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An Efficient VHO Algorithm to Enhance QoS in internet of Vehicles with the Integration of 5G

An Efficient VHO Algorithm to Enhance QoS in Internet of Veh...

引用

2022 International conference on Electronics and Renewable systems, ICEARS 2022

作者： Pramod Kumar, P. Akshay, R. Sagar, K. Sr University Department of Computer Science and Artificial Intelligence Warangal India S R Engineering College Department of Computer Science and Engineering Warangal India Chaithanya Bharathi Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781665484251

In a de veloping country such as India, the intellection of smart city and the boom for a wide range of vehicles, internet of Vehicles (IoV) has gained a lot of consideration by furnishing numerous benefits, including traffic congestion control, smart parking, vehicle emergency and monitoring levels of pollution. Furthermore, IoV provides support for vehicles over internet aid communication. In order to have a better communication between Vehicle-to-Everything (V2X), an advanced network infrastructure is required. The currently available networks like 3rd generation (3G), 4th generation (4G) or long term evolution (LTE) are not adequate for these kinds of communications;There comes the 5th Generation (5G) cellular network into the picture. The 5G offers real-time crowd sourcing, higher data rates, low latency for transmission and sensing as a complementary base for information. In addition to the leading edge network infrastructure, the mobility of vehicles urges to have a perfect handover (HO) mechanism among heterogeneous networks. This paper discuss about the integration IoV with 5G and the importance of vertical handover (VHO) mechanism using an Artificial Intelligence algorithm and analyze its performance based on few of the parameters such as data transfer rate, transmission delay, mean throughput, packet delivery ratio (PDR) and quality of Service (QoS). © 2022 IEEE.

关键词： quality of service

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Smart Hospital Privacy Protection System Based On Cloud Computing Iot 4

Smart Hospital Privacy Protection System Based On Cloud Comp...

引用

4th International conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Li, Sen Luo, Dan Liu, Xin Luo, Rong School of Information Network Security Xinjiang University of Political Science and Law Xinjiang Uygur Autonomous Region Tumshuk City843900 China College of Intelligence and Computing Tianjin Ren'ai University Tianjin301636 China Changji University Xinjiang Changji831100 China

The swift evolution of information technology is catalyzing a transformative fusion between cloud-integrated internet of Things (IoT) and smart healthcare, poised to usher in revolutionary transformations within the medical sector. Through iot technology, various medical devices, sensors, and monitoring systems can connect and exchange data in real time, enabling remote monitoring, intelligent analysis, and personalized medicine. The confluence of the expanding internet of Things (IoT) and the blossoming smart healthcare sector is set to streamline medical resource allocation, uplift healthcare service quality, and markedly ameliorate patients' experiences in healthcare settings. At the same time, it also brings some challenges, such as data privacy protection, standardization and security issues, which need continuous scientific and technological innovation and policy support to solve. In this paper, the row index obfuscation Bloom filter is designed in the scenario of smart healthcare to protect the privacy of data. Compared with other schemes, the proposed scheme has better privacy protection and better performance, and the proposed scheme is secure. In a word, the combination of iot and smart healthcare is promoting the digital transformation and innovative development of the medical industry, and providing more intelligent and convenient medical services for people's health. © 2024 The Authors.

关键词： Access control internet Of Things Privacy Preserving Smart Hospital

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Agent Based Modelling and Simulation of Computer control systems for Steel Ingot Furnaces 23

Agent Based Modelling and Simulation of Computer Control Sys...

引用

7th International conference on Computer Science and Application Engineering, CSAE 2023

作者： Somo, Gabriel Noko Daniyan, Ilesanmi Afolabi Swanepoel, Jan Industrial Engineering Tshwane University of Technology Pretoria0001 South Africa Mechanical and Mechatronics Engineering Achievers University Owo Nigeria

ISBN: (纸本)9798400700590

To automate a manufacturing system for improved efficiency and quality of its output, a Programmable Logic controller (PLC) with internet of Things (IoT) need to be employed. At Company X, the furnaces employed for steel processing are not connected to PLC-IoT system, thus making the system less effective. This study employs the agent based modelling and simulation for the investigation of the performance of the PLC-IoT system using both quantitative analysis and a simulation model developed from the Anylogic software. A program placed in a computer control system at 20 °C was used to control the levels of the heat in the furnaces that are responsible for further processing of steel pipes. The results obtained indicated that manually operated furnaces run for approximately 5-8 hours while the ones automated with PLC-IoT system run for approximately 3-6 hours respectively. Thus, the integration of PLC-IoT system into the manufacturing system can result in considerable time effectiveness. © 2023 ACM.

关键词： internet of things

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Unsupervised Anomaly Detection in RS-485 Traffic using Autoencoders with Unobtrusive Measurement

Unsupervised Anomaly Detection in RS-485 Traffic using Autoe...

引用

IEEE International performance, Computing, and Communications conference (IPCCC)

作者： Chirupphapa, Pawissakan Hossain, Md Delwar Esaki, Hiroshi Ochiai, Hideya Univ Tokyo Grad Sch Informat Sci & Technol Tokyo Japan Nara Inst Sci & Technol Div Informat Sci Ikoma Nara Japan

ISBN: (数字)9781665480185

ISBN: (纸本)9781665480185

Remotely connected devices have been adopted in several industrial control systems (ICS) recently due to the advancement in the Industrial internet of Things (IIoT). This led to new security vulnerabilities because of the expansion of the attack surface. Moreover, cybersecurity incidents in critical infrastructures are increasing. In the ICS, RS-485 cables are widely used in its network for serial communication between each component. However, almost 30 years ago, most of the industrial network protocols implemented over RS-485 such as Modbus were designed without security features. Therefore, anomaly detection is required in industrial control networks to secure communication in the systems. The goal of this paper is to study unsupervised anomaly detection in RS-485 traffic using autoencoders. Five threat scenarios in the physical layer of the industrial control network are proposed. The novelty of our method is that RS-485 traffic is collected indirectly by an analog-to-digital converter. In the experiments, multilayer perceptron (MLP), 1D convolutional, Long Short-Term Memory (LSTM) autoencoders are trained to detect anomalies. The results show that three autoencoders effectively detect anomalous traffic with F1-scores of 0.963, 0.949, and 0.928 respectively. Due to the indirect traffic c ollection, o ur method can be practically applied in the industrial control network.

关键词： anomaly detection autoencoder industrial control system rs-485 security univariate time series

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Federated Reinforcement Learning for Automated LoRaWAN Management in Industrial IoT 20th

Federated Reinforcement Learning for Automated LoRaWAN Manag...

引用

20th EAI International conference on Mobile and Ubiquitous systems - Computing networking and Services (EAI MobiQuitous)

作者： Ivoghlian, Ameer Salcic, Zoran Wang, Kevin I-Kai Univ Auckland Auckland 1010 New Zealand

ISBN: (纸本)9783031639883;9783031639890

The scale of wireless networks is growing rapidly to support next generation industry 5.0 applications. LoRaWAN offers features such as low power consumption and long communication range, beneficial in many industrial applications. However, this comes at the cost of low data rates and link margins that rely on coding gain and careful network planning. These qualities make LoRaWAN networks vulnerable to interference and data-loss, which are particularly problematic in large-scale and mobile networks. It is vitally important that LoRaWAN networks are automatically and adaptively managed, to ensure that resources are optimally allocated, while satisfying multiple application requirements. In this paper, a novel multi-agent federated reinforcement learning framework is designed to enable knowledge sharing across multiple agents, and to resolve the issue of limited sampling coverage deep reinforcement learning. The goal is to allow individual node agents to adaptively control their network parameters to satisfy their own application requirements, while ensuring fair access across all nodes. The proposed method is evaluated against a non-federated approach. The results show that the proposed federated reinforcement learning approach can overcome the cold-start problem when new devices join a network. The proposed approach also demonstrates the ability to support mobile nodes travelling through locations, with changing network conditions, while maintaining communication performance.

关键词： Federated Learning Federated Reinforcement Learning LoRaWAN Industrial internet of Things

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IoT Based Condition Monitoring and control of Induction Motor Using Raspberry Pi 13

IoT Based Condition Monitoring and Control of Induction Moto...

引用

13th Power Electronics, Drive systems, and Technologies conference (PEDSTC)

作者： Dehbashi, N. SeyyedHosseini, M. Yazdian-Varjani, A. Tarbiat Modares Univ Fac Elect & Comp Tehran Iran

ISBN: (纸本)9781665420433

Induction motors, especially three-phase induction motors, are widely used in the industry due to their outstanding features compared to others. Remote drive inverters are one of the new areas for increasing the efficiency and reliability of motors. With the fast advancement of technology and the expansion of the internet network, the internet of Things has become one of the main ways to communicate with different devices. The number of devices connected to the internet has increased, especially in industrial environments that lead to better product control and monitoring. Sending system monitoring information with IoT allows processing, storage and monitoring. The use of IoT in the control and monitoring of electric motors leads to the formation of smart drives. The benefits of using IoT include reducing maintenance costs, increasing reliability, optimizing motor performance, and improving failure prediction accuracy. In this project Raspberry Pi board is used as processor and two current and voltage sensors for monitoring electrical features and controlling motor speed Also temperature sensor for detecting failures. The data is collected by the Raspberry Pi and sent to the server and then stored in the database and after processing, the necessary instructions are sent back to the Raspberry Pi.

关键词： Induction motor Smart Inverter internet of things Raspberry Pi Condition Monitoring

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Optimal Resource Allocation Scheme for RIS-Assisted Vehicular networks 43

Optimal Resource Allocation Scheme for RIS-Assisted Vehicula...

引用

43rd Chinese control conference, CCC 2024

作者： Chen, Wenxuan Su, Jiawei Liu, Zhixin Yanshan University School of Electrical Engineering Qinhuangdao066004 China Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Hebei Province Qinhuangdao066004 China

ISBN: (纸本)9789887581581

Deploying reconfigurable intelligent surfaces (RIS) in vehicular networks can effectively improve the quality of wireless channel and increase network throughout, which is realized by optimizing the phase shifters. However, the dynamic network environment and complex multi-user interference seriously affect network reliability. Enhancing transmission powers blindly cannot solve the interference problem but also reduces the transmission efficiency of the RIS-based vehicular networks. To address the above challenges, this paper proposed a joint optimization scheme of transmission beamforming and phase shift. Based on the block coordinate descent (BCD) theory, this paper decomposed the scheme into two sub-problems: transmission beamforming optimization and RIS phase shift optimization, and the joint optimization algorithm was developted. Simulation results have demonstrated that the transmission rate has been improved with the assistance of RIS, with the multi-user interference effect being well-depressed. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Resource allocation

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A hybrid algorithm based on ABC algorithm and its application in Hpcf pump fuzzy control 5

A hybrid algorithm based on ABC algorithm and its applicatio...

引用

5th International conference on Computer Communication and network Security, CCNS 2024

作者： Xu, Lei Xu, Yang Sun, Ming Colledge of Computer and Control Engineering Qiqihar University Qiqihar161006 China ZhongKeWoYe Jiangsu Biological Co. Ltd. Suqian China

ISBN: (纸本)9781510681842

The Artificial Bee Colony (ABC) algorithm excels in solving optimization challenges but faces slow convergence, low precision, and local optima *** mitigate these limitations, a novel hybrid optimization algorithm, termed the IABC algorithm, was developed to improve the global search capability and speed up convergence. Initially, the employed bee phase adopts a sine law-based dimension-changing strategy to boost search and exploitation capabilities, accelerate convergence, and prevent premature convergence;in the onlooker bee phase, it follows the global optimum, altering its step size-large for broad searches in the early stages and small for precise searches later on. Finally, in the scout bee phase, the hunting strategy from the SWO algorithm(Spider Bee Optimization) is utilized to strengthen global and local search abilities. Experimental conducted on the CEC2017 dataset confirm enhanced strategies' success and performance efficiency. Comparisons with other ABC algorithms and competitive algorithms show that the IABC significantly enhances the performance of the ABC. In nearly all test functions, the IABC attained the superior solution quality, quickest rate of convergence, and most robust performance. Its effectiveness is further proven by successful application in pulsation suppression for the HPCF(high-pressure constant flow) pump pulse systems, indicating its potential for solving diverse optimization problems. © 2024 SPIE.

关键词： Fuzzy control

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Security-Aware Optimal Cluster Head-Based Energy-Efficient Data Transmission on Wireless Sensor network

Security-Aware Optimal Cluster Head-Based Energy-Efficient D...

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International conference on Business Intelligence and Data Analytics, BIDA 2024

作者： Bharath, A.D. Revathy, N. Ph.D Research scholar Department of Computer Science Hindusthan College of Arts and Science Coimbatore India Professor Department of Computer Application Hindusthan College of Arts and Science Coimbatore India

ISBN: (纸本)9789819777167

Wireless sensor networks, or WLANs, are the networks most essential to the development of many internet of Things (IoT)-based applications. These intelligent gadgets do, however, have limitations in processing, memory, energy, and calculation. Moreover, attaining quality of Service (QoS) with secure data transfer is one of the main obstacles for WSNs. To improve security and quality of service while using less energy in wireless sensor networks (WSNs), this paper suggests effective energy-aware secure data transmission models. Initially, the network randomly deploys the sensor nodes (SNs), and they register with the base station (BS). Next, the Low-energy Adaptive Clustering Hierarchy (LEACH) process is applied to choose the cluster head. Once the cluster head has been selected, the clusters are organised according to the cluster head. After that, the Enhanced Coronavirus Mask Protection Algorithm (ECMPA) is used to enable the best routing procedure. The Oppositional Function (OF) and Coronavirus Mask Protection Algorithm (CMPA) are combined in the suggested technique. This hybrid algorithm takes into account multiple measurements and the secure trust parameter to offer the best possible routing process. The data are then sent using the shortest path possible. The model’s performance efficiency above current methods for security, quality of service, and energy efficiency (EE) are demonstrated by the findings. NS2 is used in the implementation of the suggested method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Coronavirus

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internet of Things Enabled ML for Air quality Assessment: Systematic Review 7

Internet of Things Enabled ML for Air Quality Assessment: Sy...

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7th International conference on Intelligent Computing and control systems, ICICCS 2023

作者： Veera Manikandan, S. Abilash, Y. Hari Prasanth, S. Alfred Daniel, J. Santhosh, R. Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

A severe and pervasive environmental problem that affects the entire planet is Air Pollution (AP). Numerous researchers have focused on these issues while keeping human health in mind. One of the best methods to educate people about major health issues and safeguard human health from air pollution is through information about air quality predictions. Air pollution is one of the most difficult environmental issues, and it affects many major cities. Real-time monitoring of pollution data can help local officials assess the present state of the city's traffic and reach well-informed decisions. In order to correctly estimate the pollutant concentrations, it is necessary to have an early system for monitoring and measuring the amount of AP using the Air quality Index. Incorporating internet of Things (IoT)-based devices may significantly change the AQ forecast dynamically, hence enhancing the AQ forecast. The accuracy and cost of the Both the AP prediction that is mentioned and the evaluation of it using various known methodologies are quite low. While AP prediction is still permitted in some sectors, machine learning (ML) algorithm development is expanding swiftly and looking into almost all fields and applications. This paper highlights numerous ML research projects related to AP monitoring and prediction using IoT sensor data in the context of diverse cities. This paper also summarizes historical and current data based on AQ prediction models, methods, and methodologies, examines current research methodology, the advantages and disadvantages of AQ prediction, as well as the challenges related to real-time AQ monitoring and prediction. © 2023 IEEE.

关键词： internet of things

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