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1st International Conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Dash, Annada Mathur, bhavini Patil, Piyusha B.Tech in Computer Engineering Honors in Data Science and ML Cummins College of Engineering for Women Pune India B.Tech in Computer Engineering Cummins College of Engineering for Women Pune India

ISBN: (纸本)9798350355611

This research explores the integration of advanced AI technologies, specifically Google's Gemini-1.5-Flash-001 model and Vertex AI, into the development of EcoTrack-a mobile application that helps users monitor and reduce their carbon emissions. At the core of this innovation is Ecobot, an AI-powered chatbot embedded within EcoTrack, designed to deliver personalized, actionable insights on sustainability. by leveraging Gemini's capabilities alongside real-time data through Vertex AI, Ecobot enhances user engagement by offering tailored advice on reducing their carbon footprint. The study illustrates how Ecobot processes various data points, including user input and environmental metrics, to generate precise recommendations for users looking to make more sustainable choices. The focus of this work is on the importance of scalable AI frameworks that can adapt to evolving sustainability goals while efficiently managing real-time data. Additionally, this paper addresses the ethical dimensions of using AI for environmental purposes, discussing its potential to drive meaningful action at both the individual and societal levels, contributing to the global effort to combat climate change. © 2025 IEEE.

关键词： Carbon sequestration

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Energy conservation: Virtual energy audit of an industrial plant

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Materials Today: Proceedings 2023年 72卷 1882-1889页

作者： Joshi, Atharva Khandelwal, Niyati Suryavanshi, Yash broota, Sumir Kurulekar, Maya Dhaneshwar, Pranav LY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune 411048 India TY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune 411048 India Department of Engineering Science Vishwakarma University MS Pune 411048 India Department of Mechanical Engineering Vishwakarma University MS Pune 411048 India

Energy consumed by manufacturing industries constitutes a large part of the total energy consumption of the world. In India, almost 50% of the total energy consumption is done by Industries. Energy bills are usually a major contributor to the operating expenses of a company. Industries can profit from the opportunities coming out of energy saving by the implementation of effective energy management using appropriate tools. An industrial plant layout is usually designed within several constraints, mainly operational. The objectives were decided by the company to study and identify energy gaps in the industrial plant and suggest suitable solutions to reduce energy consumption all while reducing the average working temperature inside the plant from 38 °C to an ideal value below 30 °C, preferably without installing an air conditioning system. The study was divided into two parts;Primarily, Data collection and observations of the plant operations and then building Energy Modelling and simulation. The base model with existing conditions was modelled, simulated and validated with historical energy consumption data and temperature readings taken inside the plant. The proposed solutions include limited modifications in the existing set up considering the operational constraints. The simulations run with proposed modifications indicate a maximum of 11 % savings in energy consumed by lighting and potential to reduce temperature to 33.23 °C from 38 °C. The effect of ambient factors according to the geographical location such as sun exposure, wind directions, humidity were also taken into consideration. © 2023

关键词： Energy utilization

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Deep Learning for Glioblastoma Subtyping: Leveraging DenseNet-201 in brain Tumor Radiogenomic Classification 1

Deep Learning for Glioblastoma Subtyping: Leveraging DenseNe...

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1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - RObINS 2024

作者： Jesuraj, S. Alvin Evangelin Sonia, S.V. Shirley, C.P. Karunya Institute of Technology and Sciences B.Tech Computer Science and Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India

ISBN: (纸本)9798350372748

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI brain Tumor Radiogenomic Classification aimed at predicting the genetic subtype of glioblastoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying glioblastoma cases based on MGMT promoter methylation status, a critical biomarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhibits robust performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ability to effectively distinguish between MGMT promoter methylation-positive and negative glioblastoma cases, offering valuable support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of glioblastoma genetics and guiding personalized therapeutic interventions, ultimately contributing to improved patient outcomes in brain cancer management. © 2024 IEEE.

关键词： biomarkers

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Federated Learning for Kidney Disease Prediction using Combined LSTM and MLP Models

Federated Learning for Kidney Disease Prediction using Combi...

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International Conference on Communication Systems and Network technologies (CSNT)

作者： Anurag Pathak Anshuman Pandey B.Tech in Computer Science (AI & ML) GLA University Mathura Uttar Pradesh India B.Tech in Computer Science GLA University Mathura Uttar Pradesh India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Kidney disease (KD) is a prevalent global health issue, and early prediction is critical for improving patient outcomes. In this study, we propose a federated learning approach that combines Long Short-Term Memory (LSTM) networks with Multi-Layer Perceptron (MLP) models for kidney disease prediction. The LSTM component captures temporal dependencies in the data, while the MLP enhances the model’s ability to classify based on learned features. The federated learning framework ensures data privacy by keeping patient information decentralized across multiple hospitals. Experimental results show promising accuracy, precision, recall, and F1 score, demonstrating the potential of combining LSTM and MLP for healthcare applications.

关键词： Privacy Solid modeling Accuracy Federated learning Hospitals Predictive models Solids Long short term memory Kidney Diseases

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Implementing blockchain based Security in EHR Using Ganache 6

Implementing Blockchain Based Security in EHR Using Ganache

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Satyam, Kumar Sharma, Ayush Devi, Runumi B.Tech in Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida India Galgotias University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350304480

A blockchain-based electronic health record (EHR) system has been proposed to manage patient data and maintain computerized records across different healthcare institutions. The main objective of this system is to provide immediate access to patient health information while addressing concerns about privacy and security. It is developed on the Ethereum network using programming languages, tools, and technologies such as Ganache, Solidity, and ***. The system uses smart contracts to provide security and privacy, and transactions are verified and propagated to the entire decentralized network. The system includes a cryptocurrency wallet (MetaMask) with a centralized privacy system that allows authorized parties to access and secure records quickly. The proposed system aims to achieve several objectives such as allowing users to receive the same data simultaneously, increasing efficiency, building trust, and reducing barriers. It secures data storage by restricting user access and enables the secure transfer of patient medical records. The solution allows for better transparency and ownership of sensitive data, which can be recorded and safeguarded via blockchain technology, therefore assisting the healthcare sector. This paper describes a medical record system and a new protocol that can be used quickly and safely, paving the way for more secure and efficient healthcare systems. Overall, the proposed system offers potential solutions to the challenges associated with traditional EHR systems and has the potential to revolutionize the healthcare industry. © 2023 IEEE.

关键词： blockchain Electronic Health Record Ethereum Ganache IPFS MetaMask

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Prediction of Herbs with its benefits using Deep Learning techniques

Prediction of Herbs with its Benefits using Deep Learning Te...

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2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022

作者： begum, M. Sharmila Haris, R. Vetrimaran, V. Raj, P. Ashwin B.Tech Computer Science and Engineering Pmist Tamil Nadu Vallam Thanjavur India

ISBN: (纸本)9781665478847

Automated plant identification is a very promising solution for bridging the taxonomic gap, which is receiving much attention from botany and computer science. As machine learning technology advances, more complex models have been proposed to automate crop identification. Herbal remedies are considered in the pharmaceutical industry due to fewer harmful side effects and less expensive than modern medicine. based on these data, many researchers have shown great interest in studying the recognition of natural herbal medicines. There are various possibilities for moving towards solid phase production capable of accurately discriminating medicinal plants in real time. In this project, efficient and reliable machine learning algorithms for plant catalogues using leaf images used in recent years are being studied. The review covers image processing techniques used to locate leaves and extract important leaf features from other machine learning steps. These deep learning stages are classified according to their function when it comes to discriminating leaf images based on common plant characteristics, i.e. shapes, ridges, textures and combinations of many elements. Then you get results using herbs with improved accuracy. The test results indicate that the proposed system provides an improved level of accuracy. © 2022 IEEE.

关键词： Deep neural networks

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Enhancing Carbon Emission Tracking with Gemini: An AI Solution for Sustainable Development

Enhancing Carbon Emission Tracking with Gemini: An AI Soluti...

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AIML-Applications for Engineering & technology (ICAET), International Conference on

作者： Annada Dash bhavini Mathur Piyusha Patil B.Tech in Computer Engineering Honors in Data Science and ML Cummins College of Engineering for Women Pune India B.Tech in Computer Engineering Cummins College of Engineering for Women Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

关键词： Climate change Carbon dioxide Chatbots Real-time systems Mobile applications Artificial intelligence Sustainable development Recommender systems Monitoring

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bioCrypt: Gradient-based facial encoding for key generation to encrypt and decrypt multimedia data

arXiv

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arXiv 2024年

作者： Patel, Ankit Kumar Paul, Dewanshi Giri, Sarthak Chaudhary, Sneha Gautam, bikalpa B.Tech Electronics & Computer Engineering Graduated from VIT University Chennai India B.Tech Computer Science & Engineering Graduated from VIT University Vellore India

Security systems relying on passwords are vulnerable to being forgotten, guessed, or breached. Likewise, biometric systems that operate independently are at risk of template spoofing and replay incidents. This paper introduces a biocryptosystem utilizing face recognition techniques to address these issues, allowing for the encryption and decryption of various file types through the Advanced Encryption Standard (AES). The proposed system creates a distinct 32-bit encryption key derived from facial features identified by Histogram of Oriented Gradients (HOG) and categorized using Support Vector Machines (SVM). HOG efficiently identifies edge-aligned facial features, even in dim lighting, ensuring that reliable biometric keys can be generated. This key is then used with AES to encrypt and decrypt a variety of data formats, such as text, audio, and video files. This encryption key, derived from an individual’s distinctive facial traits, is exceedingly challenging for adversaries to reproduce or guess. The security and performance of the system have been validated through experiments using several metrics, including correlation analysis, Shannon entropy, normalized Hamming distance, and the avalanche effect on 25 different file types. Potential uses for the proposed system include secure file sharing, online transactions, and data archiving, making it a strong and trustworthy approach to safeguarding sensitive information by integrating the uniqueness of facial biometrics with the established security of AES encryption. © 2024, CC bY.

关键词： Hamming distance

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Energy conservation: Virtual energy audit of an industrial plant

Energy conservation: Virtual energy audit of an industrial p...

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作者： Joshi, Atharva Khandelwal, Niyati Suryavanshi, Yash broota, Sumir Kurulekar, Maya Dhaneshwar, Pranav LY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune411048 India TY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune411048 India Department of Engineering Science Vishwakarma University MS Pune411048 India Department of Mechanical Engineering Vishwakarma University MS Pune411048 India

关键词： Energy utilization

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A Novel Mobile Application to Empower Visually Impaired Individuals to Perform Independent Day-to-Day Activities 8

A Novel Mobile Application to Empower Visually Impaired Indi...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Paul, Dewanshi Patel, Ankit Kumar Dhanush, R. Amutha, S. Vellore Institute of Technology B.Tech Electronics and Computer Engineering School of Electronics Engineering Chennai India Vellore Institute of Technology School of Electronics Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350376425

People with visual impairments struggle or require assistance from others to perform day-to-day activities. Hence, people with visual impairments suffer from a lack of independence and quality of life. For this purpose, the app proposed in the paper is a unique, creative, innovative mobile application that will aid people with visual impairments in becoming independent and improving their quality of life. This paper introduces the novel mobile application's three key features: QR (Quick Response) code scanning, OCR (Object Character Recognition), and an Indoor Object Navigation System. The QR code scanning feature allows users to make informed decisions quickly by providing comprehensive information about products or their environment. The OCR functionality reads out the printed text aloud and helps the users understand written content with the help of audio. The indoor object finder or navigation system is a noteworthy advancement in Assistive technology. The system allows users to select a target object and then move their camera around their surroundings;once the object is detected, the app provides voice instructions about the directions of the target object to guide users towards it. by integrating these complex technologies, the novel mobile application provides an innovative approach to some of the issues encountered by those with visual impairments. The application aims to increase user independence, improve functionality, and build confidence to improve their daily experiences and engagements with the world around them. © 2024 IEEE.

关键词： Navigation systems

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