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检索条件"机构=Artificial Intelligence and Machine Learning Engineering"

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Revolutionizing Quality Control: A machine learning Approach for Precise Surface Defect Detection and Localization in Industrial Components

Revolutionizing Quality Control: A Machine Learning Approach...

引用

2024 IEEE International Conference on Emerging Technologies in Computer Science for Interdisciplinary Applications, ICETCS 2024

作者： Ajina, A. Jaya Christiyan, K.G. M S Ramaiah Institute of Technology Department of Artificial Intelligence and Machine Learning Bangalore India M S Ramaiah Institute of Technology Department of Mechanical Engineering Bangalore India

ISBN: (纸本)9798350372502

This paper focuses on the creation of a machine learning application designed to efficiently identify and categorize surface imperfections in a variety of components. Conventional methods, relying on visual examination or manually crafted characteristics are prone to inaccuracies and are time-intensive. Leveraging the capabilities of artificial intelligence architecture, we not only achieve precise defect classification but also accurate defect localization. In contrast to traditional approaches, artificial intelligence can adeptly learn optimal visual features in a supervised manner. In real image data set we performed our experiments which illustrate that our approach outperforms current methods while maintaining computational efficiency. We have developed a machine learning model for surface defect detection in steel flat surfaces through image segmentation. This advancement has resulted in reduced defects, heightened manufacturing accuracy, increased production rates and enhanced product quality. © 2024 IEEE.

关键词： Image segmentation

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Node Coverage and Connectivity Optimization in Heterogeneous Wireless Sensor Networks Using Improved Flower Pollination Algorithm 4

Node Coverage and Connectivity Optimization in Heterogeneous...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Mahankali, Saritha Kesavan, R. Kalaiselvan, S.A. Saveetha School of Engineering Simats Department of Computer Science & Engineering Chennai India Vardhaman College of Engineering Department of Computer Science & Engineering Telangana India Rajalakshmi Engineering Department of Artificial Intelligence & Machine Learning Chennai India

ISBN: (纸本)9798331529635

Wireless sensor networks (WSNs) rely on energy-conserving routing protocols due to the limited power and communication capabilities. The LEACH protocol has seen extensive usage despite its homogeneous network foundation, leads inadequate signal coverage. To solve the issue, this research proposes an improved flower pollination algorithm (IFPA) improves flower pollination algorithm (FPA) addresses issues with slow convergence and local optima. This research presents an enhanced clustering technique that may be utilized in heterogeneous sensor networks. Its main feature is the ability to adjust the status of data transmission. Once the observed information intensity above the predefined threshold, the data transmission connection is initiated and data is sent to the sink by the cluster heads, which filter the perceived information. Otherwise, cluster nodes keep track of the data and wait for the next batch of nodes to provide data. The good news is that the simulation results show a network lifespan that is several times longer than the LEACH protocol. The IFPA method stands out because it increases coverage rates while drastically decreasing the cost of deploying networks. As a result, the suggested method might find many uses, helping to lower costs and improve the performance of wireless sensor networks. © 2024 IEEE.

关键词： Sensor nodes

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Systematic Literature Review on Industry Revolution 4.0 to Predict Maintenance and Life Time of machines in Manufacturing Industry 3

Systematic Literature Review on Industry Revolution 4.0 to P...

引用

3rd International Conference on artificial intelligence and Smart Energy, ICAIS 2023

作者： Sowmya, P. Ravichandran, Sathish Kumar Rakshitha Department of Robotics and Artificial Intelligence Karnataka Nitte India Christ University School of Engineering and Technology Department of Computer Science Karnataka Bangalore India Department of Artificial Intelligence and Machine Learning Karnataka Nitte India

ISBN: (纸本)9781665462167

Industry 4.0 is digitized revolution for manufacturers or companies where in new technologies are imbibed into their production system for their day-to-day operations or activities. So that their overall economic needs and efficiency can be improved. In manufacturing industry maintenance of the equipment is the key concern. When the equipment requires maintenance, it has to be done at the earliest, failing which companies will have to face consequences in terms of loss of customers, time and money. Solution is provided to this problem in terms of a technique called predictive maintenance. The content of the article focuses on different predictive maintenance strategies, which help manufacturers to forecast if equipment/component will fail so that its maintenance and repair can be scheduled exactly before the component fails. The results will be useful for manufacturers to understand the importance of industry 4.0 for predictive maintenance. © 2023 IEEE.

关键词： Industry 4.0

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Revolutionizing Obstetric Care: IoT, AI-Enabled, and Data-Driven Partograph System

Revolutionizing Obstetric Care: IoT, AI-Enabled, and Data-Dr...

引用

2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023

作者： Zaveri, Dishant Jagtap, Vividha Gill, Jasleen Jain, Krishi Sheth, Shivam Shekokar, Narendra Djsce Dept. of Computer Engineering Mumbai India Djsce Dept. of Artificial Intelligence and Machine Learning Mumbai India Mumbai India

ISBN: (纸本)9798350314878

This research paper introduces a comprehensive real-time labor and delivery monitoring system that uses various hardware devices like ultrasound transducers, cardiotocographs, sphygmomanometers, and IoT devices. It creates a database accessible via a dedicated mobile app for doctors, nurses, and receptionists. The system includes features to identify and notify medical staff of potential risks such as preterm labor or fetal distress, using SMS alerts and LED lights for immediate attention. In emergencies, it notifies relevant medical personnel and receptionists for urgent interventions like cesarean sections. If needed facilities aren't available nearby, the system searches for hospitals within an 8-kilometer radius and sends alerts to check availability, arranging for an ambulance if necessary. This system allows real-time access to patient data, leading to faster responses and improved outcomes, enhancing decision-making and reducing maternal and child mortality through timely interventions and improved maternal care quality. © 2023 IEEE.

关键词： Ultrasonic transducers

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Quantum Chain of Things: 'The Quantum triad - Integrating Blockchain, IoT and Quantum Computing for a Transcendent Future'

Quantum Chain of Things: 'The Quantum triad - Integrating Bl...

引用

International Conference on Computer Vision and Internet of Things 2023, ICCVIoT 2023

作者： Jain, Shweta Aggarwal, Rishit Gandhi, Anju Bhandari Department of Artificial Intelligence and Machine Learning Panipat Institute of Engineering and Technology Panipat India Department of Computer Science and Engineering Graphic Era University Dehradun India

ISBN: (纸本)9781839539848

The Internet of Things (IoT), which is building a new world where everything is interconnected and can be remotely operated, is one of the developing technologies. The epoch of machines conquering the universe is just getting warmed up. The next technological innovation is blockchain, which uses a peer-to-peer communication link to preserve general transactional data and information (or blocks) across several repositories (or chains). The terminology "Digital Ledger" alludes to an instance of block storage. Quantum computing is the next quickly developing technology. It incorporates the use of numerous quantum physics aspects, notably superposition and entanglement. Every foundational premise of the computational game is amended by quantum excellence. A new paradigm dubbed Quantum - Chain of Things (QCoT), which is the most potent technology from the sub-emerging technologies is presented when we scrutinize the collaboration of the three powerful advanced. The BC-IOT (Blockchain coupled with IOT leveraging Arduino) and QC-IOT (Quantum computing merged with IOT using IBM Qiskit) subsystems are the cornerstones of QCoT technology. The prevailing breakthroughs in blockchain, quantum computing, and IOT will be addressed in this paper, followed by an exploration of the recommended architectural model for the improved technology. © The Institution of engineering & Technology 2023.

关键词： Blockchain

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A Review on the Applications of Natural Language Processing in Healthcare 4

A Review on the Applications of Natural Language Processing ...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Warbhe, Mohan K. Verma, Prateek Faculty of Engineering and Technology Department of Computer Science and Design Sawangi Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Sawangi Maharashtra Wardha442001 India

ISBN: (纸本)9798331529635

In healthcare, Natural Language Processing (NLP) is a technique to improve clinical decision support, patient care, and medical research. By automating clinical recording, NLP enhances the calibre of medical records and professional communication. It makes Electronic Health Records (EHRs) easier to use by facilitating quick and easy data entry, retrieval, and access to vital patient data that helps with precise diagnosis and efficient treatment planning. Through the analysis of patient-specific data, NLP supports clinical decision support by delivering prompt recommendations. Chatbots and virtual assistants managing repetitive duties like booking appointments also improve patient connection. NLP makes it easier to analyse vast amounts of literature for medical research, facilitating the extraction and summary of important discoveries. Healthcare data processing requires text preparation, sentiment analysis, Named Entity Recognition (NER), semantic parsing, and Natural Language Generation (NLG). However, there are obstacles to overcome, like bias, ethical concerns, system integration, privacy, and data quality. The healthcare industry can use NLP to enhance patient outcomes, promote personalized medication, and streamline healthcare delivery by guaranteeing interoperability and setting standards. © 2024 IEEE.

关键词： Challenges of NLP in Healthcare Future treads of NLP for healthcare Healthcare NLP

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machine learning-Enabled Smart Transit: Real-Time Bus Tracking System for Enhanced Urban Mobility

Machine Learning-Enabled Smart Transit: Real-Time Bus Tracki...

引用

Intelligent Systems and machine learning Conference (ISML)

作者： Nadimpalli Madana Kailash Varma Md. Irfan Ahmed G. Madhusudhan G. Rishab Babu T. Shalini Fatima Unnisa Department of Artificial Intelligence & Machine Learning Vardhaman College of Engineering Hyderabad Telangana India Department of Artificial Intelligence & Machine Learning Vardhaman College of Engineering Hyderabad-Panatella India

ISBN: (数字)9798350343878

ISBN: (纸本)9798350343885

In bustling urban cities, the efficiency of public transportation stands as a critical factor in alleviating traffic congestion and enhancing the daily commuter experience. This paper introduces a state-of-the-art Bus Tracking System that is meticulously designed to empower passengers by providing real-time updates on bus locations, availability, and estimated arrival and departure times. By leveraging cutting-edge technologies, this innovative system offers a myriad of advantages, notably including the reduction of passenger wait times, the optimization of route planning, and an overall enhancement of the public transportation journey. Through a comprehensive exploration of the significance of bus tracking technology and its potential to revolutionize urban mobility, this research underscores its pivotal role in promoting sustainable, convenient, and seamless transportation solutions tailored to the needs of modern cities. Our model uses machine learning techniques like regression, Kalman filter algorithm, and support vector machines to analyze the accuracy of arrival and departure of buses and further help in time-efficient and demand-based management of buses. A real-time location of buses can be provided by Google Maps API and Google Geolocation API.

关键词： Support vector machines machine learning algorithms Accuracy Web services Urban areas machine learning Real-time systems Kalman filters Public transportation Traffic congestion

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Enhancing Tactile Sensor Technology with Neuromorphic Models and machine learning 6

Enhancing Tactile Sensor Technology with Neuromorphic Models...

引用

6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Lenka, Komali Jyothi, Pulaparthi Lakshmi Asha Brahma Ramesh, Kallakuri N.V.P.S. Lanka, Dasaradha Ramayya Srikanth, M. Rajesh, Jonnapalli Tulasi Dept of IT S.R.K.R.Engineering College India India AP Bhimavaram India Dept of Artificial intelligence and Machine learning Aditya University India Dept of IT SRKR Engineering College Bhimavaram India

ISBN: (纸本)9798331522667

This study presents a novel approach to enhancing touch sensor technology by utilizing machine learning techniques and neuromorphic models. Tactile sensing has struggled to accurately understand complex physical interactions, despite its significance for artificial touch and robotic dexterity. Our approach improves the classification of tactile data by using neuromorphic computing—models inspired by brain processing—to identify changes in the environment, variations in force, and textures. We evaluate our model on benchmark tactile datasets and demonstrate its superior sensory resolution and increased adaptability. For robotics, prosthetics, and human-machine interfaces, the results are very important because they show that neuromorphic tactile sensors improve the accuracy and speed of data classification. This study showcases the potential of neuromorphic models to improve tactile perception, paving the way for more advanced and adaptable sensory systems. © 2025 IEEE.

关键词： Prosthetics

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Echo Insights: YouTube Sentiment Analysis App

Echo Insights: YouTube Sentiment Analysis App

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Vijay, K. Sharan Adhitya, C.D. Senthilnaathan, K. Jaeyalakshmi, M. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331541170

ISBN: (纸本)9798331541187

In an era where social media is getting a wider attraction seeing an improvement in content creators than consumers, ECHO INSIGHTS is a tool for analyzing YouTube video sentiments. This mainly focusses on creating an analytical tool that inputs a YouTube video link from user and uses YouTube API V3 to fetch comments from the video and organize them into a dataframe using pandas. For global audacity, these extracted comments are translated into English using Google trans library in Python. Subsequently, each of the fetched results are assigned with sentiments using Vader, a pre trained sentiment analysis model with a better accuracy of 96%. Then the analyzed results are displayed in a intuitive dashboard designed using streamlit enabling users to interpret sentiment patterns in the content. The dashboard offers various visualization contents like, good and bad comments based on Vader sentiment providing a clear view on sentiments of comments. Additionally, a summarized sentiment score is also displayed, providing general tone of the video. One of the additional features of out webapp is Wordcloud, a python library that plots most comments used or relevant words in the fetched comments representing a quicker glance in video engagement and users' opinions on video. ECHO INSIGHTS aims to empower content creators with better analysis and a healthier component and understanding of audience feedback and engagement with videos. Overall enabling users and creators with continuous improvement and optimization of their content, thus acting as a goof asset by translating raw comments till overall sentiment facilitating deeper connection with audience and crafting contents more efficiently. © 2024 IEEE.

关键词： Sentiment Analysis Streamlit Vader Wordcloud YouTube API

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AI-Powered Mental Health Assessment using Emotion Detection for Real-Time Analysis

AI-Powered Mental Health Assessment using Emotion Detection ...

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Computational, Communication and Information Technology (ICCCIT), International Conference on

作者： Vijay K Raghakeerthana R Renata Rachael Milinda Thusheel S Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

This paper is an AI-driven mental health assessment tailored to each patient's distinct emotional needs, addressing the global mental health crisis. Using advanced machine learning and natural language processing, it aims to deliver personalized guidance for psychological and physical wellness activities, along with tools for tracking individual progress. The papers employ exploratory case studies and knowledge discovery techniques to evaluate the effectiveness of these interventions. Data mining methods reveal hidden patterns within mental health datasets, with the potential to reshape therapeutic paradigms. Expected outcomes include enhanced accessibility to mental health resources, early intervention, personalized progress monitoring, improved quality of life, and reduced stigma. By integrating sophisticated data processing, machine learning, and empathetic user interaction, it operates by redefining mental health support. The system's architecture is designed to promote both emotional and cognitive well-being, fostering positive change in mental health care delivery.

关键词： Emotion recognition Neural networks Mental health machine learning Prediction algorithms Knowledge discovery Real-time systems Safety Information and communication technology Monitoring

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