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检索条件"任意字段=Conference on Internet Quality and Performance and Control of Network Systems"

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Smart Visual Pollution Detection System

Smart Visual Pollution Detection System

引用

Advanced Innovations in Smart Cities (ICAISC), International conference on

作者： Rothana Alsolami Rasha Atwah Ranad Alajlani Sara Alhajaili Department of Computer and Network Engineering College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

As Saudi Arabia moves forward with its Vision 2030 initiative to improve the quality of life and services for its people, visual pollution continues to have a negative impact on the environment. However, assessing and addressing visual pollution in cities remains a challenging task due to its subjective nature and complexity. One of the main challenges is the lack of powerful and reliable intelligent systems for detecting visual pollution. To tackle this issue, we have invested our efforts in developing a cost-effective intelligent system using advanced technologies like the internet of Things (IoT) and computer vision. This system will help detect and monitor visual pollution, including items such as water cans, paper, and plastic cups. Our smart system uses sensors like cameras to collect data and then analyzes it to display the information on a user-friendly control panel for administrators to monitor the area under study. The system has been successfully tested under various scenarios and has shown promising accuracy rates, reaching up to 87% in detecting recyclable materials. We believe that there are numerous opportunities to further enhance the performance of future designs.

关键词： Visualization Pollution Accuracy Smart cities Cameras Real-time systems Water pollution internet of Things Intelligent systems Monitoring

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Blockchain-Based Access control Mechanism for IoT Medical Data 19th

Blockchain-Based Access Control Mechanism for IoT Medical Da...

引用

19th International conference on Advanced Intelligent Computing Technology and Applications (ICIC)

作者： Yang, Tianling Huang, Shuanglong Ma, Haiying Guo, Jiale Nantong Univ Informat Sci & Technol Nantong Jiangsu Peoples R China Nanyang Technol Univ Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9789819947546;9789819947553

With the proliferation of medical internet of Things (IoT) devices that collects sensitive healthcare data, access control is more crucial than ever to ensure medical IoT data from unauthorized use. The security and privacy of medical records must be addressed rigorously. The security protocols and distributed system architecture are designed for effectively implementing the access control mechanisms to prevent privacy leakage and insecure data sharing. Blockchain is a promising candidate for strengthening the security and privacy needs of IoT medical systems. This paper proposes a blockchain-based access control mechanism for IoT medical data. Medical IoT data can be encrypted and stored off-chain in a distributed file storage system. Data access transactions only record the address of the data ciphertext and the encryption-key ciphertext into the blocks, which can significantly improve the scalability of the blockchain and strengthen privacy protection of medical data. The immutable nature of blockchain ensures the integrity and authenticity of medical data. Our BAC-IOMT scheme embeds the access policies into smart contracts to execute data access control mechanism. Finally, this scheme is proven to be secure and its performance efficiency, data volume and delay are analyzed in detail, the experimental results show that it is efficient and feasible.

关键词： IoT Access control Blockchain Smart Contract Medical Data

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Implementation of Deep Convolution Neuro-Fuzzy network to Plant Disease Detection, Risk Assessment, and Classification 2

Implementation of Deep Convolution Neuro-Fuzzy Network to Pl...

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2nd International conference on Sustainable Computing and Data Communication systems, ICSCDS 2023

作者： Koshariya, Ashok Kumar Ashraf, Mohd. Shaikhul Nigam, Rashmi Kumar, T. Sampath Awasthi, Deepak Kumar. Elavarasan, G. Lovely Professional University School of Agriculture Department of Plant Pathology Punjab Jalandhar India Bandipora Kashmir India Department of Plant Pathology Uttar Pradesh India Sr University Department of Computer Science & Artificial Intelligence Warangal India Khandelwal College of Management Science and Technology Department of Computer Science Uttar Pradesh Bareilly India Excel College for Commerce and Science Department of Computer Applications Namakkal Tamilnadu Komarapalayam India

ISBN: (纸本)9781665491990

Indian agriculture drives the economy. Sickness is common in plants exposed to several environmental conditions. This lowers crop quality. Due to recent weather changes, farmers' biggest issue is maximizing output quality and quantity. Diagnosing and treating crop diseases quickly maximizes agricultural productivity. Illnesses can reduce tomato crop yields, lowering farmers' income. To treat and control tomato leaf diseases, proper identification is crucial. Deep learning improved recognition accuracy. Artificial intelligence incorporates deep learning. Due to its self-directed learning and feature extraction benefits, academic and industry circles have been discussing it recently. Learning-based methods in plant leaf disease detection can speed up research, improve feature extraction, and loosen disease spot feature selection. To improve identification accuracy, deep learning now uses fuzzy rules to represent and manage fuzzy information. Using a deep neuro-fuzzy neural network, we classify rice plant illnesses. To extract complex features, the neuro-fuzzy network uses a fuzzy inference layer and a fuzzy pooling layer. Then classify them in the fully linked layer. A huge dataset of 8 types of infected and uninfected rice plant photos yielded a 96.9% identification accuracy for the moa del. Three performance indicators were also used. The trials show the benefits of employing NFNHDL to diagnose rice diseases. © 2023 IEEE.

关键词： Fuzzy inference

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23rd International Multidisciplinary Scientific Geoconference, SGEM 2023 - conference Proceedings of Selected Papers in Informatics, Geoinformatics and Remote Sensing

23rd International Multidisciplinary Scientific Geoconferenc...

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23rd International Multidisciplinary Scientific Geoconference: Informatics, Geoinformatics and Remote Sensing, SGEM 2023

ISBN: (纸本)9786197603606

The proceedings contain 43 papers. The topics discussed include: applications of software tools for hydrogen safety studies;approach to the visualization of timelines of images generated by forecasting models;black box model as a possibility to model out the combustion process in an engine;comparing embedded solutions for mechanical vibration analysis of a 3D-printed cycloidal gearbox;comparison of the performance of different neural network architectures and pre-trained neural networks for the classification of forest flora and fauna;computing platform for integrating wireless heterogeneous networks into industrial internet of things systems;control system reducing energy consumption of manipulator drives based on reinforcement learning;and cyberterrorism and social engineering - methods and countermeasures.

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Computational Analysis of an Optimized 32 channel 320 Gbps DWDM Hybrid Free Space/ Fiber Optic Communication System with Cascaded Dispersion Compensating Fiber

Computational Analysis of an Optimized 32 channel 320 Gbps D...

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2023 IEEE International conference on Next Generation Electronics, NEleX 2023

作者： Bhattacharjee, Rituraj Dey, Priyanka Kar, Aparupa Saha, Ardhendu Manipal Institute of Technology Department of Instrumentation & Control Engineerig Karnataka Manipal576104 India Department of Electronics & Instrumentation Engineering NIT Agartala Tripura Agartala799046 India Department of Electrical Engineering NIT Agartala Tripura Agartala799046 India

ISBN: (纸本)9798350319088

In the current trend of internet of Things (IoT) and 5G based communication networks, Free Space Optical (FSO) Communication endorses high speed bit rate 5G communication as well as offers reliable massive scale connectivity in IoT networks. In practical scenarios, a fiber optic cable link at the receiver end is often required leading to a hybrid FSO/ Fiber Optic (FSO/FO) network. The possibility and advantages of inclusion of Dispersion Compensating Fiber (DCF) in the connecting fiber link to the receiver unit in Dense Wavelength Division Multiplexing (DWDM) based hybrid FSO/FO networks has been explored in this work. With optimized parameter values for dual FSO channels and DCF used in Optisystem software, for clear weather, the maximum link ranges have been found as 34 Km and 8 Km without and with Misalignment Losses (ML) respectively. The corresponding values for Hazy weather were obtained as 10.5 Km without ML and 6.2 Km considering ML attenuation. Maximum quality factors (Q factor) of around 7.5 and 6.5 were obtained for both clear and hazy weather scenarios respectively. The performance of the developed hybrid FSO/FO network was found to be superior in terms of link range than existing architecture. © 2023 IEEE.

关键词： Fiber Bragg gratings

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Optimizing IoT Congestion control Through Priority Based Rate Limiting Technique to Prevent Flooding Attacks

Optimizing IoT Congestion Control Through Priority Based Rat...

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International conference on Circuits, Communication, control and Computing

作者： Anitha P H S Vimala Shreyas J Dept. of CSE UVCE Bengaluru India Dept. of Information Technology Manipal Institute of Technology Bengaluru

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528546

In terms of technology, internet of Things (IoT) research has grown dramatically. It simultaneously attempts to transmit data from many nodes because every node is connected to another. The network becomes congested as a result of the high load. A malicious node can also cause congestion in the 6LoWPAN network by flooding superfluous data. Using a low data rate and low power network, IPV6 packets are transmitted via the 6LoWPAN protocol. The network's overall performance decreases as a result of this congestion. Therefore, the priority-based rate-limiting (PBRL) approach is suggested as a way to prevent this. by giving nodes varying priority levels and putting in place the token bucket algorithm, which gives a token to every authorized user. In doing this, the packets are transmitted according to the priority of each node, thus separating the malicious and authorized nodes. This process guarantees the best possible resource allocation and minimizes network overhead. A performance comparison is performed using the IFNoT technique, which has been implemented and simulated on the Cooja simulator.

关键词： Limiting Protocols Simulation Circuits quality of service Throughput internet of Things Data communication Resource management

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Recent Management Trends Involved with the internet of Things in Indian Automotive Components Manufacturing Industries 5

Recent Management Trends Involved with the Internet of Thing...

引用

5th International conference on Contemporary Computing and Informatics, IC3I 2022

作者： Syed, Farhat Ali Bargavi, N. Sharma, Abhishek Mishra, Abhishek Nagpal, Pooja Srivastava, Aparna Madhya Pradesh Indore India Bharat Institute of Higher Education and Research Demartment of Management Studies Tamilnadu Chennai India Lovely Professional University Mittal School of Business Punjab Phagwara India Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun India International School of Business Excellence ISME Department of Management Studies Karnataka Bangalore India Lloyd Institute of Engineering and Technology Department of MCA Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350398267

The development of smart manufacturing systems is being driven by a variety of diverse needs for the dependability of equipment and the prediction of quality. In order to accomplish this objective through the use of machine learning, a wide range of approaches are being investigated. The management and protection of one's company's data presents yet another challenging aspect of doing business. In order to cope with fraudulent datasets, machine learning and internet of things technologies were utilized. These technologies were used to protect system transactions and manage a dataset. Because of this, we were able to find solutions to the problems that we had previously discussed. The gathered information was organized and examined with the help of big data techniques. The internet of Things system was constructed using the Hyperledger Fabric platform, which is a private computer network. In addition, a hybrid prediction strategy was utilized for the defect diagnostic as well as the defect forecasting. The latest machine learning techniques were utilized in order to model the complexity of the environment and estimate the genuine positive ratio of the quality control system. The quality control of the system was evaluated using these pieces of data. © 2022 IEEE.

关键词： internet of things

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Intrusion Detection System (IDS) of Multiclassification IoT by using Pipelining and an Efficient Machine Learning 9

Intrusion Detection System (IDS) of Multiclassification IoT ...

引用

9th International conference on Engineering and Emerging Technology, ICEET 2023

作者： Hazim, Layth Rafea Jasim, Abdulrahman Ahmed Ata, Oguz Ilyas, Muhammad College of Computer Science and Mathematics Tikrit University Tikrit Iraq Altinbas University Dept. of Electrical and Computer Engineering Istanbul Turkey College of Engineering Al-Iraqia University Baghdad Iraq Altinbas University Istanbul Dept. of Software Engineering Turkey Altinbas University Istanbul Dept. of Computer Engineering Turkey

ISBN: (纸本)9798350316926

The internet of Things (IoT) has quickly advanced and been incorporated into many different fields. With the use of IoT technology, gadgets can receive, process, and send data automatically. IoT has been rapidly accepted in many important fields since it makes life easier and increases service quality, yet it still faces significant privacy and security problems. An Intrusion Detection System (IDS) could be implemented as a security feature to protect IoT networks from a variety of cyberattacks. This study suggests using IDS to defend against a wide range of cyberattacks on IoT systems. The suggested approach makes use of the Multi-layer Perceptron (MLP) as well as Extra Trees (ExT) as efficient algorithms of classification. Also, the study uses the pipeline to put together several cross-validated phases while selecting various parameters to increase the detection rate. One dataset is utilized for evaluating and analyzing the performance outcomes so as to validate the efficiency of the suggested IDS approach. The evaluation findings show that the suggested IDS methods may greatly increase detection performance results concerning accuracy rate, precision, F1-score, and recall while also improving detection efficiency. © 2023 IEEE.

关键词： network security

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Image Dehazing Using Generic Model Agnostic Convolutional Neural network 7th

Image Dehazing Using Generic Model Agnostic Convolutional Ne...

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7th International conference on Inventive Communication and Computaional Technologies, ICICCT 2023

作者： Khurana, Gurditya Garodia, Rohan Saranya, P. Department of Computing Technologies SRM Institute of Science and Technology Chennai Kattankulathur India

ISBN: (纸本)9789819951659

The most frequent environmental factor that affects image quality and image analysis is fog. A coherent generative approach to image organization is suggested in this study. We require the construction of a fully convolutional neural network in order to recognize the haze pattern in the input photo and restore a clear, fog-free image. The suggested method is agnostic because it doesn’t take into account air scattering models. Surprisingly, even SOTS outdoor images created using atmospheric scattering models outperform current state-of-the-art image decluttering techniques. Many modern apps use visual data analysis to find patterns and make decisions. Intelligence and control systems are some instances where clear pictures are crucial for precise outcomes and dependable performance. Environmentally generated distortions, the most frequent haze and fog, could, however, have a considerable impact on such systems. Therefore, the challenge of recovering high-quality images from their fuzzy equivalents has received attention in the vision community. The dehaze problem is the common name for that issue. This work proposes a dehazeNN that simply focuses on creating a blur-free version of the input picture, offering a novel and more flexible approach to the dehaze problem. It constructs an encode and decode architecture using the most recent developments in deep learning in order to recover the clear image, while entirely removing the estimation problem. The method might also be able to spot intricate haze patterns that the atmospheric scattering model missed, which were present in the training data. A convolutional neural network called the generic model-agnostic convolutional neural network (GMAN) has been proposed for the elimination of haze and the restoration of clear images. An end-to-end deep learning system for photo denoising uses encoder-decoder networks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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Design and Implementation of Centralized Timesensitive network controller Cluster System

Design and Implementation of Centralized Timesensitive Netwo...

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Electronics and Communication, network and Computer Technology (ECNCT), International conference on

作者： Xuyang Zhao Jun Zhu Wenjiao Yang Donghui Lu Research Center for Intelligent Manufacturing Computing Zhejiang Lab Hangzhou China

ISBN: (数字)9798350366143

ISBN: (纸本)9798350366150

With the development of the new generation of information network technology and the massive data integration generated by the internet of Everything, the management planning of data is becoming more and more reasonable. The data management plane is configured and issued to the data service plane, which can meet the data transmission requirements of different application scenarios. Most network configurations need to be performed during network downtime or when the device is offline, which makes it difficult to meet the requirements for application scenarios such as industrial control. Time- sensitive network (TSN) introduces centralized network configuration (CNC) and centralized user configuration (CUC) through IEEE 802.1Qcc to realize the dynamic configuration of the network and flexibly configure new devices and data flows when the network is running. This paper designs a centralized time-sensitive network controller cluster system to configure the resources of the data service plane of time-sensitive network devices, optimize the resource utilization of the network, and realize flexible networking of the network; based on the distributed cluster technology characteristics of the ONOS open source controller, the network controller is designed and deployed with high reliability, and the controller fault tolerance and elasticity mechanism are realized to solve the reliability problem caused by the single point failure of the TSN network controller.

关键词： performance evaluation Computer network reliability Industrial control Fault tolerant systems Configuration management Reliability engineering control systems Planning Resource management internet of Things

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