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Analysis Of Concrete Cracks And Fatigue In Smart Cities Using Yolov3

Analysis Of Concrete Cracks And Fatigue In Smart Cities Usin...

Research methodologies in Knowledge management, Artificial Intelligence and Telecommunication engineering (RmKmATE), International Conference on

作者： U. Archana Sarvdaman Sharma Sitesh Kumar Singh Sureshkumar R Senthilkumar P T. Harish Babu Department of Computer Science and Design R.M.K. Engineering College Chennai India Department of Civil Engineering University Institute of Engineering and Technology University of Jammu Jammu & Kashmir India Department of Civil Engineering Wollega University Nekemte Oromia Ethiopia Department of Electronics and Communication Engineering VEL Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai KL School of Architecture Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India Department of Electrical and Electronics Engineering Sethu Institute of Technology Tamilnadu India

This study focuses on the application of the YOLOv3 (You Only Look Once version 3) object detection algorithm for the analysis of concrete cracks and fatigue within Smart Cities. Concrete infrastructure plays a crucial role in urban environments, and its structural integrity is paramount for ensuring public safety and sustainable development. The proposed approach utilizes YOLOv3 to identify and localize instances of concrete cracks and signs of fatigue in images and videos captured from various urban settings. By leveraging deep learning techniques, this research aims to enhance the efficiency and accuracy of monitoring and maintaining concrete structures, contributing to the overall resilience and longevity of Smart Cities. The findings of this study present valuable insights into the potential of utilizing advanced computer vision methods for proactive infrastructure management in the urban landscape.

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A Novel Development of Artificial Intelligence Enabled Learning methodology for Human Depression Prediction Scheme

A Novel Development of Artificial Intelligence Enabled Learn...

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Intelligent Systems for Cybersecurity (ISCS), International Conference on

作者： G. Ramkumar R Priyadharshini K. Selvi K. Kalaiselvi S. Rathika N. Kanagavalli Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Information Technology R.M.K Engineering College Chennai Tamil Nadu India Department of Data Analytics Saveetha College of Liberal Arts and Sciences Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Department of Master of Business Administration Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

Human Depression Prediction is essential for several reasons, primarily centered around improving mental health outcomes and providing timely interventions. Firstly, early detection of depression allows for prompt and targeted interventions, enabling individuals to receive appropriate support and treatment before their condition worsens. The Human Depression Prediction Scheme (HDPS) introduces an innovative method for predicting depression by synergizing the capabilities of deep learning through the LeNet architecture with the optimization prowess of the Grey Wolf Optimization (GWO) algorithm. The proposed scheme achieves a commendable accuracy of 95%, attesting to its effectiveness in discerning depressive tendencies. Notably, the HDPS is implemented in Google Colab, emphasizing its accessibility and ease of use. This integration of advanced technologies and optimization techniques positions HDPS as a promising tool for early detection of depression, offering both high accuracy and practical implementation in a widely accessible computing environment.

关键词： Deep learning Accuracy mental health computer architecture Depression Prediction algorithms Internet

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Hmm Classifier Object Recognizing System in Brain–computer Interface 8th

HMM Classifier Object Recognizing System in Brain–Computer ...

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8th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2020

作者： Anupama, H.S. Jain, Raj V. Venkatesh, Revannur Cauvery, N.K. Lingaraju, G.m. Department of Artificial Intelligence and Machine Learning BMS Institute of Technology & Management Bangalore India Department of Computer Science and Engineering R. V. College of Engg Bangalore India Department of Information Science and Engineering R. V. College of Engg Bangalore India Department of Information Science M. S. Ramaiah Institute of Tech. Bangalore India

ISBN: (纸本)9789811557873

machine learning (mL) is the field that adds intelligence to devices providing them with capabilities to process and identify patterns in data just like human beings do. Programming devices in this manner can help in identifying those patterns which human beings often cannot. machine learning is based on modelling data mathematically. mL has been gaining a lot of attention in the last few decades, especially in fields of interdisciplinary research. Brain–computer Interface (BCI) is an area where machine Learning technology is been rapidly using. Also, machine Learning techniques have to be used so that one can get a better result and more efficiency. Information Transfer Rate is the best way to measure the performance of the signals. The current research is mainly focused on achieving the systems with higher ITR. The focus of the proposed system is to get better and high Information Transfer Rate by merging two different approaches. The approach used in this work is (SSVEP), Visually Evoked Potential and (SSAEP) Auditory Evoked Potential by using Hidden markova model (Hmm). The system which is to be developed checks whether the existing system has such facility if it has, does it provides accuracy which is of a higher rate and can put it in the real-world applications. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hidden markov models

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A Robust Network Connection Across Internet of Things Devices Inside the Room with Visible Light Communication

A Robust Network Connection Across Internet of Things Device...

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Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： N. Banupriyal Suresh G R. Nandhini Anu mary mathew L. Saravanan Anitha G Department of Computer Science and Engineering R.M.K. Engineering College Chennai Department of Electrical and Electronics Engineering Sona College of Technology Salem Department of Electronics and Communication Engineering Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai Department of Electronics and Communication Engineering Mar Baselios Christian College of Engineering and Technology Kerala Department of Electronics and Communication Engineering PERI Institute of Technology Chennai Department of Electronics and Communication Engineering Saveetha School of Engineering Chennai

In order to better monitor and engage with the communal assets of smart cities, the amount of Internet of Things (IoT) devices that have been installed has been continuously rising. This might result in a reduction in network efficiency as a consequence of the increasing volume of network traffic and connections brought about by different Internet of Things devices. In order to address these challenges, one approach that shows promise is to take advantage of the close physical proximity of communicating devices and to facilitate communication between individual devices in order to achieve low latency, efficient use of bandwidth, and reliable service. Taking use of new technologies like visible light and ultrasound, our study aims to improve the performance of indoor Internet of Things (IoT) connectivity in settings such as smart homes and small office and home offices (SOHO). This method expands the capacity of the network, ensures that network connections among IoT devices are stable, and offers effective ways to allow distance-bounding services. We have constructed communication modules for visible light and ultrasonic using off-the-shelf components, and we are now evaluating their network performance as well as their energy usage.

关键词： Performance evaluation Ultrasonic imaging Smart cities Telecommunication traffic Smart homes Internet of Things Reliability

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Different optical fiber hybrid repeater amplifiers arrangement for optical losses and optical dispersion management in the presence of modulation code schemes

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Journal of Optical Communications 2024年

作者： Prabu, Ramachandran Thandaiah Lingaraj, Vanitha Gajendran, Bhavani Balakrishnan, Balamuralitharan Balashanmugam, Thiyaneswaran Dorairajan, Nithya Adel, marian Habbib Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha University Tamilnadu Chennai India South Institute of Computer Science Giza Egypt Department of ECE S.A. Engineering College Tamilnadu Chennai India Department of ECE R.M.K. Engineering College Tamilnadu Chennai India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamilnadu Avadi India Department of ECE Sona College of Technology Tamilnadu Salem India Department of ECE Panimalar Engineering College Tamil Nadu Chennai India

This paper highlights the different optical fiber hybrid repeater amplifiers arrangement for optical losses and optical dispersion management in the presence of modulation code schemes. The light signal power is measured and clarified with/without any amplification versus fiber channel length with 1,300 and 1,550 nm wavelength based on various modulation schemes. Electrical output power after receiver is clarified without amplification and with various amplification techniques against fiber channel length with second and third wavelength based on on-off keying modulation code scheme. The quality factor and BER are measured after receiver against transmission data rates without amplification and with various amplification techniques against 300 km fiber channel length with 1,300 nm wavelength based different modulation code schemes. © 2024 Walter de Gruyter GmbH. All rights reserved.

关键词： Optical fibers

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motion Pattern Recognition from Crowded Video

Motion Pattern Recognition from Crowded Video

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International Conference on Reliability, Infocom.technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Upasana Singh manoj Kumar Choubey Dept of Computer Engineering & Applications M.tech CSE GLA University Mathura India Dept of Computer Engineering & Applications GLA University Mathura India

ISBN: (数字)9781728170169

ISBN: (纸本)9781728170176

During the previous decades, in the era of video surveillance, an immense consideration had been given to crowd video control and crowd management. Among the undertakings for video surveillance, retrieval of crowd video is a very challenging task. motion Pattern Recognition from Crowded Video generally faces the problem of occlusion, low resolution, cluttering sometimes object social interaction is not present then find the abnormal behavior is quite tough. We handle these pattern recognition problems by introducing the social force model approach in which we calculate the social force between pedestrians presented in the crowd which helps in recognizing the behavior of the crowd in an abnormal situation. In our approach, we find some well-known types of motion pattern these are: lane, ring, fountainhead, and bottleneck [1]. In this paper, our proposed approach focused on some steps these are: preprocessing of frames, calculate optical flow, calculate the social force model among pedestrians, Clustering after Jacobian matrix calculation and in the last step behavior recognition with the help of KNN classifier.

关键词： Force Jacobian matrices Optical flow Pattern recognition Surveillance mathematical model Brightness

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Harnessing Tidal Energy: Design and Performance Evaluation of marine Energy Conversion Systems

Harnessing Tidal Energy: Design and Performance Evaluation o...

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technological engineering and its Applications in Sustainable Development (ICTEASD), International Conference for

作者： Dharmesh Dhabliya Neeraj Varshney m. Sasikumar P. Vijayaraghavan m. Vimala J.B. Sapaev muntather Almusawi Dupakuntla Ushasree Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Computer Engineering and Applications GLA University Mathura India Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Electrical and Electronics Engineering R.M.K. Engineering College Kavaraipettai Tamil Nadu India National Research University Tashkent Uzbekistan Western Caspian University Baku Azerbaijan Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq GRIET Hyderabad Telangana India

ISBN: (数字)9798350336474

ISBN: (纸本)9798350336481

Ocean wave energy, a sustainable energy source with significant growth prospects, has substantial storage capacity. Tidal energy technologies' application possibilities and practical significance for harnessing tidal energy resources are extensive. Researchers have developed several Wave Energy Converters (WECs) with diverse architectures and designs based on various principles. This study comprehensively analyzes tidal energy power production technology's basic framework and Power Take-Off (PTO) mechanism. This article introduces several types of WEC and multi-Degree Wave Energy Converters (mDWEC) and provides implementation examples. The analytical method creates an extensive multi-index model and assesses the current WEC based on five perspectives: energy capture, technological cost, economics, dependability, environmental friendliness, and adaptability. The results indicate that the mDWEC exhibits outstanding overall efficiency and has various applications in tidal energy consumption and development. Applying subjective and quantitative approaches determines the ideal technical strategy for WEC. This is achieved by reviewing and analyzing the technological principles of tidal energy power production and the implementation of devices. These findings are utilized for the advancement of WEC.

关键词： Performance evaluation Analytical models Adaptation models Energy capture Costs Production Ocean waves

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5G Approach: Perspectives Into Smart Infrastructure Implementation

5G Approach: Perspectives Into Smart Infrastructure Implemen...

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Communication, Computing and Energy Efficient technologies (I3CEET), International Conference on

作者： Urinbaev Sharofiddin S. Gopi muntather Almusawi Rakesh Kumar manjinder Kaur Wratch Amarjeet Kumar Ghosh Department of Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University Tashkent Uzbekistan Western Caspian University Scientific Researcher Baku Azerbaijan Department od CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Engineering and Applications GLA University Mathura Department of Computer Science Engineering Chandigarh Engineering College Chandigarh Group of Colleges Jhanjeri Mohali Punjab India Department of Electronics & Communication Engineering IES College of Technology Bhopal M. P. India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

Intelligent buildings and intelligent asset monitoring on tenants comfort (ICT for enhanced tenant comfort) Nonetheless, present systems are failing the SFm in connecting so many IoT devices as they tend to have poor connection quality and long latency. 5G technology offers ultra-reliable and low latency, high-speed network infrastructure with slicing features for providing real-time economics. It is also expected to make possible a more sustainable future by reducing energy use and directing new applications in ways that meet ever-tougher sustainability targets. In this blog, he shows the benefits and what is possible now and then explains where 5G has not been fully realised just yet on his SFm applications for various use cases. This document also provides an illustrative example of the Singapore 5G deployment plans based on SUSS and a SFm use case development timeline to be undertaken by the 5G Advanced BIm Lab in alignment with Singapore's 5G deployment strategy. In addition to the 5G forest project, we innovate and co-create with a range of industry partners in order to benefit our students in learning new ways of using this technology across fields and sectors (and also as part of their education/training for entry-level professionals; you read more about it here). Their abilities are supported by development. Facilitates the Utilization of 5G Networks This paper sets a benchmark for future moves on SFm methodology and directs training activities aiming to exploit 5G networks in response to growing sustainability demands, compatible with improved enterprise ***- Improved Extreme Learning machine, Prediction, Human Scenarios, Smart Homes, Healthcare Support, monitoring, Recurrent Formulation, Feedback mechanisms, Precision, Swiftness.

关键词： Training Industries 5G mobile communication Government Transportation Smart homes Internet of Things Sustainable development monitoring Facilities management

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A Robust Design of Cooperative model to Enhance Energy Efficiency over Heterogeneous 5G Wireless Sensor Network Paradigm

A Robust Design of Cooperative Model to Enhance Energy Effic...

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Innovation in technology (APCIT), Asia Pacific Conference on

作者： C. Anitha G. m. Karthik m. Uma maheswari L. Vinoth Kumar G. Sasikala Jayanthi S Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Information Security School of Computer Science and Engineering (SCOPE) Vellore Institute of Technology Vellore Tamil Nadu India Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai Tamil Nadu India Department of Information Technology RMK Engineering College Chennai Tamil Nadu India Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering R.M.D Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

multiple interconnecting Wireless Sensor Networks (WSN) built on the same region have grown increasingly prevalent in recent years due to the widespread diffusion of 5G Wireless Sensor Networks (WSNs). Cooperative packet forwarding is anticipated to prolong their lifespan in this scenario. While some studies have looked at 5G network models that work together, the majority of these studies ignore the fact that WSNs vary greatly in terms of factors like battery life, starting time of operation, number of nodes, locations of nodes, energy consumption, packet size and/or data transmission timing, and so on. Optimistic lifelong gains through teamwork could not hold water in a diverse setting. Improve Energy Efficient Communication Paradigm (EEECP) is a fair cooperative routing approach that we offer in this study for 5G wireless sensor networks that are diverse and overlapping. The efficiency of this suggested approach will be evaluated by cross-validating it with the usual Cooperative Data Communication (CDC) model of communication. In order to keep the overall energy usage down, it implements a cooperative forwarding system and an energy-pool. The energy pool mediates equitable collaboration. Last but not least, the suggested strategy performs exceptionally well according to the simulation findings.

关键词： Wireless sensor networks Energy consumption technological innovation 5G mobile communication Array signal processing Data models Energy efficiency

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Si-rich Silicon Nitride for Nonlinear Signal Processing Applications

Si-rich Silicon Nitride for Nonlinear Signal Processing Appl...

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Smart Photonic and Optoelectronic Integrated Circuits 2024

作者： Gardes, Frederic Vitali, Valerio Bucio, Thalía Domínguez Liu, Hao González, José manuel Luque Jurado-Romero, Francisco Ortega-moñux, Alejandro Churchill, Glenn Gates, James C. Hillier, James Kalfagiannis, Nikolaos melati, Daniele Cristiani, Ilaria Schmid, Jens H. Cheben, Pavel Wangüemert-Pérez, J. Gonzalo molina-Fernández, Íñigo Lacava, Cosimo Petropoulos, Periklis Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Electrical Computer and Biomedical Engineering Department University of Pavia Pavia27100 Italy Universidad de Málaga CEI Andalucía TECH E.T.S.I. Telecomunicación Málaga29010 Spain School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Centre de Nanosciences et de Nanotechnologies Université Paris-Saclay CNRS Palaiseau91120 France Advanced Electronics and Photonics Research Center National Research Council Canada 1200 Montreal Road OttawaONK1A 0R6 Canada

ISBN: (纸本)9781510670402

We report the demonstration of an integrated silicon-rich silicon nitride wavelength converter based on the Bragg scattering intermodal four-wave mixing process. This broadband wavelength converter incorporates on-chip mode conversion, multiplexing and de-multiplexing functionalities. The system allows for broadband signal conversion with a 3dB bandwidth exceeding 70 nm. © 2024 SPIE.

关键词： Four wave mixing

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