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International Conference on Renewable Energy, Climatic Change, and Environmental Protection (IC-RECCEP)

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Articles

Maximizing Employability Through Machine Learning and Media Technology: Enhancing English Language Communication Skills

Dr. Jeton KELMENDI, Dr. Vinod Bhatt, Dr. Dev Brat Gupta,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study explores the potential of machine learning and media technology in maximizing employability by enhancing English language communication skills. It investigates the impact of incorporating these technologies in language learning methodologies and identifies their role in improving spoken and written English proficiency. The study analyzes the effectiveness of adaptive learning algorithms and interactive media tools in promoting language acquisition and fostering effective communication in professional contexts. Through a comprehensive literature review and empirical research, this study aims to uncover the potential benefits of these technological approaches in equipping individuals with the necessary language skills to succeed in the job market. The findings contribute to the ongoing discourse on the intersection of technology and language learning, offering insights for educators, learners, and policymakers interested in optimizing employability prospects through innovative approaches

Revolutionizing Democracy: A Cutting-edge Web-Based Voting System for Modern Electoral Processes Using AI

Dr. M. Sunil Kumar, P.Neeraja, Padichetty HariKrishna, Naijam Himaja, Tellagolla Sireesha,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract presents an Online Voting System that leverages Python algorithms along with a range of technologies and frameworks including Django, face recognition, OpenCV, Pillow, Scikit-learn, Tesseract, Mkdocs, Django REST API, SQLite3 database, Jinja tags, HTML, and CSS. The proposed Online Voting System aims to provide a secure, efficient, and accessible platform for conducting elections or voting processes. It incorporates robust security measures to ensure the integrity and confidentiality of votes. Face recognition, implemented using OpenCV and face recognition algorithms, allows for biometric authentication, minimizing the risks of fraudulent activities and impersonation. To ensure accurate vote counting and analysis, the system employs Python algorithms and Scikit-learn for data processing and classification tasks. Additionally, Tesseract, an optical character recognition (OCR) engine, enables the system to handle scanned documents or images containing text-based information. The Django framework is utilized to develop the web application, providing a user-friendly interface for voters to cast their votes securely. Django' s built-in authentication and authorization mechanisms, along with SQLite3 database, ensure data integrity and prevent unauthorized access. Mkdocs is employed to generate comprehensive documentation for the system, enabling easy maintenance and understanding of the codebase. Additionally, Django REST API is utilized to facilitate seamless integration with external services or applications. Jinja tags, HTML, and CSS are used for front-end development, allowing for a visually appealing and responsive user interface. This combination of technologies ensures an intuitive and accessible voting experience across various devices and platforms. The Online Voting System presented in this abstract offers a secure, efficient, and user-friendly solution for conducting elections. By leveraging Python algorithms and an array of cutting-edge technologies, the system provides robust security, accurate vote counting, and a seamless user experience, thereby addressing the challenges faced by traditional voting systems.

Accident Severity Detection Using Machine Learning Algorithms

Dr. M. Sunil Kumar, M.Sowmya vani, D.Vyshnavi Reddy, M.Hemalatha, A.Thanuja,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Road incidents constitute a substantial worldwide threat to public safety, leading to considerable financial and human detriment. Accurate and timely identification of the severity of a disaster is critical for facilitating efficient emergency response and allocating resources. This article outlines a methodology for determining the severity of road accidents via machine learning and the extraction of various characteristics from accident data. The research is centered on the construction of a predictive model by integrating variables including meteorological conditions, road type, vehicle characteristics, and human factors into historical accident data. The dataset comprises various criteria for determining the severity of an accident, including its location, time of occurrence, and vehicle speed. Severity levels are classified into various categories that correspond to distinct degrees of harm and destruction. The predictive model is trained utilizing supervised learning in the proposed method. Initial preprocessing of the dataset addresses outliers, absent values, and categorical variables. Methods of the process of feature engineering is employed to extract pertinent attributes from the data. In order to facilitate model evaluation and training, the dataset that has been preprocessed is divided into distinct evaluating and training groups. Random forests, decision trees, and support vector machines are all instances of machine learning methodologies. that were implemented during the accident severity detection model apos; s training process. To evaluate the effectiveness of each technique, the utilization of pertinent performance metrics includes accuracy, precision, recall, and F1-score. Based on experimental data, the proposed methodology provides road accident severity detection that is both precise and dependable. The accident severity levels are effectively classified by the trained model using the features that were provided. The provided information has the potential to assist emergency response teams in effectively allocating resources and promptly responding to incidents of different magnitudes. This study as a whole presents a machine learning-based solution for determining the severity of road incidents. thereby providing a valuable instrument to improve emergency response systems and road safety. By integrating the developed model into pre-existing traffic management systems, real-time accident severity predictions can be generated, which in turn reduces response delays during emergency situations and facilitates efficient resource allocation

Internet of things (IoT) applications using smart materials and sensor technologies to prevent COVID-19

Dr. Jampani Chanda Sekhar, Mrs.Anitha Christy Angelin.P, Dr.R.Giri Prasad, Mr.Samson Ebenezar Uthirapathy, Mr. Prashant Agrawal, Mr Trilok Suthar,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

In order to effectively screen patients during the COVID-19 pandemic, novel strategies have been required on a global scale. In this regard, intelligent materials and the Internet of Things (IoT) have proven to be indispensable. These technologies provide alternatives to traditional diagnostic tests, increase patient satisfaction, and decrease hospital readmissions. By integrating IoT sensor technologies with intelligent materials, they demonstrate analytical capabilities that facilitate the timely diagnosis of COVID-19 symptoms. This study assesses the viability of IoT-connected ubiquitous, photosensitive, and electrically sensitive devices for assisting COVID-19 patients effectively by integrating biosensors to monitor symptoms such as fever and respiratory difficulties. By incorporating COVID-19 diagnostics, intelligent materials, biosensors, and viral detection examples, the study demonstrates how IoT frameworks can be implemented in intelligent healthcare

Technology for creating an intelligent system for managing the activities of the department of a higher educational institution

Ozoda Safibullayevna Abdullayeva, Baxodir Sayitkamolxonovich Azamxonov,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The main element of the activity leading to the creation of software is modeling. The designed department management model will allow you to visually demonstrate the desired structure and behavior of the system.In the implementation of the software product, the following stages were defined: development of requirements for the creation of an intelligent information system for managing the activities of the department; 2. The stage of the project implementation, which includes the task - to determine the totality of the software product, tools and means for the implementation of an intelligent information system for managing the activities of the department; 3. The stage of correction and control, the purpose of which is to identify the advantages and disadvantages in the intelligent information system for managing the activities of the department, as well as eliminating them. It is advisable to identify the criteria for evaluating the system, as well as experimental verification of the developed intelligent information system for managing the activities of the department and determining the results of the activity from its implementation.To determine the criteria for evaluating the effectiveness of the information system, testing of the created software product was carried out. Testing a software product is the most important process, consisting of identifying, correcting and correcting errors found in a program created on an electronic computer.To make sure that the intelligent information system meets the declared characteristics and requirements, the following criteria were defined: 1. Functional testing is intended to verify the designed technical task, that is, the requirements set for the functionality of the system. Examples are load testing (tools: Grinder, Locust, LoadStorm), configuration testing of an information system, and others; 2. Security testing to check the safety and reliability of data storage, use of user access by individual login and password, protection of personal data by system users; 3. Testing in use. This testing involves checking the effectiveness of an intelligent information system and the convenience of its use (time spent to perform certain actions on the part of users).

Power quality enhancement of solar based microgrids using ML and AI

K. Paul Joshua, Dr.C.Vennila, Kurikyala Prasad Yadav, Dr. D. Kirubakaran, Dr. Vartika Kulshrestha, Praveen B.R,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Microgrids powered by using solar power are at- tracting lots of attention as a cost-powerful and environmentally pleasant technique of producing decentralized power. The elec- tricity satisfactory of such microgrids is challenged by using the fluctuating and intermittent nature of solar power. The approach described on this work uses machine learning (ML) and synthetic intelligence (AI) processes to enhance the electricity high-quality of sun-primarily based microgrids. The counseled method uses present day ML algorithms to forecast sun power production and foresee in all likelihood changes within the micro grid’s energy output. The ML models can correctly predict modifications in sun irradiance, climate, and other critical factors by analyzing ancient facts and real-time records, allowing proactive control of the micro grid’s power float. Compared to traditional manage procedures, the suggested ML and AI-based totally solution has some of the benefits, consisting of advanced power best, proactive strength control, and greater forecasting accuracy. The usefulness of the strategy in minimizing interruptions to linked loads, improving balance, and lessening the have an effect on of sun energy oscillations on the micro grid is proven by simulation and experimental findings. It has a top-notch deal of capability

Real-Time Identification of Medicinal Plants Using Deep Learning Techniques

Mr. S. Girinath, MS. peddinti Neeraja, Dr. M. Sunil Kumar, S. Kalyani , B. Lakshmi Mamatha, N.R.T. GruhaLakshmi,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The majority of people throughout the world utilize medicinal plants as an alternative source of medications as well as a key source of therapeutic compounds. As a result of recent advances in computer vision, plant identification from images is currently a fast-emerging study subject. Several discoveries exhibited high precision, accuracy, and real-world applicability. The goal of this research was to explore into precise automated identification of medicinal plants. It is difficult to discern a leaf from its background due to the inconsistent lighting in the environment. We present a method for determining the species of a plant from a sample of its leaves . We provide a brand-new dataset of medicinal plants that comprises images of ten (10) distinct plant species classifications as well as one. Convolutional neural networks (CNNs) are used in the proposed method to automatically extract useful information from photographs of plants. The CNN model is trained using a sizable dataset of high-resolution photos of many types of medicinal plants. The trained model can recognize different plant species based on their distinctive visual traits, such as the shape, color, and texture of their leaves. The created system is deployed on a mobile or embedded platform, allowing users to take pictures of plants using a smartphone or portable device, to enable real-time identification. The trained CNN model is then used to analyze the acquired picture, quickly producing an accurate classification result.

Securing Trust in the Connected World: Exploring IoT Security for Privacy in Connected Environments

Sheetal, Deepa, Alli.A,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract delves into IoT security measures to ensure privacy in connected environments. It examines encryption, authentication, access control, and data privacy techniques. Key considerations include end-to-end security, vulnerability mitigation, regulatory compliance, and user trust. By addressing these challenges, trust can be established in the connected world, enabling the widespread adoption of IoT technologies while safeguarding user privacy.

Transforming Homes into Smart Living Spaces: Exploring Advancements in IoT-Based Home Automation Systems

Dr.Reepu,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The potential and developments of Internet of Things-based home automation systems are examined in this abstract. for transforming houses into smart living places. It explores the use of networking technology, data analytics, and intelligent devices to allow smooth automation and customized interactions. convenience, security, and energy efficiency and user-centered design are all important factors to consider. Homes may be equipped using automated technologies that raise living standards generally and enhance comfort and efficiency by using Internet of Things technology.

By Leveraging Technology for Sustainability, Environmental Monitoring via IoT

Jotiram K Deshmukh, Ritesh Tirole, Anand Bhaskar,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Nanotechnology is making a substantial contribution to the development of a wide variety of technological and industrial disciplines, and is even causing some of these industries to undergo a revolution. These industries encompass not only electrical, agricultural, medical, and electronic technology but also domestic food safety and security, transportation, and a great lot of other disciplines as well. In the modern world, discoveries in chemistry, mechanics, materials science, and biology are leveraged by nanotechnology to assist the synthesis of new materials with their own distinctively their own properties after the nanoscale have been employed to determine their structures. The many different ways in which nanotechnology has been put to use over the last several decades are investigated in this article. The term "nanotechnology" alludes to the ways in which it paves the way for other technological advancements by acting as a groundbreaker.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

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