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检索条件"任意字段=4th IEEE International Conference on Distributed Computing in Sensor Systems"

共 6248 条记录，以下是151-160 订阅

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Situation theory Based Query Generation for Determining Situation Awareness Across distributed Data Streams 4

Situation Theory Based Query Generation for Determining Situ...

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4th ieee international conference on Human-Machine systems, ICHMS 2024

作者： Jia, Lesong Peng, Anfeng Li, Huao Guo, Xuehang Lewis, Michael University Of Pittsburgh School Of Computing And Information PittsburghPA15260 United States

ISBN: (纸本)9798350315790

While conventional measures of Situation Awareness (SA) focus on its adequacy in supporting decisions, fully exploiting information being returned by teams of unmanned aerial vehicles (UAVs) requires close attention to the sources as well as the impact of information. the problem of measuring SA for UAV teams lies in determining the extent to which information is being integrated from across the team. To address this problem, we are developing a Situation theory based method for spatially and temporally indexing relevant situations. Observations from each UAV are treated as 'infons' indexed by their particular time and place. By maintaining provenance on individual observations, we can trace their participation in supporting operator SA and use these data to evaluate the effects of alternative data presentations for multi-UAV surveillance. A wildfire monitoring application domain is introduced, and an example developed from a wildfire training scenario for Great Sand Dunes National Park. © 2024 ieee.

关键词： Antennas

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Sensing the Future: Challenges and Trends in IoT sensor Technology 4

Sensing the Future: Challenges and Trends in IoT Sensor Tech...

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4th international conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Rajora, Ricky Rajora, Aarju Sharma, Bhanu Aggarwal, Priyanshi thapliyal, Siddhant Chitkara University Institute of Engineering and Technology Chitkara University Punjab 140401 India Chandigarh Engineering College Department of Computer Science & Engineering Mohali India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science & Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350307757

In the ever-evolving world of the Internet of things (IoT), sensors play a crucial role as essential parts, linking and merging different elements to create a smart worldwide network. this study examines the crucial function of sensors in the Internet of things (IoT) ecosystem, where they serve as sensory organs that translate the intricacies of the physical world into a uniform language for networked systems. the main emphasis is on their ability to gather and evaluate factual data from the surroundings, which impacts the performance and effectiveness of IoT applications in many industries. this research explores the uses and relevance of many sensor types, including temperature, humidity, proximity, motion, gas, biometric, vibration, image, infrared (IR), occupancy, water quality, pressure, light, and sound sensors. Although sensors contribute to the improvement of automation, control systems, and predictive analysis, they also give rise to issues in terms of security, interoperability, and power efficiency. the convergence of edge computing, artificial intelligence (AI), quantum sensors, 5G connection, and improved sensor integration has the potential to bring about significant changes in the Internet of things (IoT) environment. the study provides a thorough survey of sensor applications in several domain including healthcare, agriculture, smart cities, and automotive sectors. Lastly, it examines the difficulties and potential opportunities, highlighting the vital significance of sensors in influencing the future of interconnection and data-driven decision-making. © 2024 ieee.

关键词： Internet of things

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Optimization of DG with Enhanced Elephant Herding Optimization in Distribution Network 4

Optimization of DG with Enhanced Elephant Herding Optimizati...

引用

4th ieee international conference on computing, Communication, and Intelligent systems, ICCCIS 2023

作者： Chouhan, Vinod thakur, Ritula Government Polytechnic College Electrical Engineering Department Rajasthan Jodhpur India N.I. T T TR. Chandigarh Electrical Engineering Department Chandigarh India

ISBN: (纸本)9798350306118

Conventional and Non-Conventional Centralized power plants far from populations are utilized to generate electric power and this electric power transmits from generating stations to distribution stations over long distance. Distribution systems are generally radial and ring type. the use of radial distribution systems (RDS) is popular because they are straightforward, affordable, and only rely on a single feeder for supply when something goes wrong. Due to the unidirectional flow of electricity in RDS and the large r/x(resistance/reactance) ratio, huge voltage drops, poor Voltage Stability, and significant energy loss occur. distributed Generation (DG) is installed in the distribution network at the customer's end, but correct installation is necessary to maximize its size and allocation. Meta-heuristic techniques are applied to get solution of the optimize problem of DG site and size. Single as well as Multi-objective problem can be solved using meta-heuristic artificial intelligence techniques such as Enhanced Elephant Herding Optimization (EEHO) by using a load flow technique (Newton Raphson method) for placing small generating units in the distribution system. A Meta heuristic algorithm Elephant herding optimization (EHO) is based on herding behavior of elephants. Enhanced Elephant herding optimization (EEHO) is modified phase of EHO to improve inappropriate divergence towards origin of clan and improve its exploration and extraction aptitude by updating both clan and separating operators. © 2023 ieee.

关键词： distributed power generation

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Research on optimizing autonomous operation of multi-objective clusters based on improved particle swarm algorithm 4

Research on optimizing autonomous operation of multi-objecti...

引用

4th international conference on Intelligent Power and systems, ICIPS 2024

作者： Bao, Wei Yang, Yanan Yan, Yuehao Li, Jingli State Grid Zhengzhou Power Supply Company ZhengZhou China Zhengzhou University School of Electrical and Information Engineering ZhengZhou China

ISBN: (纸本)9798331532765

With the vigorous development of new power systems and the large-scale access of distributed energy, cluster control, as a new type of power system control scheme, can alleviate communication pressure during distributed energy control and achieve refined control of distributed energy. the cluster includes various elements such as distributed power sources, energy storage systems, and loads. Challenges in internal cluster control include difficulties in coordinated control and efficient energy utilization. Based on considerations of economic, environmental, and reliability factors, this paper establishes a cluster autonomous optimization scheduling model. By comprehensively considering operating costs, environmental impact, and system stability, the model aims to achieve efficient, economical, and environmentally friendly operation within clusters. An improved particle swarm algorithm is proposed to address the multi-objective optimization problem of cluster autonomous operation. By dynamically adjusting the inertia factor and introducing mutation operations, the algorithm's global search capabilities and local search accuracy are enhanced, effectively avoiding local optima and improving optimization results. the results indicate that compared to the autonomous solutions obtained by the original algorithm, the optimized operational plans obtained by the improved particle swarm algorithm can further enhance the cluster's wind power accommodation capacity, enable more precise control and coordination of controllable power within the group, and achieve superior economic and environmental benefits. © 2024 ieee.

关键词： distributed Wind

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Development of Weight Measurement System Based on Bend sensor and Linear Compression Spring 4

Development of Weight Measurement System Based on Bend Senso...

引用

4th international conference on computing and Communication systems, I3CS 2023

作者： Deka, Parama Deka, Surajit Roy, Ram Kishore Bezboruah, Tulshi Gauhati University Department of Electronics and Communication Technology Guwahati India Gauhati University Department of Electronics and Communication Engineering Guwahati India

ISBN: (纸本)9798350323771

In this paper, we proposed to develop a weight measurement system by using bend sensors and a linear compression spring. In the proposed system, a bend sensor is mounted vertically to a linear compression spring. the free end of the bend sensor is attached to the top end and the other end having electrical connection is attached to the bottom end of the spring. the bend sensor is a flexible sensor whose resistance varies with the variation in bending radius of the curvature. the weight to be measured is applied on top of the pane placed on the compression spring. With the application of weight, the length of the compression spring will vary and hence this variation will vary the bending radius of the flex sensor. thus, the variation in bending radius will introduce variation in the resistance of the bend sensor. Using resistance to voltage converter, the variation in resistance is converted to voltage. the signal conditioning circuit is used to process the output of resistance to voltage converter. Further, National Instruments Data Acquisition card NI USB-6001 is used to acquire the signal and transmit it to a personal computer in real time. the Graphical User Interface developed on LabVIEW platform hosted in personal computer displays the measured weight in real time. the advantages of the system are it's simple in design and low in cost. © 2023 ieee.

关键词： Personal computers

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Spectral Clustering Based Resource Allocation Strategy for distributed Large-scale Network Emulation 25

Spectral Clustering Based Resource Allocation Strategy for D...

引用

25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Jiyan Gu, Rentao Bai, Lin Sch. of Information and Communication Engineering Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Beijing China School of Economics and Management Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350330014

Nowadays, networks are increasingly reliant on software frameworks and virtualization. To obtain relevant pre-dictions of the behavior of their protocols, network emulation tools play a crucial role. However, as networks grow in size and complexity, the emulation task demands more physical resources such as CPU and memory. Consequently, a single physical machine is no longer sufficient to handle large-scale network emulation. Instead, distributed network emulation tools must be employed for resource-intensive network emulation tasks. In resource-intensive distributed network emulation, the physical resource allocation is NP-hard to perform appropriately. In this paper, we propose SCBG (spectral clustering based greedy node placement algorithm) as a means to enhance the bandwidth utilization between physical nodes in distributed emulation. SCBG aims to address the communication bottleneck in distributed network simulation, surpassing the algorithm proposed by Distrinet, while also improving the algorithm's execution speed. Additionally, SCBG incorporates optimization for time dilation when physical bandwidth resources are severely insufficient. this optimization leads to a reduction in the additional time required for network simulation after applying time dilation. Experimental results demonstrate that SCBG surpasses the algorithm in Distrinet across a diverse range of intricate large-scale networks. © 2023 ieee.

关键词： Optimization

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SELF-CARE: Selective Fusion with Context-Aware Low-Power Edge computing for Stress Detection 18

SELF-CARE: Selective Fusion with Context-Aware Low-Power Edg...

引用

18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Rashid, Nafiul Mortlock, Trier Al Faruque, Mohammad Abdullah Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA USA

ISBN: (纸本)9781665495127

Detecting human stress levels and emotional states with physiological body-worn sensors is a complex task, but one with many health-related benefits. Robustness to sensor measurement noise and energy efficiency of low-power devices remain key challenges in stress detection. We propose SELFCARE, a fully wrist-based method for stress detection that employs context-aware selective sensor fusion that dynamically adapts based on data from the sensors. Our method uses motion to determine the context of the system and learns to adjust the fused sensors accordingly, improving performance while maintaining energy efficiency. SELF-CARE obtains state-of-theart performance across the publicly available WESAD dataset, achieving 86.34% and 94.12% accuracy for the 3-class and 2-class classification problems, respectively. Evaluation on real hardware shows that our approach achieves up to 2.2x (3-class) and 2.7x (2-class) energy efficiency compared to traditional sensor fusion.

关键词： Stress detection edge computing energy efficiency sensor fusion

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Minimum Utilization of Energy Resource via MAC Routing Protocol for Mobile sensor Network 4

Minimum Utilization of Energy Resource via MAC Routing Proto...

引用

4th ieee Annual Flagship India Council international Subsections conference, INDISCON 2023

作者： Singh, Alka Desai, Meena College of Education Iimt University Uttar Pradesh Meerut India Isme - School of Management & Entrepreneurship Atlas Skill Tech University Maharashtra Mumbai India

ISBN: (纸本)9798350333558

the MAC routing protocol for mobile sensor networks is a method of communication that enables the data transfer between sensors over an established network. this protocol is designed to provide reliable, fast and efficient data delivery between nodes within a mobile sensor network. It differs from the traditional routing protocol in that it takes into consideration the mobility of the nodes and changes the routes dynamically to meet the dynamic requirements of the network. the main features of MAC for mobile sensor networks include route discovery and maintenance, dynamic path selection and dynamic quality of service. It also ensures reliability by providing multiple paths for data transmission and path diversity for redundant data transfer. Additionally, it provides fault tolerance and security via neighbor discovery and authentication. the protocol is also suited to heterogeneous networks due to the support for different types of communication technologies such as 802.11, ZigBee, etc. Furthermore, the MAC routing protocol provides multiple solutions such as deferred ordering, probabilistic forwarding and distributed routing. the MAC routing protocol, therefore, provides an effective way to connect sensors in mobile sensor networks. © 2023 ieee.

关键词： Routing protocols

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Liquid Level Fiber sensor Based on Fully Connected Neural Network and In-line Mach-Zehnder Interferometer 4

Liquid Level Fiber Sensor Based on Fully Connected Neural Ne...

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4th international conference on Communication Technology and Information Technology, ICCTIT 2024

作者： Bai, Junjie Lin, Weihao Xu, Renan He, Yihua Lin, Boqiang Zhang, Mingkun The Higher Educational Key Laboratory for Flexible Manufacturing Equipment Xiamen China

ISBN: (纸本)9798331528973

An innovative fiber optic liquid level sensor based on a peanut-shaped fiber structure has been designed and fabricated for use in micro-buoy systems. this sensor features two cascaded peanut-shaped structures with a 25 mm spacing, and its sensing characteristics have been thoroughly studied. this setup achieves millimeter-level monitoring intervals by measuring changes in interference wavelengths, enabling the system to accurately deduce the current liquid level state with a sensitivity of 0.087 nm/mm. To enhance the accuracy of data analysis, a Fully Connected Neural Network (FCNN) has been implemented for data processing and analysis. After training this model, the average percentage error was successfully reduced to 0.76%. Consequently, this cutting-edge fiber optic liquid level sensor demonstrates significant potential for precise measurements in marine micro-buoy systems, thereby ensuring seamless monitoring and robust protection of offshore wind energy installations and critical port infrastructures. the design effectively demonstrates the potential development space for the application of artificial intelligence and fiber optic sensing technology in oceanic micro-buoy liquid level measurement. © 2024 ieee.

关键词： Mach-Zehnder interferometers

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Accurate Prediction Model of Greenhouse sensor Data based on Deep Learning Algorithm 4

Accurate Prediction Model of Greenhouse Sensor Data based on...

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4th ieee international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Cai, Haotian Chuai, Xiaolong JiLin Agricultural Science and Technology University College of Electrical and Information Engineering Jilin China

ISBN: (纸本)9798350352931

Traditional greenhouse environmental monitoring systems mostly rely on simple algorithms for data processing. When faced with complex environmental factors, these methods often cannot accurately capture the temperature and humidity characteristics in the data, resulting in limited prediction accuracy. this article adopts a precise prediction model for greenhouse sensor data that combines Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) networks, aiming to improve prediction accuracy and the intelligence level of data analysis. the spatial features extracted by CNN are then fed into an LSTM network. the noise increased from 0% to 25%, and the accuracy of temperature prediction decreased from 90% to 72.82%, while the humidity dropped sharply from 88% to 58.62%. the research results indicate that the application of deep learning (DL) technology provides an efficient and innovative method for greenhouse environment monitoring, significantly enhancing the intelligence level and effectiveness of agricultural management. © 2024 ieee.

关键词： Data accuracy

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