainable Development (HiTech)

作者： Ventsislav Nachev Daniela Gotseva Department of Computer Systems Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350358100

ISBN: (纸本)9798350358117

This research project focuses on the design and implementation of a web-based programming platform designed for Misty humanoid robots. Misty robots possess advanced capabilities, and to fully utilize their potential, a user-friendly and accessible programming environment is essential. The proposed platform aims to streamline the development process, enabling both novice and experienced developers to create custom applications and behaviors for Misty robots. This research involves the design and implementation of a secure and scalable architecture, integration of essential sensor data and hardware interfaces, and the development of a comprehensive software development kit. The platform's versatility will empower developers to explore new possibilities in the field of humanoid robotics, contributing to advancements in robotics research, education, and commercial applications.

关键词： Computer languages Education Humanoid robots Robot sensing systems Libraries Hardware Sustainable development Programming profession Software development management Programming environments

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Martian Flight: Enabling Motion Estimation of NASA's Next-Generation Mars Flying Drone by Implementing a Neuromorphic Event-Camera and Explainable Fuzzy Spiking Neural Network Model

Martian Flight: Enabling Motion Estimation of NASA's Next-Ge...

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conference on Digital Avionics systems (DASC)

作者： David AR Harbour Kelly Cohen Steven D Harbour Bradley Ratliff Alex Henderson Hallie Pennel Stephen Schlager Tarek M Taha Chris Yakopcic Vijayan K Asari Jan Boril Aqsa Sultana Shaik Nordin Abouzahra Anya Bulter Connor Prikkel NASA (Ohio Space Grant Consortium) University of Dayton ELE Undergrad Beavercreek Ohio USA Director of AI Bio Lab University of Cincinnati Mason Ohio USA Director of AI Hardware Research Parallax Advanced Research Beavercreek Ohio USA Applied Sensing Lab University of Dayton Dayton Ohio USA Parallax Research Institute Beavercreek Ohio USA Sinclair College Clayton Ohio USA University of Dayton Dayton Ohio USA Air Force Department University of Defense Brno Czechia University of Dayton Beavercreek Ohio USA

ISBN: (数字)9798350349610

ISBN: (纸本)9798350349627

The event camera is researched, developed, and designed to imitate the human eye; it is a groundbreaking vision sensor with the following advantages over a standard camera: a net rate that is much faster, a latency that is far less, a high dynamic range, and it uses far less power. These fundamental properties assist in enabling the design of third-generation algorithms in Spiking Neural Networks intended to mimic the human brain and vision processing. Moreover, these fundamental properties enable swift robotics despite the challenges of motion blur and high latency that standard cameras face. Also, these properties should enable motion estimation from the surface features on Mars, which is difficult to achieve with standard cameras. For this research, the team is using a NASA Space use-case application. For this NASA Space application, the team has chosen a challenging motion-estimation task involving a Mars-based above-ground Helicopter beyond “Ingenuity” and the planet and surface of Mars. Event-based cameras have been gaining interest within the computer vision community. They are particularly suitable for applications with challenging temporal constraints and safety requirements. Thus, Event-based sensors are an excellent match for Spiking Neural Networks (SNNs), as coupling an asynchronous sensor with neuromorphic hardware can result in real-time systems with minimal power requirements. Moreover, methods to verify and validate event-based sensing platforms for space applications are lacking. In this paper, we investigate the addition of fuzzy logic models to arrive at an explainable SNN algorithm for the NASA space use-case. Ultimately, the team aims to develop a unified model yielding reasonably accurate optical flow estimates.

关键词： Mars Neuromorphics Event detection NASA Robot vision systems Spiking neural networks Cameras sensor systems Real-time systems Standards

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Acoustofluidic Based Wireless Micropump for Portable Drug Delivery applications 43

Acoustofluidic Based Wireless Micropump for Portable Drug De...

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43rd Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (IEEE EMBC)

作者： You, Rui Fu, Xing Duan, Xuexin Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China

ISBN: (纸本)9781728111797

In this study, an acoustofluidic based wireless micropump for drug delivery was proposed and fabricated. The key actuator of this micropump is a small gigahertz piezoelectric resonator, which could induce strong fluidic streaming at low applied power. This acoustofluidic micropump has stable and accurate dosage resolution (7.0 mu L), and sufficient flow rate (1.34 mL/min). The miniaturized size and wireless controlled operation prove it as a portable drug delivery system.

关键词： Wireless communication Drugs Wireless sensor networks Electric potential Micropumps Drug delivery sensor systems

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SwarmCatcher: An AI-Powered Anti-Drone Surveillance System for Public Safety Over 5G and Beyond Ecosystems

SwarmCatcher: An AI-Powered Anti-Drone Surveillance System f...

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International conference on Intelligence in Next Generation Networks (ICIN)

作者： Sarantis Kalafatidis Dimitrios Tsiktsiris Dimitrios Trakos Antonios Lalas Konstantinos Votis Dimitrios Tzovaras Centre for Research and Technology Hellas / Information Technologies Institute Greece

ISBN: (数字)9798331542399

ISBN: (纸本)9798331542405

The proliferation of unmanned aerial vehicles (UAVs) presents significant challenges to public safety and critical infrastructure protection. This paper introduces SwarmCatcher, an innovative AI-powered anti-drone and surveillance system designed to detect and classify UAV threats in real-time. Swarm-Catcher integrates multi-sensor technologies, including optical, thermal, RF, and acoustic systems, with advanced AI algorithms to provide thorough situational awareness. Utilizing the low-latency, high-throughput capabilities of cloud-native architecture and 5G networks, the system supports scalable deployment across diverse environments, offering rapid threat mitigation. Real trials were conducted, utilizing 5G infrastructures in the FIDAL and CERTH testbeds, evaluating and demonstrating SwarmCatcher's potential to address the requirements of public safety agencies and pave the way for integration with 6G networks. The paper investigates SwarmCatcher's architecture, key performance metrics, and its role in advancing next-generation vertical-specific applications for public safety.

关键词： Cloud computing Technological innovation 5G mobile communication Surveillance Prevention and mitigation Autonomous aerial vehicles Public security Real-time systems Critical infrastructure systems support

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Wearable Smart Health Monitoring Transmitter and Portable Receiver systems for Enhanced Wellness Insights

Wearable Smart Health Monitoring Transmitter and Portable Re...

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Automation, Computing and Renewable systems (ICACRS), International conference on

作者： T.C Sivaprasad R. Surendhar A. J. Heiner Electronics and Communication Engineering Saveetha Engineering College Chennai India

This study presents the development and evaluation of a smart wearable belt designed for comprehensive health monitoring and fall detection. The wearable integrates advanced sensors, including vibration and heartbeat, to give users real-time insights into their well-being. The vibration sensor, meticulously calibrated for precise fall detection, exhibited high sensitivity and responsiveness, distinguishing between daily activities and potential accidents. Simultaneously, the heartbeat sensor demonstrated accurate and consistent heart rate monitoring, contributing to proactive cardiovascular health management. The seamless integration of these sensors, supported by MQTT connectivity and secure data transmission, ensures a user-friendly experience. Cloud integration enhances data processing and analytics, empowering users with a comprehensive health dashboard. Results indicate the reliability of the fall detection system and the accuracy of heart rate monitoring. This intelligent wearable belt represents a promising advancement in health technology, offering a holistic solution for users seeking real-time health insights and proactive fall prevention. Ongoing research focuses on refining algorithms and incorporating user feedback for continuous improvement and broader applications in personalized health care.

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