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

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Efficient Drone-Based Mobile Wireless sensor Network for Spatio-Temporal Environmental Monitoring

Efficient Drone-Based Mobile Wireless Sensor Network for Spa...

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International Symposium on advanced Networks and Telecommunication systems (ANTS)

作者： Ayshika Kapoor Dheeraj Kumar Department of Electronics and Communication Engineering Indian Institute of Technology Roorkee Uttarakhand India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

The technological advancements in wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) or drones have made significant contributions in various fields, benefiting human society. Although WSNs have been widely used for environmental monitoring, their utility is constrained by inherent limitations, which make them suitable only for small-scale sensing tasks. On the other hand, UAVs provide quick access to large areas, including challenging terrains, allowing faster data collection that is both less labor-intensive and more cost-effective. In this paper, we present an efficient method to collect data for environmental monitoring using a drone-based mobile WSN system. The framework discretizes the region to be monitored into a 3D spatial-temporal field, where the field is further divided into sub-grids for the deployment of drones in each sub-grid. The drones utilize their built-in sensors to move around the designated region in a pre-defined trajectory to collect spatio-temporal data. In order to obtain parameter values at intermediate points within the surveyed region, interpolation techniques such as inverse distance weighting (IDW) and nearest neighbors (NN) are applied, ensuring comprehensive data coverage. To validate the feasibility of our proposed system, experiments are performed for temperature modeling applications using a simulated dataset, a real-world NYC weather dataset, and a real-time REST API dataset. The obtained results demonstrate that the proposed model is well-suited for large-scale sensing, even in remote areas, exhibiting cost-effectiveness and substantial reductions in labor and resource requirements, providing a robust and efficient solution for real-time environmental data collection and analysis.

关键词： Temperature sensors Wireless sensor networks Interpolation Accuracy Real-time systems sensors Trajectory Environmental monitoring Drones Meteorology

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advanced Sensing Development to Support Robot Accuracy Assessment and Improvement

Advanced Sensing Development to Support Robot Accuracy Asses...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Qiao, Guixiu NIST Gaithersburg MD 20899 USA

ISBN: (纸本)9781728190778

Robots can perform various types of automated movements in the workspace. In recent years, robot applications have been expanded to a much wider scope, including robot machining, robot assembly, robot 3D printing, robot inspection, etc. Many of these applications require robots to have higher absolute accuracy compared with conventional robot part handling and welding. The capability to assess a robot's accuracy, and further, improve accuracy becomes important. In this paper, an advanced sensor and an accompanying methodology are developed that enable manufacturers to perform accuracy assessment to improve their robot systems. A smart target (patent pending) is developed at the National Institute of Standards and Technology (NIST). This sensor is integrated with a vision-based measurement instrument to perform high accuracy measurements of six-dimensional (6-D) information (x, y, and z position, roll, pitch, and yaw orientation) for a moving robot arm. The smart target is motorized. It can constantly rotate toward the vision-based measurement instrument to maximize its line-of-sight. A use case is presented to demonstrate the accuracy degradation assessment by using the smart target on a Universal Robot.

关键词： Robotic assembly Instruments Welding Position measurement NIST Robot sensing systems Three-dimensional printing

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Review of Dynamic Spectrum Sharing: Techniques and Challenges

Review of Dynamic Spectrum Sharing: Techniques and Challenge...

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International conference on Optimization and applications (ICOA)

作者： Chaymaa Lakouismi Hamza Ouamna Zhour Madini Younes Zouine Dept. electrical and telecommunication ISET Laboratory Kenitra Morocco

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

It appears that the frequency bands used by the current mobile network are becoming increasingly scarce, making it impossible for it to meet the overwhelming demand brought on by the introduction of 5G and the rapidly growing popularity of IOT devices. It is evident that due to spectrum shortage, the traditional method of statically allocating spectrum to particular services or users became systematically inefficient and unsustainable. As a result, it is time for a wireless communication system to emerge that allows multiple users or wireless systems to share radio frequency spectrum in real-time and efficiently. It's DSS ( dynamic spectrum sharing), a revolutionary approach that allows different wireless technologies to dynamically share the same spectrum resources based on demand and usage patterns. This dynamic allocation is typically facilitated by advanced spectrum management techniques and intelligent algorithms that we are going to provide in this article in addition to the challenges that this technology has to face.

关键词： Wireless sensor networks 5G mobile communication Scheduling algorithms Reviews Heuristic algorithms Dynamic scheduling Frequency measurement sensors Security Radio spectrum management

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Smart Cooling: Temperature-Controlled BLDC Motor with advanced System Health Monitoring

Smart Cooling: Temperature-Controlled BLDC Motor with Advanc...

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International conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： S G Srivani Sahana R Dept. of Electrical and Electronics Engineering RV College of Engineering Bengaluru India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

With the industrial reliability of the STM32 microcontroller and highly versatile temperature sensor to enhance the efficiency of BLDC motors in cooling applications. The system dynamically adjusts motor speed based on real-time temperature readings, ensuring optimal thermal management. Additionally, it employs a linear regression model to predict motor speed, that improve system performance and extend system lifespan of the cooling system. The integration of real-time monitoring and predictive analytics offers significant advancements in motor control technology, enhancing reliability and energy efficiency. The system's design, including hardware and software components, and presents experimental results demonstrating its effectiveness in maintaining desired temperature levels and responsiveness to thermal conditions. This smart cooling solution provides a reliable and efficient approach for managing BLDC motors in industrial applications, contributing to improved system health and energy savings.

关键词： Temperature sensors Temperature measurement Cooling Linear regression Motors Real-time systems Energy efficiency Software reliability Monitoring Predictive maintenance

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Dynamic Energy-Efficient Clustering Algorithms Using advanced Metaheuristics for Prolonged Network Lifetime in Wireless sensor Networks

Dynamic Energy-Efficient Clustering Algorithms Using Advance...

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Ubiquitous Computing and Intelligent Information systems (ICUIS), International conference on

作者： T. Sivakumar A. Sathiya M. Saravanan G. Uma S. Arivumani Samson A. Elangovan Dept. of Electronics & Communication Engg M. Kumarasamy College of Engineering (Autonomous) Dept. of Electronics & Communication Engg Full Time Research Scholar M. Kumarasamy College of Engineering (Autonomous) Dept. of Electronics & Communication Engg Faculty of Engineering & Technology Annamalai University Chidambaram Dept. of Mathematics Sathyabama Institute of Science and Technology Chennai Dept. of Electronics & Communication Engg Arunai Engineering College Tiruvannamalai

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

Wireless sensor Networks (WSNs) are pivotal in modern applications, yet challenges such as energy efficiency and network lifetime remain critical. This paper proposes a Dynamic Energy-Efficient Clustering Algorithm (DEECA) utilizing hybrid metaheuristics combining Egret Swarm Optimization and Genetic Algorithms. The proposed method dynamically selects cluster heads and optimizes clustering based on node energy, distance, and traffic conditions. Simulations were conducted on diverse WSN scenarios to evaluate energy consumption, network lifetime, packet delivery ratio, and throughput. Results demonstrate that DEECA outperforms traditional algorithms such as LEACH, HEED, and PSO by achieving a 20% increase in network lifetime and a 15% improvement in packet delivery ratio. Visual analyses include energy consumption trends, coverage heatmaps, and multi-metric radar plots. The findings validate DEECA's capability to enhance energy efficiency and scalability in WSNs, offering a robust framework for real-world deployments in resource-constrained environments.

关键词： Wireless communication Wireless sensor networks Energy consumption Visualization Heuristic algorithms Metaheuristics Clustering algorithms Energy efficiency Particle swarm optimization Genetic algorithms

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The Influence of Computer Vision on Road Traffic

The Influence of Computer Vision on Road Traffic

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International conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Melvin Verdinan Mulia Hans Dominic Tirta Said Achmad Rhio Sutoyo Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Implementing computer vision in road traffic management brings significant impacts, making transportation systerms more efficient, safe, and sustainable. This advanced technology analyzes real-time traffic conditions, providing crucial data for effective traffic management. Using computer vision, authorities can monitor traffic flow, detect incidents, and manage congestion more effectively. The primary aim of this paper is to explore the challenges and impacts associated with using computer vision in road traffic management while offering insights for future research and practical applications. A Systematic Literature Review (SLR) was conducted, adhering to the PRISMA Flowchart Diagram methodology, to identify and evaluate relevant studies in this field. The systematic approach ensures a comprehensive understanding of the current state of computer vision in the transportation sector. The findings from this review underscore the transformative potential of computer vision in enhancing traffic management systems. Moreover, this work highlights several existing challenges that need to be addressed to maximize the benefits of computer vision. These challenges include the need for more advanced algorithms capable of handling diverse and complex traffic scenarios and integrating this technology with existing infrastructure. By identifying these challenges, the paper provides valuable insights for future research, emphasizing the importance of developing more robust and adaptive computer vision systems. Ultimately, this research aims to contribute to advancing computer vision in road traffic management, promoting safer and more efficient transportation systems worldwide.

关键词： YOLO Computer vision Accuracy Transportation sensor fusion Traffic control Cameras Road traffic Real-time systems Systematic literature review

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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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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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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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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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