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Research on Digital Equipment Application Based on Digital Twin Technology

Research on Digital Equipment Application Based on Digital T...

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2023 international conference on Internet of Things, Robotics and distributed computing, ICIRDC 2023

作者： Zhang, Yangyang Fang, Liqing Qi, Ziyuan Deng, Huiyong Liang, Hui 1st Dept. of Shijiazhuang Campus Army Engineering University Shijiazhuang China

ISBN: (纸本)9798350375275

Modern large-scale mechanical equipment usually has diverse tasks and complex structures. The traditional development and design, task management and operation and maintenance modes are increasingly difficult to meet the practical needs. With the development of computer and information technology, digital twin technology has been proposed and widely concerned. It can realize the interaction and fusion between an object's physical entity and virtual model by establishing a model with multi-physics, multi-scale, multi-level and multi-disciplinary attributes. It has the characteristics of virtual-real synchronization, faithful mapping, and high fidelity, which provides a new way to solve the above problems. Therefore, based on the basic theory and technology of digital twin, taking typical complex equipment as the research object, this paper proposes the overall architecture of digital equipment, summarizes the key technologies of developing digital equipment, and explores several potential application services based on digital twin, such as product design, auxiliary decision-making, intelligent maintenance and health management, to provide theoretical and methodological references for further research and equipment application in the future. © 2023 ieee.

关键词： Decision making

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An FPGA-Based Accelerator for Graph Embedding using Sequential Training Algorithm

An FPGA-Based Accelerator for Graph Embedding using Sequenti...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Sunaga, Kazuki Sugiura, Keisuke Matsutani, Hiroki Keio Univ 3-14-1 HiyoshiKohoku Ku Yokohama 2238522 Japan

ISBN: (纸本)9798350364613;9798350364606

A graph embedding is an emerging approach that can represent a graph structure with a fixed-length low-dimensional vector. node2vec is a well-known algorithm to obtain such a graph embedding by sampling neighboring nodes on a given graph with a random walk technique. However, the original node2vec algorithm typically relies on a batch training of graph structures;thus, it is not suited for applications in which the graph structure changes after the deployment. In this paper, we focus on node2vec applications for IoT (Internet of Things) environments. To handle the changes of graph structures after the IoT devices have been deployed in edge environments, in this paper we propose to combine an online sequential training algorithm with node2vec. The proposed sequentially-trainable model is implemented on an FPGA (Field-Programmable Gate Array) device to demonstrate the benefits of our approach. The proposed FPGA implementation achieves up to 205.25 times speedup compared to the original model on ARM Cortex-A53 CPU. Evaluation results using dynamic graphs show that although the accuracy is decreased in the original model, the proposed sequential model can obtain better graph embedding that achieves a higher accuracy even when the graph structure is changed.

关键词： FPGA Graph embedding node2vec OS-ELM Sequential training

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Automated Cybersecurity Attack Detection Using Prairie Dog Optimization and Multilayer Perceptron in Healthcare System 3

Automated Cybersecurity Attack Detection Using Prairie Dog O...

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3rd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Pillai, Sanjaikanth E. Vadakkethil Somanathan Poddar, Sanjay Susanta Nagendar, Y. Pareek, Piyush Kumar Zanke, Pankaj School Of Electrical Engineering And Computer Science University Of North Dakota Grand Forks United States Fortinet Ltd DallasTX United States School Of Computer Science And Engineering Sr University Telangana Warangal India Nitte Meenakshi Institute Of Technology Department Of Aiml And Ipr Cell Bengaluru India Sapiens International Corporation United States

ISBN: (纸本)9798350318609

Internet of Things (IoT) technologies have become an inevitable part of our lives with many innovations and conveniences in many fields such as education, healthcare, social life and security. While healthcare network complexity and connectivity are developing in a superior manner at the same time, cyber-attack surfaces and vulnerabilities are also increasing dramatically. Harming people either physically or digitally are some of the threat to the health and life of patients through data breaches across multiple departments of health systems. In this research, the prairie dog optimization (PDO) algorithm and multilayer perceptron (MLP) is proposed cyber-attack detection model. The proposed approach was performed the several IoMT cybersecurity datasets using Intensive Care Unit (ICU Dataset), Washington University in st. Louis enhanced healthcare monitoring system (WUstL-EHMS) datasets, Edith Cowan University- Internet of Health Things (ECU-IoHT), and TON-IoT. PDO is used for selecting the optimal features from the attained dataset, MLP parameters is performed by hyperparameter optimization as well as 10-fold cross-validation technique for performance assessment. The proposed method has the potential to counter cyber-attacks in healthcare applications, it attained higher precision at 99.54%, accuracy of 99.45%, recall 99.56% and f1-score 99.46% in ECU-IoHT dataset. © 2024 ieee.

关键词： Internet of things

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The Impact of the Mixed Load Model on the Placement and Sizing of distributed Generation (DG) in a Radial Distribution Network 1

The Impact of the Mixed Load Model on the Placement and Sizi...

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1st international conference on Social and Sustainable Innovations in Technology and Engineering (SASI-ITE)

作者： Manikanta, G. Math, Ashish Valavala, Madhu Gunaga, Shruti Kumar, Sujit Kumar, N. Kiran Mishra, Suchana Rao, K. Durga Dayananda Sagar Coll Engn Bangalore Karnataka India Amity Univ Amity Innovat & Design Ctr IIC Noida India Swarnandhra Coll Engn & Technol Narsapur India MS Ramaiah Inst Technol Bangalore Karnataka India Avanthi Inst Engn & Technol Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9798350360806;9798350360790

Distribution systems heavily employ distributed Generators (DG) to decrease losses. Some writers have explored this crucial optimization problem with a constant power load model. Consumers in distribution network load centres utilize varied loads based on voltage. A few authors have investigated this optimization problem with voltage-dependent load models. Some studies used a single load model independent of voltage or depending on bus system voltage. Few studies have employed a single load model on the whole feeder, lateral or sub-lateral, to analyze all voltage-dependent load models. A mixture of voltage-dependent load models calculates consumer load on a bus or all buses in actual distribution networks. Combining all voltage-dependent load models at one or more buses has yet to be fully researched. This study examines mixed load model effects in radial distribution networks with DG. DG position and capacity must be optimized to decrease power losses, a tough, nondifferentiable, non-convex combinatorial task. A quantum-inspired evolutionary metaheuristic algorithm solves this combinatorial optimisation challenge. A quantum-inspired evolutionary algorithm (AQiEA) determines DG placement and capacity. The suggested technique is evaluated on two ieee benchmark test bus systems. Tabulated findings show that AQiEA reduces power loss the most.

关键词： distributed Generation Active power loss Voltage-dependent load model AQiEA Mixed Load Model

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Catastrophe Alert System for Risk Mitigation and an Auxiliary Vital Monitoring sensor 1

Catastrophe Alert System for Risk Mitigation and an Auxiliar...

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1st international conference on Intelligent Technologies for Sustainable Electric and Communications systems, iTech SECOM 2023

作者： Chandran, Sharath Praveen, D. Sabeenian, R.S. Sudha, V. Sona College of Technology Department of Ece Salem India

ISBN: (纸本)9798350371185

This article proposes a sophisticated, secure-edge Internet-of-Things (IoT) architecture for monitoring catastrophes. This article focuses on developing a LoRa-based catastrophe monitoring system incorporating an avalanche detection system, a fire detection module, and an accelerator-based earthquake detector. The system aims to provide real-time monitoring and early warning capabilities for potential disasters such as fires, earthquakes, and avalanches. The system has an auxiliary vital sign measurement system for wearable applications in snowy terrains. The system can detect potential disasters and issue timely warnings by continuously monitoring environmental parameters and observing an individual's vitals. LoRa technology is commendable for its long-range, low-power capabilities. Employing LoRa allows the system to transmit data over long distances with minimal power consumption, allowing for extended battery life and reduced maintenance requirements. By promptly detecting and reporting these natural disasters, the system can help mitigate their impact, save lives, and facilitate faster response and recovery efforts. © 2023 ieee.

关键词： Disasters

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Design and Implementation of a Flexible Wireless sensor Network for Environmental Monitoring with in Digital Cities Framework 1

Design and Implementation of a Flexible Wireless Sensor Netw...

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1st international conference on Intelligent systems and Computational Networks, ICISCN 2025

作者： Manogna, B. Sai Rao, R. Gowri Shankar Chythanya, K. Ravi Navamani, C. Raghuram, K.S. Isaac, J. Samson Marri Laxman Reddy Institute of Technology and Management Department of Computer Science and Engineering Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Physics Chennai India Sr University School of Computer Science and Artificial Intelligence Warangal India Department of Computer Science and Engineering Erode India Department of Mechanical Engineering Visakhapatnam India School of Engineering and Technology Karunya Institute of Technology and Sciences Department of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798331529246

The paper highlights a Wireless sensor Network (WSN) implementation for environmental monitoring, emphasizing cost-effectiveness and adaptability. APIs designed to handle values instead of voltage levels increase system resilience, while open standards promote security, cost efficiency, and auditability. The data shows a diurnal temperature range from 20°C (night) to 38°C (day), stable humidity at 38%, and UV radiation peaking at 6 (day) and dropping to 1.5 (night). Smoke levels are consistently high at 490 μg/m3, while toxic gas concentrations slightly rise to 0.5 ppm during the day from 0.45 ppm at night. Fire metrics remain low and stable. These findings highlight the need for UV protection, air quality controls, and consistent fire safety measures. The system achieves effective environmental monitoring while remaining adaptable for future needs, underscoring its value in scalable, cost-efficient, and sustainable public management solutions. © 2025 ieee.

关键词： Environmental monitoring

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RGBD Depth sensor Frame Data streaming to Handheld Device Using WebRTC-Based Framework 1

RGBD Depth Sensor Frame Data Streaming to Handheld Device Us...

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1st ieee international Symposium on Consumer Technology, ISCT 2024

作者： Ahmad, Muhammad Anwar Suaib, Norhaida Mohd Ismail, Ajune Wanis Asari, Mohammad Khairul Shaleh Md Universiti Teknologi Malaysia Faculty of Computing Johor Malaysia Miit UniKL Kuala Lumpur Malaysia

ISBN: (纸本)9798350365191

Depth estimation on handheld devices can be highly beneficial for enhancing Augmented Reality (AR) applications. Depth estimation enables spatial awareness functionalities for a more realistic and immersive environment in the application such as occlusion handling, collision detection, and lighting. These improvements allow AR applications more engaging and practical, opening up new possibilities for education, navigation, gaming, and various other fields. However, performing depth estimation on handheld devices requires high computational processing. This paper presents a method to live stream RGBD depth sensor frame data to browsers in handheld devices using a WebRTCbased framework, therefore bypassing the device's computational limitations. The WebRTC-based framework also allows transmission on input from users like tapping the screen, thus the application can be controlled in real time as well. We detailed the flow and implemented the method using Unity Render streaming and ZED Mini depth sensor, demonstrating successful depth estimation and occlusion handling in an AR application. The results show that when the occlusion handling toggle is turned on, the depth of the scene is understood by the AR application and the virtual objects were correctly occluded by the real object, in which we use hand gestures. The hand gestures consist of open palm and grabbing gestures. The research concludes that the WebRTC-based Unity Render streaming framework can effectively integrate depth sensors with handheld devices that support HTML5 browsers, offering a new pathway for immersive AR experiences. The method is also robust with different depth sensors, as long as the depth sensor's camera feed can be displayed by the Unity game engine. © 2024 ieee.

关键词： Augmented reality

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Precise Wireless Charging in Complicated Environments 42

Precise Wireless Charging in Complicated Environments

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Yang, Wei Lin, Chi Dai, Haipeng Ren, Jiankang Wang, Pengfei Wang, Lei Wu, Guowei Zhang, Qiang Dalian Univ Technol Sch Software Technol Dalian 116024 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710000 Peoples R China Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116621 Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Wireless Rechargeable sensor Networks (WRSNs) have become an important research issue as it can overcome the energy bottleneck problem of wireless sensor networks. However, inaccurate discretization methods and imprecise charging models yield a huge gap between theoretical results and practical applications, making it difficult for wide adoptions. In this paper, we focus on designing a precise charging method for maximizing charging utility when line-of-sight (LOS) and none-line-of-sight (NLOS) charging cases exist in complicated environments. First, we design discretization methods for charging area and charging orientation for precisely constructing the charging model. Then, we develop a novel electromagnetic wave reflection model to describe the signal propagation model in the presence of obstacles. We formalize the mobile charging problem into a submodular function maximization problem which can be solved by a proposed algorithm with an approximation guarantee. Finally, extensive experiments and simulations demonstrate that our schemes outperform comparison algorithms by 31.45% on average in charging utility in complicated environments.

关键词： Wireless communication Wireless sensor networks Inductive charging Line-of-sight propagation Directional antennas Directive antennas Approximation algorithms

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Gray Wolf Optimization Algorithm to Enhance Data Aggregation in Wireless sensor Network 5

Gray Wolf Optimization Algorithm to Enhance Data Aggregation...

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5th international conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Loganathan, Sathyapriya Victoria Jancee, B. Senkamalavalli, R. Subbu Lakshmi, T.C. Srm Institute of Science and Technology Department of Computing Technologies Tamil Nadu Kattankulathur India St.Joseph's College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India East Point College of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Francis Xavier Engineering College Department of Information Technology Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350321425

Wireless sensor networks (WSNs) have become increasingly popular as distributed systems using small, lightweight nodes with limited resources for monitoring environmental conditions or measuring physical parameters. To minimize energy utilization, data aggregation can be employed to reduce the data quantity forward to the base station (BS). To solve these issues, a Gray wolf optimization algorithm (GWOA) is proposed to enhance data aggregation in WSN. Increasing the network lifetime, node reliability, and throughput with the selection of best cluster heads (CHs) utilizing the Gray Wolf Optimization (GWO) algorithm is the major objective of this research. This approach selects the CH by applying the GWO algorithm established on the node remaining energy, available bandwidth, and distance. The GWO-based clustering protocol minimizes dead nodes and energy utilization and raises the clustering rounds and throughput. The simulation results demonstrate that the increases the node reliability and network throughput. © 2023 ieee.

关键词： Energy efficiency

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Preserving Data Integrity and Security in IoT-Enabled Wireless sensor Networks: Employing an Intrusion Detection System strategy 1

Preserving Data Integrity and Security in IoT-Enabled Wirele...

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1st ieee international conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Vaithiyanathan, M. Jose, Naduvathezhath Nessariose Sasireka, C.S. Mishra, Pooja James, T. Prabahar Godwin Venu, Nookala Sri Sai Ram Engineering College Department: Information Technology India Regent Strategic Solutions Rochester United States Srm Institute of Science and Technology Department Of Computer Science and Engineering India Dy Patil Institute of Engineering Management and Research Pune India Sri Sairam Institute of Technolgoy Department Of Computer Science and Engineering India Centre for IoT Madhya Pradesh Gwalior474005 India

ISBN: (纸本)9798350377002

The proliferation of IoT-enabled wireless sensor networks (WSNs) has ushered in a multitude of applications but has also heightened concerns regarding data integrity and security. This underscores the critical necessity for robust Intrusion Detection systems (IDS) tailored explicitly for such environments. This study presents an innovative IDS framework designed to safeguard the integrity and security of data within -enabled. Our IDS framework introduces advanced machine learning techniques and anomaly detection algorithms to enable real-time monitoring and analysis, effectively identifying and mitigating potential threats. Through extensive experimentation and validation, we demonstrate the reliability and efficacy of our IDS in detecting various intrusion attempts while minimizing false alarms. Moreover, our framework incorporates adaptive mechanisms to address evolving threats and network dynamics, ensuring continuous protection against malicious activities. By enhancing the resilience of IoT-enabled WSNs against intrusions, our research contributes to bolstering trust and reliability in critical applications. © 2024 ieee.

关键词： Network intrusion

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