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

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A Flexible Hybrid Resource Allocation Model for Enhanced Efficiency using AI in Wireless sensor Networks 3

A Flexible Hybrid Resource Allocation Model for Enhanced Eff...

引用

3rd International conference on Electronics and Renewable systems, ICEARS 2025

作者： Endla, Purushotham Mohandas, R. Saikia, Achinta Lakshmi, C. Karthikeyan, G. Moharekar, Tejashree Tejpal Sr University School of Sciences and Humanities Department of Physics Telangana Warangal506371 India Chennai Institute of Technology Department of Ece Chennai India Mariani College Department of Statistics Mariani Assam Jorhat785634 India Saveetha Engineering College Chennai India Karpagam College of Engineering Department of Artificial Intelligence & Data Science Coimbatore India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798331509675

Wireless sensor Networks (WSNs) have become a cornerstone technology in various fields, including environmental monitoring, industrial automation, and healthcare. This paper presents a novel hybrid resource allocation model designed to enhance efficiency in Wireless sensor Networks (WSNs) using advanced Artificial Intelligence (AI) techniques. The proposed model integrates static and dynamic resource allocation strategies with machine learning and reinforcement learning to optimize key network resources such as energy, bandwidth, and processing power. Comprehensive evaluations demonstrate that the proposed model outperforms nine existing models across multiple metrics, including energy efficiency, network lifetime, throughput, delay, latency, and accuracy of resource allocation. The proposed model achieved an energy efficiency of 0.98 J/bit, extended network lifetime to 620 days, and maintained a high throughput of 620 Kbps. Notably, the model demonstrated the lowest delay (90 ms) and latency (180 ms) while achieving the highest resource allocation accuracy of 97.8%. These results highlight the model's capability to dynamically adjust resource allocation in response to real-time network conditions, ensuring optimal performance and resource utilization. The proposed model's success in efficiently managing WSN resources marks a significant advancement in the field, offering a robust solution for various WSN applications requiring high efficiency and reliability. © 2025 IEEE.

关键词： Artificial Intelligence Energy Efficiency Machine Learning Network Lifetime Reinforcement Learning Resource Allocation Wireless sensor Networks

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Comparative Analysis of Multi Objective Node Placement Strategies in Wireless sensor Networks 17

Comparative Analysis of Multi Objective Node Placement Strat...

引用

17th IEEE International conference on advanced Networks and Telecommunications systems, ANTS 2023

作者： Ojha, Amritesh Gupta, Bharat National Institute of Technology Electronics & Communication Engineering Patna India

ISBN: (纸本)9798350307672

Real-world service providers in Wireless sensor Networks (WSN) face the challenge of balancing two important considerations: achieving a high coverage and extending the network's lifespan. The optimization problem of coverage in WSN holds significant importance as it aims to achieve a balance between network lifetime and coverage. This encompasses the reduction of energy consumption, the enhancement of coverage rate, and the optimization of energy consumption balance. Although heterogeneities are acknowledged and addressed in certain aspects of WSNs, such as routing protocols, researchers tend to overlook their significance when it comes to node placement or deployment. This research presents a comparative examination of multi-objective node placement algorithms in WSNs, specifically focusing on their performance in heterogeneous circumstances. However, the impact of an asymmetric link, which may vary depending on the node, is not well considered in heterogeneous WSNs. The detrimental effects of link heterogeneity on the performance of deployment methods have been observed. Our investigation revealed that the thought-out strategy for exploiting heterogeneity was not used. The implementation of sensor networks based on 6G technology in smart city applications necessitates the utilization of diverse sensor nodes. In order to achieve optimal resource usage, it is imperative to take into account the heterogeneity of nodes during the deployment process. © 2023 IEEE.

关键词： sensor nodes

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Modeling of Total Occupancy Curves with Integrated Single Parking Times as Input for Microscopic Traffic Simulation 18th

Modeling of Total Occupancy Curves with Integrated Single Pa...

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18th Scientific and Technical conference on Transport systems - Theory and Practice (TSTP)

作者： Kaiser, Alexander Schade, Joachim Zadek, Hartmut Inst Automat & Kommunikat Transport & Assistance Magdeburg Germany

ISBN: (纸本)9783031223587;9783031223594

This paper presents a novel approach for the preparation of real parking data for microscopic traffic simulation or similar applications. Against the backdrop of an incomplete database given from single parking spot sensors and manual countings on a few parking spaces in Munich, the data are cleaned and expanded by various methods, e.g. a neural network to forecast the total occupancy at each hour as well as an optimization model to generate the corresponding parking times of each car. This results in a list of realistic parking events for a certain location and day. The method is transferable to other use cases regarding off-street parking spaces, particularly with an incomplete and discontinuous detection of parking occupancy and times.

关键词： Parking occupancy Parking time Parking sensor Neural network Optimization model Microscopic traffic simulation

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Neural Network Technology of Mine Recognition Based on Data From Magnetic Field sensors 12

Neural Network Technology of Mine Recognition Based on Data ...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Peleshchak, Roman Lytvyn, Vasyl Peleshchak, Ivan Voloshyn, Serhii Lviv Polytechnic National University Department of Information Systems and Networks Lviv79000 Ukraine

ISBN: (纸本)9798350358056

Mine detection is an ongoing and growing problem that affects many people around the world due to the enormous danger that mines pose to humans. Mine detection occurs using various methods that use active sensors, including ultra-wideband (UWB) radar. Although active landmine sensors are often used for performance reasons, they can cause unintended landmine detonations because they operate on transmitted and reflected electromagnetic signals. Another way to detect mines without detonating mechanisms is the use of passive detectors. In this article, an optimal neural network structure with Adam's optimization algorithm is developed for effective mine classification based on magnetic field sensor data. This approach made it possible to increase the accuracy of mine detection to 99.23 percent. © 2023 IEEE.

关键词： Adam's optimization algorithm data preprocessing data visualization deep neural network passive mine detection

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Understanding Properties of DriveBay Electromagnetic Tracker for Use in Soft Robot Experiments 28th

Understanding Properties of DriveBay Electromagnetic Tracker...

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2024 International conference Automation

作者： Smaz, Tomasz Zubrycki, Igor Lodz Univ Technol Inst Automat Control Stefanowskiego 18 PL-90537 Lodz Poland

ISBN: (纸本)9783031782657;9783031782664

Soft Robotics experiments necessitate advanced measurement techniques to track robot pose and deformations accurately. Electromagnetic tracking systems provide substantial benefits over vision-based systems, especially in capturing both the position and orientation of a robot's surface without occlusion issues. However, these systems are typically designed for applications in controlled environments, with multiple guidelines stated by the producers, necessitating an evaluation of their effectiveness in different contexts. This paper presents a series of foundational experiments to assess the capabilities and limitations of such a system in Soft Robotics. We investigate the impact of distance from the base station, resistance to environmental interference, effects of metallic elements, and the accuracy of rotational measurements. The results demonstrate a significant influence of positional accuracy relative to the distance from the transmitter, with a tenfold decrease in accuracy observed. Additionally, the presence of metallic objects in close proximity (less than 20mm) to the probes adversely affects accuracy, as do large metallic elements such as construction materials. This effect is particularly pronounced when the sampling frequency of the system aligns with multiples of the electrical network frequency, resulting in more than a tenfold reduction in accuracy.

关键词： Soft Robotics Electromagnetic Tracking sensor Accuracy Robotics Measurement systems Environmental Interference in Robotics

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Printed Flexible Carbon Black-Based sensor for Nitrite Detection in Medical applications 5

Printed Flexible Carbon Black-Based Sensor for Nitrite Detec...

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5th IEEE International conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Shboul, Ahmad Al Pacheco, Dianne Izquierdo, Ricardo Department of Electrical Engineering 1100 Notre-Dame St W MontrealQCH3C 1K3 Canada

ISBN: (纸本)9781665457330

This work presents a novel printed and flexible sensor for detecting nitrite (NO2-) using a hybrid nanocomposite composed of carbon black (CB), polyvinyl butyral (PVB), and 4-aminophenol (AP). We prepared the NO2- sensor using a combination of simple mixed materials, and a moderate drying temperature of 40°. The sensor has two linear response ranges to NO2- from 25 μM to 1 mM and from 1 to 50 mM, with a detection limit of 25 μM at room temperature. Our results show that the sensor displays appropriate selectivity towards 50 μM of NO2- in the presence of potentially interfering anions and organic compounds that may be present in human urine. We propose that the sensing mechanism is based on the physical electrostatic interaction of NO2- molecules with AP's positively charged amine groups. This interaction results in a reduction of the electrical resistance when the sensor is exposed to NO2- anions. Our work highlights the potential of this printed sensor as a reliable and accurate tool for NO2- detection in medical applications. © 2023 IEEE.

关键词： Carbon black

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Incorporating LoRa Based Wireless sensor Network and Machine Learning Technologies to Improve Precision Agriculture 3rd

Incorporating LoRa Based Wireless Sensor Network and Machine...

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3rd International conference on Intelligent systems and applications, ICISA 2024

作者： Shaikh, Aman Ranjan, Nihar M. Rai, Satayush Rao, Pranil Ashok Shinde, Ganesh Department of Information Technology JSPM’s Rajarshi Shahu College of Engineering Pimpri-Chinchwad India

ISBN: (纸本)9789819798384

In the contemporary landscape, the agricultural sector has undergone transformational changes, embracing progressive dynamics through the integration of cutting-edge technologies and methodologies. The global adoption of IoT, AI/ML, and similar innovations reflects their capacity to furnish precise, reliable, and consistent outcomes, enabling data-driven decision-making. The amalgamation of IoT and ML models emerges as a strategic choice to enhance data analytics, aiming at a substantial improvement in both the quantity and quality of agricultural yields. This paper seeks to elucidate the synergistic interaction of various agrarian elements, orchestrating the computational prowess facilitated by ML models and data derived from IoT sensors transmitted through LoRa-based Wireless sensor Network (WSN) infrastructure. The proposed system advocates a comprehensive three-tier architectural framework, wherein ML and IoT systems collaborate seamlessly to process data for field management. The envisioned system extends its utility by translating these predictions into visually comprehensible representations. The integrated approach signifies a departure from conventional methods, offering a novel pathway to ensure the sustainability of yield, encompassing both production and grading standards. This paper thus contributes to the discourse on leveraging advanced technologies for agricultural optimization in response to evolving global demands. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decision making

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Smart Fish Feeding in IoT-based Aquarium: A Comprehensive Approach Integrating Computer Vision, Machine Learning and sensor Technology 4

Smart Fish Feeding in IoT-based Aquarium: A Comprehensive Ap...

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4th International conference on Next Generation Computing applications, NextComp 2024

作者： Cassy, Ryan Bekaroo, Girish Middlesex University Mauritius Flic-en-Flac Mauritius

ISBN: (纸本)9798331517403

With the increasingly busy lifestyles of people, advanced maintenance systems such as automated feeding has become of utmost importance to aquarium owners. Despite existing technologies, there remains a gap in smart feeding solutions tailored to the specific dietary requirements of different fish species and population sizes. This paper investigates smart fish feeding through automated detection, counting, classification and feeding of fishes within aquariums. As part of this paper, a smart population-driven aquarium maintenance system, named AquaTrack, is proposed that integrates Internet of Things (IoT), computer vision, machine learning, and sensor technologies. The system detects, classifies, and counts fish, adjusting feeding amounts based on species and population to mitigate the risks of overfeeding and underfeeding, which can significantly affect water quality. The system was evaluated through four research questions, where a general accuracy of 76.9% in fish species identification and 77.1% in fish counting were found. While promising outcomes were observed under specific conditions, variability and limitations in performance across different scenarios were also noted. Environmental factors such as lighting, reflections, shadows, and particulate matter affected the accuracies, particularly in scenarios involving smaller fish quantities. Based on these findings, the study recommends further refinement of the system to enhance its capabilities. © 2024 IEEE.

关键词： Fish

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Modelling and analysis of QPD based track sensor developed for inter-satellite optical communication 18

Modelling and analysis of QPD based track sensor developed f...

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18th IEEE International conference on advanced Networks and Telecommunications systems, ANTS 2024

作者： Singh, Nirlesh Keshavappa, Ravikumar Senapati, Priyabrata Raha, Bijoy Praveen, K.C. Kalyani, K. Mittal, Sanjay Umesh, S.B. Karantha, S.P. Laboratory for Electro Optics Systems LEOS-ISRO Bangalore India

ISBN: (纸本)9798350391725

Free Space Optical Communication (FSO) is an emerging and promising technology that utilizes optical signals to transmit data through free space. It offers several advantages, including high data rates, low latency, security, and immunity to electromagnetic interference. FSO systems find applications in various fields, including telecommunications, satellite communication, disaster recovery, and military operations. Utilizing lasers for free space optical communication presents an appealing alternative to conventional radio frequency (RF) communication methods, particularly in managing substantial data volumes while simultaneously reducing size, weight, and power (SWaP) requirements. Among the formidable challenges in the realm of satellite-based optical communication systems lies the necessity for highly precise acquisition and tracking of target satellites. Quad Photodetector (QPD) tracking sensors stand out as the preferred choice for discerning angular positions due to their rapid responsiveness and excellent accuracy. In this paper, we expound upon the operational principles and mathematical modelling of QPD-based tracking sensors, aiming to attain optimal sensitivity and meet predefined field of view (FOV) specifications. Additionally, we elucidate the focusing technique, detail the testing setup, and present the achieved outcomes of the tracking sensor. © 2024 IEEE.

关键词： Photodetectors

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Hydrogen sensor based on Planar Polymer Bragg Grating coated with Pd/Ni composite film 12

Hydrogen sensor based on Planar Polymer Bragg Grating coated...

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conference on advanced sensor systems and applications XII

作者： Zhou, Yong Hu, Wenbin Ye, Yongxin Wang, Jingjing Dai, Jixiang Yang, Minghong Hellmann, Ralf Kefer, Stefan Wuhan Univ Technol Natl Engn Res Ctr Fiber Opt Sensing Technol & Net Wuhan 430070 Hubei Peoples R China Aschaffenburg Univ Appl Sci Appl Laser & Photon Grp Aschaffenburg Germany

ISBN: (纸本)9781510657090;9781510657083

As one of the cleanest energy sources in the 21st century, the development of hydrogen energy has attracted the attention of all countries in the world, so the monitoring of hydrogen leakage has become a current research focus. This study demonstrates a novel hydrogen sensor that combines a planar polymer grating with a Pd/Ni hydrogen-sensitive material that takes advantage of the hydrogen-absorbing expansion properties of Pd to cause the central wavelength drift of Planar Polymer Bragg Grating (PPBG) by strain transformation. The experimental results show when the hydrogen concentration is 0.3%, 0.6% and 1%, the wavelength shift of the sensor is 50 pm, 85 pm and 110 pm respectively, and the response time is approximately 30 seconds. This hydrogen sensor has the advantages of high sensitivity, low cost and compact structure, leading to great potential in industrial applications.

关键词： PPBG Hydrogen sensor Pd/Ni composite film

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