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Smart control of Traffic Lights using Artificial Intelligence 15

Smart Control of Traffic Lights using Artificial Intelligenc...

引用

15th international conference on Advances in computing, control, and Telecommunication Technologies, ACT 2024

作者： Pushpa, P. Kumar, Racha Phani Sai, Miniga Prem Sanjay, Minukuri Department of Electronics and Communication Engineering Vignana Bharathi Institute of Technology Telangana Ghatkesar501301 India

ISBN: (纸本)9798331300579

The increasing number of vehicles and urban population has made traffic congestion a serious problem. In addition to creating traffic jams and driver frustration, this issue raises fuel consumption and pollutes the air. Although congestion is a problem everywhere, megacities get the worst of it. The increasing traffic volume emphasizes how crucial real-time road traffic density estimations are to improved signal control and effective traffic management. The management of traffic flow is largely dependent on traffic controllers, and in order to keep up with demand, traffic control systems must be optimised. Our suggested method uses artificial intelligence (AI) and image processing to determine traffic density utilising real-time video feeds from traffic intersections. It also concentrates on creating algorithms to modify traffic light timings according to vehicle density, which will lessen traffic, facilitate quicker transit, and cut down on pollution. © Grenze Scientific Society, 2024.

关键词： Traffic congestion

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Harnessing Medical Imaging Applications: Survey on 3D Deep Learning Models for Image Segmentation 3

Harnessing Medical Imaging Applications: Survey on 3D Deep L...

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3rd international conference on communication, control, and Intelligent Systems, CCIS 2024

作者： Nambiar, Rajashree Nanjundegowda, Raghu Dept of Electronics and Communication Bengaluru India Dept of Robotics and Ai Engineering Nitte India Dept of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798331528201

The domain of 3D medical image segmentation has progressed markedly with the incorporation of deep learning methodologies, offering critical instruments for accurate and quick examination of intricate medical pictures. Various research has created 3D convolutional neural networks (CNNs) designed to segment diverse anatomical and pathological features, tackling specific issues such as high dimensionality, class imbalance, and computing requirements. Innovative models such as DeepMedic, which implemented a multiresolution strategy for brain lesion identification, together with other U-Net adaptations, have attained remarkable outcomes in tumor and organ segmentation through the integration of contextual and spatial data. Recent advancements encompass models employing large-kernel (LK) attention modules, transformer-based architectures, and hybrid approaches such as UNETR++ with Efficient Paired Attention, all enhancing accuracy while optimizing computing efficiency. These developments highlight the potential of 3D deep learning for clinical applications;yet, challenges such as restricted data availability, substantial annotation expenses, and generalizability across varied datasets persist as avenues for additional investigation. © 2024 IEEE.

关键词： Convolutional neural networks

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An Improved BBR Algorithm with Adaptive Congestion control for LEO Satellite Networks

An Improved BBR Algorithm with Adaptive Congestion Control f...

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2024 international conference on Cloud and Network computing, ICCNC 2024

作者： Wang, Zhiyi Zhao, Ya Han, Wei Jin, Fan Lan, Lixin Lu, Haitao Chen, Chen State Grid JiLin Province Electric Power Company Limited Information Changchun China Xidian University School of Telecommunications Engineering Xi'an China Xi'An Beilin University-Based Innovation Group Co. Ltd. Xi'an China National Key Laboratory of Science and Technology on Space Microwave Xi'an China Ningbo Joynext Technology Corporation Joynext Ningbo China Science and Technology on Communication Networks Laboratory Shijiazhuang050000 China Xidian University Xidian Hangzhou Institute of Technology Hangzhou China

ISBN: (纸本)9798350367805

Low Earth Orbit (LEO) satellite networks are favored for their global coverage, low latency, and geographical flexibility, but they also face challenges of high dynamism in network topology and congestion control. To address these issues, this study introduces an improved BBR congestion control algorithm (Deep-BBR) based on traffic prediction. The algorithm integrates Long Short-Term Memory networks, Graph Convolutional Networks, and attention mechanisms to accurately predict bandwidth utilization and dynamically adjust pacing gains. Experimental results show that the Deep-BBR algorithm significantly outperforms the traditional BBR algorithm in effective throughput, latency, and in-flight data management, effectively enhancing the communication performance and stability of LEO satellite networks. This improvement offers a more efficient and intelligent solution for congestion control in LEO satellite networks. © 2024 IEEE.

关键词： Satellite communication systems

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The smart Cross-Layer Design for Congestion control in Wireless Networks 15

The smart Cross-Layer Design for Congestion Control in Wirel...

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15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Giri, Rakesh Kumar Manju Bargavi, S.K. Kusum, Kriti Mishra, Abhinav Dhabliya, Dharmesh Jaison, B. Sunrise University Department of Computer Science & Engineering Alwar301028 India University Department of Computing Sciences And Information Technology Karnataka Bangalore India Symbiosis International University Department of Communication Design Pune India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Vishwakarma Institute of Technology Department of Information Technology Maharashtra Pune India R.M.K.Engineering College Department of Computer Science and Engineering Kavarapettai601206 India

ISBN: (纸本)9798350370249

The clever pass-layer layout for congestion management in wireless networks is a complete approach that leverages the interaction between community layers to develop efficient, dependable, and cozy Wi-Fi networks. This design combines the transport and MAC (media access control) layer protocols, which include TCP (transmission manage protocol) and IEEE (Institute of Electrical and Electronics Engineers) 802.11, respectively, so that it will manage the flow of records and decrease congestion. It considers both packet-stage information, including packet arrival, inter-packet arrival, and packet size, as well as bodily layer parameters, including channel country information, multi-user variety, and interference. Also, it addresses the ISPs' necessity of changing transmission charges and granting the proper stability among throughput and honest distribution of assets to defend different programs. This layout should respond to modifications within the network quickly and efficiently to obtain the favored quality of service (satisfactory service). Additionally, the cross-layer layout needs to be flexible and sufficient to be extended to modern-day and future communique networks while configurable to specific varieties of networks for better deployment. © 2024 IEEE.

关键词： Combines Information Management Modifications Networks

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Lightweight Deep Learning Approach for Monkeypox Detection 15

Lightweight Deep Learning Approach for Monkeypox Detection

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15th international conference on Advances in computing, control, and Telecommunication Technologies, ACT 2024

作者： Babu, Panguluri Vinodh Panguluri, Sumanth Kumar Patnala, Madhukumar Vasanthi, Ponduri Basheera, Shaik Rao, V. Venkata Department of Electronics and Communication Engineering Bapatla Engineering College Andhra Pradesh Bapatla522102 India Department of Electronics and Communication Engineering Eswar College of Engineering Narasaraopet Andhra Pradesh Guntur522601 India Department of Electronics and Communication Engineering Narasaraopeta Engineering College Narasaraopet Andhra Pradesh Guntur522601 India

ISBN: (纸本)9798331300579

Monkeypox is a rare viral disease that can cause severe illness in humans. Early and accurate detection of monkeypox is critical for the timely treatment and prevention of its spread. In recent years, convolutional neural networks (CNNs) have emerged as powerful image recognition tools. This paper presents a study on the use of a lightweight CNN model for monkeypox detection based on skin lesion images. We ran our experiments on a monkeypox skin lesion images dataset, and precision, recall, F1-score, and accuracy were 93%, 92%, 92%, and 93.12%, respectively. Finally, we evaluated the monkeypox skin lesion dataset's performance using sensitivity, specificity, BAS (Balanced Accuracy Score), and MCC (Matthew's Correlation Coefficient) parametric and achieved 95%, 89%, 92.46 %, and 85.15 % respectively. These promising results, imply that the proposed model is appropriate for mass screening by health practitioners. © Grenze Scientific Society, 2024.

关键词： Convolutional neural networks

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CC Link IE Based Remote Monitoring and control of Windmills Using Slot Type controller 10

CC Link IE Based Remote Monitoring and Control of Windmills ...

引用

10th international conference on Advanced computing and communication Systems, ICACCS 2024

作者： Jagatap, Govind Vishwanath Ingale, Sanjaykumar Patil, Deepak T. Mane, Atish Bandpatte, Sagar Chandu Hariharan, R. Bharati Vidyapeeth College of Engineering Department of Mechanical Engineering Navi Mumbai400614 India Sanjay Ghodawat University Department of Mechanical Engineering Kolhapur India Bharati Vidyapeeth college of Architecture Navi Mumbai India Bharati Vidyapeeth College of Engineering Department of Mechanical Engineering Pune Lavale India Bharati Vidyapeeth Deemed to be University College of Engineering Department of Chemical Engineering Pune India Sri Eshwar College of Engineering Department of Electrical and Electronics Engineering Coimbatore641 202 India

ISBN: (纸本)9798350384369

There are millions of wind mills are operated in the world and producing the electricity to meet out the demand. Generation of electricity and the transmission of the same is an easy one to all the power sector companies or power engineers. But the monitoring of windmills from the remote location and exchanging the data between the control station and the windmill is somehow tedious task. Even though the wireless communication and SCADA are implemented in most of the windmills, the lack of speed or data transmission and acquisition of real time data without any dead band is a challenging one. In ordered to over this drawback, CC-Link IE based wired transmission is introduced. It uses the modular master controller called 'R04 CPU', CC-Link networking module and few remote I/O Modules near the windmill station. It reduces the loss of data and improves the communication speed, data handling capacity and security. © 2024 IEEE.

关键词： SCADA systems

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An Intelligent Terminal for Safety Production Based on AI Video Analysis

An Intelligent Terminal for Safety Production Based on AI Vi...

引用

2023 IEEE international conference on Electrical, automation and Computer Engineering, ICEACE 2023

作者： Zhang, Mingzuo Zhang, Weiwei Wang, Jianping Zhou, Yang Duan, Weidong Yan, Jinsong Wang, Hongwei Li, Haotian Beijing Gas Group Company Limited Beijing100034 China

ISBN: (纸本)9798350309614

The intelligent security and management of site construction safety is an important goal of building 'smart site'. The safety production intelligent terminal device designed in this paper is an intelligent terminal that can realize the functions of AI edge computing and central gateway, and can be closely linked with the construction site video surveillance, automation equipment, mobile terminals and other equipment to realize the safety management of construction personnel, construction equipment and construction site perimeter. It also has the ability to link more other functional devices in the architecture, and can match different kinds of regulatory cloud platforms and mobile apps to meet users' needs for integrated management and control of background and mobile terminals. © 2023 IEEE.

关键词： AI video analysis Edge computing Safe production smart construction site

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Verilog-A Based 8-Bit Pipeline ADC Tailored for Low Power Performance and High-Speed Operation in 90 nm Technology 1

Verilog-A Based 8-Bit Pipeline ADC Tailored for Low Power Pe...

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1st IEEE international conference on Electronics, computing, communication and control Technology, ICECCC 2024

作者： Shohal, Amit Kaur, Jasbir Department of Electronics & Communication Engineering Chandigarh India

ISBN: (纸本)9798350371802

This research delves into the intricate realm of designing and fine-tuning of an 8-bit pipeline Analog-to-Digital-Converter (ADC), navigating the delicate balance between power efficiency and speed optimization. The chosen pipeline ADC architecture offers a promising avenue for achieving superior resolution while managing power consumption effectively. Through innovative strategies tailored to mitigate power drain and speed constraints inherent in conventional pipeline ADCs, this study pioneers a novel approach. Grasping the simplicity of a one-bit stage in the pipeline ADC, the design harnesses the cascading structure of multiple stages, facilitating seamless implementation using high-level transistor languages like Verilog-A. The paper presents the meticulous design process of an 8-bit Pipelined Analog-to-Digital Converter (ADC) fabricated with 90 nm CMOS technology, meticulously characterizing its performance metrics such as SNR, SFDR, power dissipation, and consumption. Notably, simulation results showcase an impressive power dissipation of 2.8 mW, alongside a measured SNR of 56.35 dB, SFDR of 66.39 dB, and a power consumption of 0.12W, all achieved within the confines of 90 nm CMOS technology. © 2024 IEEE.

关键词： Electric power utilization

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Leveraging Industrial IoT Infrastructure for Remote Sensing and Edge computing in the Mining Sector 5

Leveraging Industrial IoT Infrastructure for Remote Sensing ...

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5th international conference in Electronic Engineering, Information Technology and Education, EEITE 2024

作者： Eleftherios, Emmanouil Papatsaroucha, Dimitra Markakis, Evangelos K. Hellenic Mediterranean University Electrical and Computer Engineering Heraklion Greece

ISBN: (纸本)9798350372878

Mining 4.0 signifies a paradigm shift within the mining sector and is defined as an all-encompassing strategy for industry revolution by optimizing mining processes through the utilization of digital technologies, automation, and data analytics to streamline processes. Mining 4.0 aims to develop intelligent and networked mining systems that enhance resource utilization, improve operational efficiency, reduce costs, and mitigate environmental harm, all while prioritizing the safety and welfare of workers. The process of mining digitization encompasses the methodical collection, management, and monitoring of data derived from diverse sources, including sensors, equipment, vehicles, and more. It permits remote, realtime monitoring of environmental and operational conditions, as well as the integration of control systems designed to optimize and automate processes. With digital transformation, the mining sector aspires to overcome conventional obstacles and adjust to changing market requirements, therefore facilitating a more sustainable and efficient future. A critical challenge in the process of digitizing the mining sector is the need to provide reliable routes for transmitting and communicating data between physical and digital components within mining environments. This paper examines the convergence of Mining 4.0 and mining digitization, with a specific emphasis on the pivotal role that remote sensing, edge computing, and decentralized communication systems play in data transmission and real-time monitoring in light of enhancing mining operations' safety and efficiency. The study performed puts forward a European solution based on open standards and tools, revolving around an Industrial Internet of Things (IIoT) Gateway that is a core component of the proposed communication system. This gateway will function as an intermediary between the edge and cloud-based platforms and will facilitate real-time monitoring through the establishment of resilient wireless communi

关键词： Gateways (computer networks)

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A Thyristor Based IoT System to control the Illuminance of Lamp Using Matrix Keypad 5

A Thyristor Based IoT System to Control the Illuminance of L...

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5th IEEE international conference on computing, Power, and communication Technologies, IC2PCT 2024

作者： Mishra, Saket Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350383522

The lighting is the important phenomena that are used in our day to day life. They must be utilised in a proper way without any consequences. The rise in the demand is caused due to functioning of equipment unnecessary that leads to increase in the consumption of power. To overcome these drawbacks, the digitalization is implemented. This is done through the internet of things. This helps to function through evolving the two way communication system. The lighting system must be properly functioned through analysing the illuminance and luminance. Higher or lower illuminance level can cause various constraints in physical and mental health. To overcome these constraints, the proposed system is implemented. This is done through the thyristor controlled system. The thyristor is a solid state switching devices that are used to withstand the rated voltage until it gets triggered. The thyristor once triggered, the current through the triggering phase can be removed without turning off the equipment. The illuminance percentage is visualised through matrix keypad. The overall system is functioned and monitored through internet of things. © 2024 IEEE.

关键词： digitalization Illuminance internet of things inverters lamp luminance matrix keypad rectifiers voltage control voltage source converters

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