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An Novel Based Mobile Dropping Sesing to Protect using Inertia sensor and Integration of DL Technology 4

An Novel Based Mobile Dropping Sesing to Protect using Inert...

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4th ieee international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Barkunan, S.R. Radha, J. Egala, Raju Singhal, Ritesh Kumar Alkhafaji, Mohammed Ayad Sefeer, Ban Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi India Nandha Engineering College Department of Cse Tamilnadu Perundurai India Department of Ece Andhra Pradesh Visakhapatnam India Ajay Kumar Garg Institute of Management Ghaziabad India National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350360165

With all such technologies, the recent advances in health monitoring due to smartphone sensor technologies provide an opportunity to quantify an individual's functional performance and deviations from normality. Falling and drowning are two major unnatural reasons for accidental silent death, and it requires an ambient approach to detect the same. this paper presents a novel ambient assistive framework, FaDD (Falling and Drowning Detection), designed for identifying and distinguishing incidents of falls or drowning. Input data are taken through smartphone sensors like the accelerometer, gyroscope, magnetometer, and GPS, which capture the movement of a person's body for effective recognition. By adopting a hierarchical approach, FaDD effectively detects dropping and choking actions using machine learning models. the framework is also integrated with the emergency alert notifications embedded in a smartphone application and, in the case of drowning, immediately alerts the respective stakeholders of the guardians, rescue team, and close community circle. With an accuracy rate of 98%, FaDD is proficient in detecting falls, drowning, and normal activities. Coordination of all stakeholders through the FaDD framework is bound to enhance the provision of an effective and efficient health service to the people. © 2024 ieee.

关键词： Smartphones

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MEMS RESERVOIR computing USING FREQUENCY MODULATED ACCELEROMETER 35

MEMS RESERVOIR COMPUTING USING FREQUENCY MODULATED ACCELEROM...

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35th ieee international conference on Micro Electro Mechanical systems conference (ieee MEMS)

作者： Mizumoto, Takahiro Hirai, Yoshikazu Banerjee, Amit Tsuchiya, Toshiyuki Kyoto Univ Kyoto Japan

ISBN: (纸本)9781665409117

We developed an intelligent MEMS sensor with data processing ability for data acquisition and conversion at low power consumption. It enables data processing at the sensing device for efficient distributed processing. We employed a MEMS reservoir which integrates sensing and computing functions in single device structure. In this research we designed a frequency modulated capacitive accelerometer and characterized its frequency response. the measured response was used for simulation of time series prediction and the machine learning task was successfully demonstrated.

关键词： Reservoir computing Frequency Modulated Accelerometer Intelligent sensor Nonlinear Resonator

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Smart-Hop: Low-Latency Multi-hop Networking for LoRa 18

Smart-Hop: Low-Latency Multi-hop Networking for LoRa

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

作者： Ahmar, Absar-Ul-Haque Joosen, Wouter Hughes, Danny Katholieke Univ Leuven Comp Sci Imec DistriNet Leuven Belgium

ISBN: (纸本)9781665495127

Low Power Wide Area Networks (LPWANs) provide the Internet of things (IoT) with energy-efficient, low cost, and long-range networking. LoRaWAN is one of the most widely deployed and studied LPWAN technologies due to its license-free operation and open standard, which has enabled 3rd parties to deploy millions of networks worldwide. LoRa allows transmission range and speed to be traded off by configuring the Spreading Factor (SF) setting. By tuning this parameter, the performance envelope of the network can be configured to favor a higher speed or longer range. While the SF of LoRA provides a simple and elegant means to tailor performance, at the highest spreading factor, maximum throughput drops to a few bits per second, dramatically increasing data extraction times. In this paper, we address this problem by proposing Smart-Hop, a novel multi-hop MAC layer protocol for LoRa which implements low-overhead routing. In contrast to prior work, Smart-Hop exploits the variable range afforded by different SFs to eliminate much of the complexity and overhead of traditional multi-hop mesh networking. Smart-Hop reduces the number of end-devices operating at high SFs while implementing low overhead routing in order to reduce data extraction times. these improvements are achieved while preserving the maximum range offered by LoRa in its highest SF configuration.

关键词： Low Power Wide Area Networks (LPWAN) LoRa Spreading Factor (SF) allocation Wireless sensor Networks (WSN) mesh networking.

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An Efficient Technique for Energy Consumption and Network Lifetime by distributed Data Gathering Method from IoT Nodes 4

An Efficient Technique for Energy Consumption and Network Li...

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

作者： Pratap Rana, Ravendra Sharma, Vishal Agarwal, Varsha School of Media Film &television Studies Iimt University Uttar Pradesh Meerut India Isme - School of Management & Entrepreneurship Atlas Skill Tech University Maharashtra Mumbai India

ISBN: (纸本)9798350333558

distributed data gathering from Internet of things (IoT) nodes is a widely used process for collecting information in a distributed way from connected IoT devices. this process can be used in a range of scenarios, from home automation to the industry, to collect data from multiple nodes in an efficient and reliable way. In distributed data gathering, each node is responsible for collecting its own data and transmitting it to an aggregating server, or a gateway, which centralizes the data of all nodes. As a result, data can be processed faster, having access to an up-to-date overview of all the nodes in a given network. Furthermore, distributed data gathering can allow for more data to be collected, as well as real-time observation of the environment since the data flow is continuous and uninterrupted. © 2023 ieee.

关键词： Internet of things

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Smart Flood Detection and Communication in Hazardous Zones via MANET-Based IoT and Parallely distributed Slimmable Neural Networks 4

Smart Flood Detection and Communication in Hazardous Zones v...

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4th international conference on Sustainable Expert systems, ICSES 2024

作者： Sathya, V. Bhadula, Shuchi Srinivasan, R. Bhargav, H.K. Panda, Bhavani Sankar Barve, Amit Department of Computer Science Vallam Tamil Nadu Thanjavur613403 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248 002 India Veltech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Department of Computer Science and Engineering Avadi Tiruvallur Tamil Nadu Chennai600054 India Shridevi Institute of Engineering and Technology Department of Computer Science and Engineering Karnataka Tumakuru572106 India Raghu Engineering College Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam531162 India Parul Institute of Technology Parul University Faculty of Engineering and Technology Department of Computer Science and Engineering P.O.Limda Gujarat 391760 India

ISBN: (纸本)9798331540364

Disasters can be mitigated by an early warning signal and proper communication within the hazardous environment using the MANET technology. However, the exact prediction of disaster situation is needed for the timely disaster management. Hence in addition to MANET technology, deep learning algorithms and Inter of things (IoT) can also be integrated into disaster detection and communication systems. the presented research developed a novel parallely distributed slimmable neural network with orchard algorithm for the accurate flood disaster prediction. the model processed the dataset containing various measurements such as temperature, humidity, precipitation, air, soil moisture and rainfall level that are collected by the IoT sensor deployed in the various location of the hazardous environment. the gathered data are initially pre-processed using the correlation coefficient min-max normalization approach. Further, the relevant characteristics of the flood disaster from the data are extracted through spike driven transformer process. these refined and dimensionality reduced data are then entered into the proposed framework for the disaster prediction. Here the integrated orchard algorithm increased the disaster monitoring accuracy on the basis of better optimized parameters. the model resulted 95% accuracy, 93% precision, 94% recall and 96% f-score. therefore, the presented method is an effective prediction mechanism for the disaster management in IoT MANET. © 2024 ieee.

关键词： Soil moisture

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High signal-to-noise ratio distributed fiber optic sensor based on Nonlinear frequency modulated signal 4

High signal-to-noise ratio distributed fiber optic sensor ba...

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4th international Computational Imaging conference, CITA 2024

作者： Zhang, Jing Xu, Tuanwei Xie, Yaning Cao, Kai Deng, Dimin Li, Fang State Key Laboratories of Transducer Technology Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510688834

this article presents the design of an optical pulse signal utilizing nonlinear frequency modulation. the designed signal achieves pulse compression with an acceptable signal-to-noise ratio (SNR) and controlled main lobe broadening, significantly suppressing sidelobes and attaining a sideband suppression ratio exceeding -57.15 dB. this methodology is applicable to distributed fiber optic sensing systems, theoretically enabling such systems to maintain high SNR and extensive dynamic range, thereby fulfilling the requirements for high spatial resolution and ultra-long-distance fiber sensing. © 2025 SPIE.

关键词： Frequency modulation

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Assessment of distributed Photovoltaic Power Generation Potential Based on LCOE 4

Assessment of Distributed Photovoltaic Power Generation Pote...

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4th international conference on Advanced Electrical and Energy systems, AEES 2023

作者： Tian, Xueqin Luo, Jiasong Fan, Hao Wu, Shichong Xie, Hua State Grid Econ & Technol Res Inst Co Ltd Beijing China State Grid Corporation of China Beijing China Beijing Jiaotong University School of Electrical Engineering Beijing China

ISBN: (纸本)9798350342659

Accurately assessing the potential of distributed photovoltaic (PV) power generation in China is of great significance for realizing the dual-carbon goal. Combining various factors such as the nature of land for housing construction, meteorological conditions and policies, an assessment model for the power generation potential of distributed PV technology was constructed. Considering economy, an economic developable capacity assessment model based on LCOE was constructed based on analyzing the cost of PV power generation. the distributed PV power generation potential of Chifeng City in Inner Mongolia Autonomous Region was evaluated, and the results showed that Chifeng City still has a great potential for distributed PV development. © 2023 ieee.

关键词： Solar energy

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distributed Photovoltaic Data Compression Method Based on Time Series Prediction Model 4

Distributed Photovoltaic Data Compression Method Based on Ti...

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4th international conference on New Energy and Power Engineering, ICNEPE 2024

作者： Li, Bo Shi, Zhan Deng, Xiaozhi Wu, Zhentian Yang, Zhihua Electric Power Dispatching Control Center Guangdong Power Grid Co. Guangzhou China Guangdong Electric Power Communication Technology Co. Guangzhou China

ISBN: (纸本)9798331516086

With the proliferation of distributed photovoltaic (PV) systems, the need for efficient real-time monitoring and data management has become indispensable. this paper presents a novel approach that integrates the ProbAttention mechanism into the Transformer model to enhance predictive encoding compression. By optimizing the attention mechanism, this study addresses challenges related to time complexity, memory usage, and prediction errors, thereby significantly improving compression rates. A layered sampling method is employed to optimize the PV data for the encoder-decoder architecture. the ProbAttention-Transformer model, utilized as the predictor, demonstrates superior prediction accuracy and reduced prediction errors, requiring fewer bits for encoding and achieving higher compression ratios. Extensive experiments on datasets from PV meters and inverters corroborate the effectiveness of this approach. Comparative experiments reveal that the ProbAttention-Transformer model outperforms logTrans and LSTMa, reducing MSE scores by 10.9% and 23.8%, respectively, while improving compression ratios by 20.18% and 27.78%. © 2024 ieee.

关键词： Data compression distributed photovoltaic Predictive encoding Time series

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High Power Isolated DC-DC Converters for MVDC-HVDC Application 4

High Power Isolated DC-DC Converters for MVDC-HVDC Applicati...

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4th ieee international conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Kumar, Chandan Patro, Siba Kumar Indian Institute of Technology Roorkee Department of Electrical Engineering Roorkee247667 India

ISBN: (纸本)9798350383997

High voltage direct current (HVDC) technology become crucial for power systems because of its benefits including less losses, easier asynchronous grid connections, improved controllability, higher system availability, and less short-circuit currents. Recently, several innovative converter topologies have been proposed to connect medium-voltage to high-voltage systems. Many of these topologies are based on chain-link or modular concepts, which offer scalability across different voltage and current ranges while maintaining high reliability, feasibility, and power quality. this article aims to analysis a comprehensive review of recent isolated DC/DC converters topologies based on modular multilevel converter (MMC) for MVDC to HVDC interconnections. A comparative analysis of these topologies is conducted to ascertain their configuration, operating principles, as well as their advantages and limitations. these analyses will be helpful in identifying the most suitable topology for a particular application. © 2024 ieee.

关键词： distributed Renewable energy Sources (DRES) High Voltage Direct Current (HVDC) Isolated DC-DC converter Medium Voltage Direct Current (MVDC) Modular Multilevel converter (MMC)

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Research on key technologies of multi-agent game decision distributed learning system for agent equipment decision parameter optimization 4

Research on key technologies of multi-agent game decision di...

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4th international Signal Processing, Communications and Engineering Management conference, ISPCEM 2024

作者： Yu, Xie Yu, Changzhou Liu, Siyuan Yang, Guang Xu, Haoran An, Bo Jiangsu WebAce Intelligent Industry Innovation Center CO. LTD. Nanjing211135 China

ISBN: (纸本)9798331528676

the optimization of decision parameters for equipment in the Intelligent agent domain is becoming increasingly paramount, driven by advancements in modern technology and the intricacies of battlefield environments. Multi-agent game theory, by simulating the interactions and confrontations of various agents under diverse scenarios, can authentically replicate the complex dynamic relationships inherent in the battlefield. Meanwhile, distributed learning systems demonstrate unique advantages in managing vast data sets and intricate computations. the synergy of these two approaches not only enhances the accuracy and timeliness of decision-making but also propels the innovation and advancement of intelligent agent technology. the transition from theory to practical application encompasses numerous critical technologies, including the construction of multi-agent game models, algorithm design, and the establishment of distributed architectures, all aimed at achieving efficient and precise optimization of intelligent agent equipment decision parameters. ©2024 ieee.

关键词： Adversarial machine learning

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