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Enhancement of Industrial Automation using Internet of Things

Enhancement of Industrial Automation using Internet of Thing...

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2024 international conference on advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Sheeba, Adlin Subasini, C.A. Kata Purna Avinash, S. Maheswaran Vijayendran, S. St. Joseph's Institute Of Technology Tamil Nadu Chennai600 119 India

ISBN: (纸本)9798350364828

The convergence of Industrial Automation, Cloud computing, and the Industrial IoT Devices has sparked a transformative paradigm shift across diverse industries. This synergy harnesses the power of interconnected smart devices, cloud-based data processing, and automated systems to redefine operational landscapes. In this abstract, we explore the intricate integration of these technologies and their collective impact on industrial realms. IoT sensors embedded within machinery facilitate real-time data collection on performance metrics, environmental factors, and machine health. These data streams, propelled through cloud-based infrastructure, undergo robust processing and analysis, enabling predictive maintenance, process optimization, and informed decision-making. The marriage of cloud computing and IoT not only allows for remote monitoring and control but also facilitates agile responsiveness to dynamic operational needs. By leveraging machine learning algorithms, anomalies are identified, allowing preemptive actions to mitigate potential downtime and enhance productivity. Moreover, the scalability and accessibility of cloud systems offer unprecedented flexibility in adapting to evolving industry requirements. However, such integration necessitates robust security measures to safeguard sensitive industrial data transmitted and stored within cloud environments. Encryption protocols, stringent access controls, and resilient authentication mechanisms become paramount to ensure data integrity and confidentiality. This abstract encapsulates the potential of this amalgamation, illuminating its transformative capabilities in optimizing processes, reducing downtime, and fostering cost-efficient, data-driven decision-making across industrial sectors. © 2024 IEEE.

关键词： Cloud computing

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Deep Neural Networks for Image-Based Indian Sign Language Recognition: A Comprehensive Review and Practical Analysis 1

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2nd international conference on advances in data-driven computing and intelligent systems, adcis 2023

作者： Kaur, Harleen Bedi, Sanjam Kaur Rao K, Mallikharjuna Lekhana, M.A. Data Science and Artificial Intelligence International Institute of Information Technology Naya Raipur Chhattisgarh Naya Raipur India Electronics and Communication Engineering International Institute of Information Technology Naya Raipur Chhattisgarh Naya Raipur India

ISBN: (数字)9789819995318

ISBN: (纸本)9789819995301

Addressing the communication barriers faced by individuals with vocal and hearing disabilities, sign language serves as a visual means of expression. However, the limited understanding of sign language among the general population creates significant challenges in various settings, such as banks, airports, and supermarkets. To overcome this, a sign language recognition (SLR) system is essential. This study focuses on developing a real-time word-level sign language recognition system that translates sign language into text, with a specific emphasis on Indian sign language (ISL) to cater to the needs of the deaf and hard-of-hearing community in India. Our research presents an ISL-based sign language recognition system, enabling users to capture hand movement images through a web camera, with the system accurately predicting and displaying the corresponding sign name. The captured images undergo several processing stages, incorporating computer vision techniques like grayscale conversion, dilatation, and masking. To achieve robust recognition, a convolutional neural network (CNN) is trained on the collected dataset, demonstrating exceptional performance with a 99% accuracy rate. This research contributes to the advancement of assistive technologies by providing an effective solution for real-time ISL recognition, promoting inclusive communication and accessibility for individuals with hearing and vocal impairments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Audition

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VIBE: A data-driven Approach to Career Guidance and Skill Development

VIBE: A Data-Driven Approach to Career Guidance and Skill De...

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2024 international conference on advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Sathya, A. Naveen, K.T. Narendran, M. Basker, S.P. Nirudeeshwar, B. Yuvaraj, S.K. Kcg College Of Technology Department Of Information Technology Tamil Nadu Chennai India Centennial Toronto Canada

ISBN: (纸本)9798350364828

Embarking on the journey to choose a career presents a widespread challenge, often leaving individuals uncertain about their future paths, despite possessing valuable skills. Our project, underpinned by machine learning, aims to empower students by helping them identify the most suitable career based on their distinct abilities and academic backgrounds. Leveraging innovative algorithms, particularly a Recurrent Neural Network (RNN), we meticulously analyze personal and academic information to provide tailored career recommendations. This methodology offers students a clear sense of direction, facilitating informed decision-making and bridging the gap between confusion and clarity. The application of cutting-edge technologies ensures a seamless and user-friendly experience, making our tool readily accessible to students seeking valuable guidance. © 2024 IEEE.

关键词： Students

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AI-Based Smart Education System to Enhanced the Learning of Students

AI-Based Smart Education System to Enhanced the Learning of ...

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2024 international conference on advances in computing Research on Science Engineering and Technology, ACROSET 2024

作者： Barde, Aaryan Thakur, Raj Patel, Shreyansh Sinah, Neelesh Barde, Snehlata Lnct Group of College Dept.of CSE-AIML Bhopal India Sage University Dept. of Aids Indore India Sage University Inst. of Advanced Computing Indore India

ISBN: (纸本)9798350388800

The education sector is poised for a significant shift propelled by Artificial Intelligence (AI) technologies. This paper explores the various uses of AI in education, such as data-driven decision assistance for instructors, adaptive assessment tools, intelligent tutoring, and personalized learning systems. It looks at how chatbots and virtual assistants driven by AI can improve learning by giving students instant, tailored support and direction. This paper also emphasizes how AI may improve student engagement and gamification of course materials, changing the educational environment into one that is dynamic, engaging, and pleasant. © 2024 IEEE.

关键词： Adversarial machine learning

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An Enhanced Deep Learning Technique for Crack Identification in Composite Materials

An Enhanced Deep Learning Technique for Crack Identificatio...

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international conference on advances in data-driven computing and intelligent systems, adcis 2022

作者： Ramanathan, Saveeth Sankareswaran, Uma Maheswari Mohanraj, Prabhavathy Department of Computer Science Engineering Coimbatore Institute of Technology Coimbatore India Department of Electronics and Communication Engineering Coimbatore Institute of Technology Coimbatore India Department of Artificial Intelligence and Data Science Coimbatore Institute of Technology Coimbatore India

ISBN: (纸本)9789819909803

Composite material consists of more than one substance, which inherit the superior properties of the constituent’s elements for light weight and tensile strength. The identification of cracks in composite material at an earlier stage reduces the cost and effort. Deep learning is a complex model in machine learning to extract significant features from a large dataset. The suitable construction of convolutional neural network topology for the application will give better results. Our proposed model uses Bayesian optimization for hyper-parameter tuning which updates the hyper-parameter value for each iteration to improvise the accuracy. In this work real time, composite material images were taken as dataset captured by Silicon Electron Microscope and Evolution VF camera. Applied proposed model on Silicon Electron Microscope dataset, obtained accuracy over 88% and on Evolution VF dataset obtained accuracy over 91%. The integration of optimization techniques with CNN reduces the computational time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electron microscopes

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Iterative Dichotomiser 3 (ID3) for Detecting Firmware Attacks on Gadgets (ID3-DFA)

Iterative Dichotomiser 3 (ID3) for Detecting Firmware Attack...

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international conference on advances in data-driven computing and intelligent systems, adcis 2022

作者： Punidha, A. Arul, E. Department of Artificial Intelligence and Data Science KPR Institute of Engineering and Technology Tamil Nadu Coimbatore India Department of Information Technology Coimbatore Institute of Technology Tamil Nadu Coimbatore India

ISBN: (纸本)9789819932498

Even while the wonderful new product's standard distribution condition still offers very little protection, receiving a cutting-edge device during the holiday season may be entertaining but does not pose any risks. This protects because anybody may openly link the commercial item to the Web despite efforts to prevent theft, industrial espionage, and infections all of which might endanger the assets and protection. In fact, malware may be detected using machine learning without the usage of signatures or behavioral analysis. In order to characterize such a software assault on devices, we use Iterative Dichotomiser 3 (ID3). By training a Firmware ID3 with several input clusters and a malicious or benign API, a single output unit is classified as malicious or benign. The unknown IoT firmware was then subjected to training by ID3 to find a harmful pattern. The result shows that the truth positive rating is 97.86%, and that the adware attack is 0.02% positive. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Malware

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Deep Learning Models for Classification of Remotely Sensed data of Sugarcane 1

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2nd international conference on advances in data-driven computing and intelligent systems, adcis 2023

作者： Kambli, Mansi Palkar, Bhakti Computer department K. J. Somaiya College of Engineering Somaiya Vidyavihar University Mumbai India

ISBN: (数字)9789819995219

ISBN: (纸本)9789819995202

The traditional machine learning algorithms are giving way to approaches for deep learning in computer vision, which refers to a computer's capacity to infer meaning from digital images and videos. Sugarcane categorization is important for agricultural management and monitoring. Traditional crop categorization methods based on manual inspection or restricted ground-based data gathering are time-consuming and frequently inaccurate. As a result, an automated and efficient strategy is suggested that requires the use of remote sensing data and the capabilities of deep learning algorithms. A dataset made from multispectral Sentinel imagery is used for the classification of sugarcane. This approach seeks to separate sugarcane-growing regions from other regions in Sentinel-2 images using VGG19, MobileNetV2, and CNN as feature extractors. These findings illustrate the feature extraction utilizing deep learning models with an SVM classifier for sugarcane. By considering variables such as distinct spectral bands, temporal fluctuations, and potential difficulties in separating sugarcane from other land cover types, the objective is to construct and check working of deep learning models for categorizing sugarcane locations using Sentinel-2 data. The sugarcane classification can further be used to find dense and sparse vegetation after the classification is done with deep learning models. The outcomes of this study will help to improve sugarcane categorization techniques and will help farmers, researchers, and agricultural stakeholders make better crop management, yield estimation, and resource optimization decisions in sugarcane farming. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Classification (of information)

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A Study on Effects of Synthetic data for Predicting the Remaining Useful Life of Aluminium Electrolytic Capacitors Using Bagging-Based Ensemble Learning 2nd

A Study on Effects of Synthetic Data for Predicting the Rema...

引用

2nd international conference on advances in data-driven computing and intelligent systems, adcis 2023

作者： Bhattacharyya, Anindya Srijith, K. Behera, R.P. Dasgupta, Arup Chakraborty, R.S. Real Time Systems Division Electronics & Instrumentation Group Indira Gandhi Centre for Atomic Research Tamil Nadu Kalpakkam603102 India Birla Institute of Technology and Science Hyderabad Campus Telangana Secunderabad500078 India Physical Metallurgy Division Materials Characterization Group Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research Tamil Nadu Kalpakkam603102 India Homi Bhabha National Institute Training School Complex Anushaktinagar Mumbai400094 India Department of Computer Science and Engineering IIT Kharagpur Kharagpur721302 India

ISBN: (纸本)9789819995172

Aluminium electrolytic capacitors (AECs) are crucial components used in power supplies, computer motherboards, and variable frequency drives for ripple filtering and energy storage. Their performance is affected by factors like temperature, frequency, ripple current, and ageing. Despite design advancements, AECs remain reliability weak points, demanding thorough analysis. This research proposes a method to predict the Remaining Useful Life (RUL) of AECs under combined temperature and voltage stress. We develop an RUL prediction model using bagged decision trees by ageing 24 AEC samples and tracking degradation via capacitance and ESR changes. Synthetic data strengthens the model due to limited training data. We assess the impact of different minority oversampling methods like SMOTE, SMOTER, and SMOGN on prediction accuracy, using ANOVA to compare outcomes within and between algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Analysis of variance (ANOVA)

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Blockchain computing: Unveiling the Benefits, Overcoming Difficulties, and Exploring Applications in Decentralized Ledger Infrastructure 2nd

Blockchain Computing: Unveiling the Benefits, Overcoming Dif...

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2nd international conference on advances in data-driven computing and intelligent systems, adcis 2023

作者： Upreti, Kamal Poonia, Ramesh Chandra Verma, Ankit Divakaran, Prakash Mittal, Shikha Vats, Prashant Biswas, Siddhartha Sankar Delhi NCR Ghaziabad India Department of CSE ADGITM New Delhi India Himalayan University Arunachal Pradesh Itanagar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of CSE SCSE Manipal University Jaipur Rajasthan Jaipur India Department of CSE SCSE Jamia Hamdard University New Delhi India

ISBN: (纸本)9789819995301

The protocol known as blockchain, which is composed of blocks, utilizes a decentralized distributed system of nodes (miners). There are three parts to every block: information, which is represented by a hash, and the hash of a previous transaction. In order to regulate data after it has been stored, it is quite difficult to make changes. Mining is compensated for each encrypted function computation they carry out to verify the transaction. This research paper will provide a comprehensive understanding of blockchain-based technologies and how they are applied in a variety of industries, including those that deal with digital currencies, financial services, medical manufacturing, privacy, and a number of other fields. Digital money, notably the cryptocurrency Bitcoin, had previously been one of the most well-known network applications. As there have lately been several studies about the unique utilization of this sort of technology, we will discuss some of these academic works as well as the challenges encountered during the development of these kinds of applications. Blockchain technology is a quickly growing area of database technology that has recently found use in a wide range of industries, including the use of digital money, hospital administration, and other academic subjects. Because of how blockchain technology works and operates, these types of applications are now possible. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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A Review of Advanced Technologies for intelligent Sensing, Diagnostics, and Personalized Healthcare Solutions 4

A Review of Advanced Technologies for Intelligent Sensing, D...

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4th international conference on Ubiquitous computing and intelligent Information systems, ICUIS 2024

作者： Ghantasala, G. S. Pradeep Rajesh Sharma, R. Sungheetha, Akey Anitha, P. Selvalakshmi, B. Pradeepa, K. Alliance College of Engineering and Design Alliance University Department of Computer Science and Engineering Karnataka Bengaluru India Sri Sai Renganathan Engineering College Department of Ece Tamil Nadu Coimbatore India Tagore Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India St. Michael College of Engineering & Technology Department of Computer Science and Engineering Tamil Nadu Sivaganga India

ISBN: (纸本)9798331529635

intelligent Health is a revolutionary approach to modern healthcare that uses the Internet of Things (IoT), artificial intelligence (AI), and sensor technologies to transform patient-centric solutions. This study examines how these technologies are combining to change patient monitoring, illness management, personalized treatment, and healthcare delivery. Wearable sensors, medical equipment, and IoT-enabled infrastructure allow for real-time, continuous monitoring of patient health data, enabling the early identification of anomalies and the implementation of personalized interventions. IoT platforms enable remote connectivity and data-driven insights by easily integrating sensor data into healthcare systems. AI algorithms analyses large amounts of sensor data to maximize clinical decision-making, forecast health outcomes, and extract insightful information. intelligent health solutions offer many advantages, such as better patient outcomes and a better patient experience. However, to fully utilize these technologies, issues like data privacy, interoperability, and regulatory compliance need to be resolved. Future directions in intelligent health include the establishment of standards and regulatory frameworks, patient-centric design, integration with electronic health records, and advances in AI and machine learning. With individualized, data-driven solutions, intelligent health holds great promise for revolutionizing the delivery of healthcare and enabling people to take charge of their own health and well-being © 2024 IEEE.

关键词： Electronic health record

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