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检索条件"机构=Artificial Intelligence and Data Science Vishwakarma Institute of Technology"

共 3933 条记录，以下是11-20 订阅

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CropOptimizer: Intelligent Crop Forecasting and Decision Support System 2

CropOptimizer: Intelligent Crop Forecasting and Decision Sup...

引用

2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Jadhav, Balasaheb Ligde, Vaidehi Malpani, Rushikesh Lakhotiya, Rushikesh Savale, Phalguni Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350388916

CropOptimizer is an innovative crop forecasting and decision support system designed to revolutionize agricultural practices. Comprising five key modules - crop recommendation, fertilizer suggestion, disease detection, weather forecasting, and market price tracking - CropOptimizer combines modern technologies to help farmers make informed decisions. The crop recommendation module, leveraging XGBoost, uses soil, climate, and nutrient data to select suitable crops that maximize production potential. The fertilizer suggestion module provides specialized guidance based on specific crop and soil characteristics, ensuring effective nutrient management through XGBoost. The disease detection module employs deep learning with ResNet-9 for image processing to identify plant diseases from leaf images, followed by specific treatment recommendations, achieving high accuracy. Weather forecasting offers a 7-day forecast, including rainfall predictions, based on plant type, state, and city through an API. Market price tracking provides live market prices for various crops, enabling farmers to make informed selling decisions. By integrating these components, CropOptimizer increases crop yield and sustainability, fostering a more resilient agricultural ecosystem and improving food security and economic success. © 2024 IEEE.

关键词： Crop rotation

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Design and Evaluation of an AI-Powered Conversational Agent for Personalized Mental Health Support and Intervention (MindBot) 5

Design and Evaluation of an AI-Powered Conversational Agent ...

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Kambare, Shweta M. Jain, Kriya Kale, Ishika Kumbhare, Vibhor Lohote, Sakshi Lonare, Shubham Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331530013

This research study describes the design and evaluation of an interactive MindBot to help a person deal with depressive Sentiments and to support individuals experiencing depressive symptoms by providing timely, interactive, and empathetic engagement. With the growing trend of mental health issues and a lack of adequate resources to cope, the need for innovative solutions is of great importance. In this MindBot, users will be connected to each other to communicate their Sentiments and seek support. The integration of NLP and LLMs by the chatbot fosters meaningful conversations and ensures timely support to users. Computational architecture optimizes response generation to control the processing cost related to LLMs while striking a balance between conversational richness and efficiency. This method allows for real-time communication without sacrificing the caliber of involvement. The chatbot's integration of NLP and LLMs promotes meaningful discussions and guarantees that consumers receive prompt service. The utilization of predefined response templates combined with dynamic responses generated by GPT -3.5-turbo further improved the implementation's performance in conversational capability. The paper covered the system architecture, methodology, and results achieved, with an emphasis on the contribution of sentiment analysis and the contributions of the chatbot towards mental health support. User happiness, emotional correctness, referral appropriateness, and the model's capacity to sustain coherent conversation even in the face of small user input errors are all used to gauge how effective the model is. The results indicate that the effectiveness of mental health interventions and user engagement are increased when sentiment analysis and sophisticated language models are combined. It was demonstrated that the impact of integrating advanced language models along with sentiment analysis can have a huge bearing on enhancing the user engagement factor as well as the ef

关键词： Chatbots

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A User-Friendly Approach to Object Removal: CGANs and STTN for Enhanced Image and Video Editing 15

A User-Friendly Approach to Object Removal: CGANs and STTN f...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Bailke, Preeti Naikwad, Aditya Pal, Aman Naik, Aryan Deshmukh, Bhairavi Bharambe, Tejas Vishwakarma Institute of Technology Pune India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798331300579

This research introduces an advanced object removal tool addressing the challenges in computer vision and image *** Generative Adversarial Networks (GANs) with Python, TensorFlow, and OpenCV, the tool utilizes conditional GANs for efficient learning of patterns and *** employing matched image sets comprising original images and corresponding object masks, the program generates realistic and aesthetically pleasing in-painted ***, a user-friendly web application is developed, allowing users to select input images and define specific regions for *** tool's versatility extends to video editing, incorporating a Spatial-Temporal Transformer Network (STTN) for seamless removal of objects in both spatial and temporal *** comprehensive solution enhances user engagement and expands the tool's applicability to eliminating unwanted elements from videos. © Grenze Scientific Society, 2024.

关键词： Computer vision

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Automated Medicinal Plant Identification through Image Processing and Machine Learning 8

Automated Medicinal Plant Identification through Image Proce...

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Kadam, Yash Yache, Ajay Solunke, Pavankumar Tati, Ramakant Kachhoria, Renu Buchade, Amar Vishwakarma Institute of Information Technology Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350391770

This research addresses the pressing challenge of accurately identifying medicinal plants in India's Ayurvedic Pharmaceutics, aiming to mitigate issues stemming from morphological variability and market adulteration. Traditional methods of plant identification are hindered by laborious processes and the potential for error, underscoring the need for an automated solution. Leveraging the power of advanced image processing and machine learning, our proposed software framework integrates the Xception model and early stopping fine-tuning to automate plant identification based on plant images. The methodology involves curating a comprehensive dataset of labelled plant images representing diverse medicinal plants, subsequently employing image preprocessing techniques to extract salient features like color, texture, and shape. The Xception model, renowned for its prowess in image recognition tasks, serves as the backbone architecture for both feature extraction and classification. To further optimize model performance and mitigate overfitting, early stopping fine-tuning techniques are applied. Through rigorous experimentation and validation, our research demonstrates the efficacy of this approach in accurately identifying medicinal plants, thereby fostering confidence and trust within the herbal medicine supply chain. By seamlessly integrating modern technological advancements with traditional botanical knowledge, our framework not only streamlines the identification process but also contributes to the sustainable utilization of herbal medicine resources. Ultimately, this research represents a pivotal step towards establishing a robust and reliable system for identifying medicinal plants, facilitating informed decision-making, and promoting the long-term viability of herbal medicine practices in India and beyond. © 2024 IEEE.

关键词： Medicinal chemistry

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Comprehensive Image Analytics for Diversion of Forest Land 4

Comprehensive Image Analytics for Diversion of Forest Land

引用

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

作者： Kambare, Shweta Rudrabhate, Aabha Divate, Srinath Taktode, Tapasvi Tekam, Anurag Thakare, Yatharth Vishwakarma Institute Of Technology Department of Artificial Intelligence & Data Science Pune India

ISBN: (纸本)9798331529635

This research study presents an initiative that seeks to revolutionize the process of tree enumeration and categorization, traditionally carried out manually. It harnesses the power of image analytics, the system aims to streamline the process, reduces manpower requirements, and lowers costs, all while minimizing the environmental impact of development projects. By incorporating techniques such as Binary Image Thresholding and Convolutional Neural Networks, the system categorizes and monitors trees using high-resolution satellite imagery. Analytical tools, including YOLOv8 for object detection and NDVI analysis for vegetation classification, are deployed to optimize land allocation and pathfinding. The proposed system's design is centered around efficiency and environmental consciousness. An interactive user interface is developed ensuring accessibility and ease of use. The integration of Google Maps API enables real-time monitoring of forest changes, supporting effective decision-making for deforestation and reforestation efforts. © 2024 IEEE.

关键词： Convolutional neural networks

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The Social Score: A Social Credit System Using Blockchain 5

The Social Score: A Social Credit System Using Blockchain

引用

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Ubale, Ganesh Bawake, Vasundhara Badkas, Kshitij Bhade, Shourya Batkadli, Aarya Belure, Prasad Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331518097

The Chinese Social Credit System (SCS) serves as a large-scale example of behaviour tracking, adapted here for a college-level social scoring framework. The system monitors student activities, achievements, and certificates to promote positive behaviour. Certificates generated by administrators are hashed and stored on the blockchain, creating an immutable, tamper-proof record that cannot be altered or forged. Blockchain technology facilitates decentralized verification, allowing certificates to be authenticated independently when uploaded by students to enhance their social scores. This approach fosters trust through enhanced transparency and security. The student dashboard provides access to certificate uploads, activity records, violation reporting, and reward monitoring, while the administrative interface supports the management of reports, violations, leaderboards, and certificate generation. The blockchain-based design ensures that processes, from certificate issuance to verification, remain secure, transparent, and resistant to tampering, establishing a reliable framework for managing social scores. © 2024 IEEE.

关键词： Blockchain

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MediScan : A Robust Xception-Based Skin Disease Classification System with Blockchain Integration 3

MediScan : A Robust Xception-Based Skin Disease Classificati...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Ubale, Ganesh Kashyap, Aryan Kalal, Sahil Kamble, Omkar Pande, Soham Mhamane, Saniya Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350354348

This research aims to revolutionize the prediction of skin diseases in patients by employing advanced deep learning methodologies. By integrating transfer learning with Xception and Convolutional Neural Network (CNN) models, we develop a robust predictive framework. Transfer learning is leveraged to accelerate training and improve accuracy by using pre-trained models on patient-specific data. To address data security concerns, we incorporate blockchain technology to securely store patient data, ensuring transparency and maintaining integrity. The model's efficacy is demonstrated on a comprehensive skin disease image dataset comprising over 3,396 images across 6 different skin conditions. Results show an improvement in diagnostic accuracy to 85%, a significant enhancement over traditional methods. This integration of transfer learning, advanced CNN models, and blockchain establishes a framework that enhances dermatological diagnostics and ensures a secure, transparent ecosystem for managing patient health data, setting new standards in predictive analytics. © 2024 IEEE.

关键词： Convolutional neural networks

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CogniVisio: Fusion Image Classifier 2

CogniVisio: Fusion Image Classifier

引用

2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Mundargi, Zarinabegam Shinde, Aryan Bahirat, Shravani Das, Shreya Deokar, Om Shetiya, Dipasha Vishwakarma Institute of Technology BTech- Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350360523

CogniVisio is an innovative project that leverages state-of-the-art technologies such as Google Colab, Python, TensorFlow, Convolutional Neural Network (CNN) Inception for developing a robust image classification system. The project addresses the challenge of enhancing image classification accuracy by employing a fusion approach that combines the strengths of image generation and the powerful feature extraction capabilities of CNN Inception. With a dataset comprising 8732 images, our methodology achieves an impressive accuracy of 86.86%, showcasing the effectiveness of the proposed fusion image classifier. The utilization of cloud-based computing through Google Colab provides scalability and accessibility, making CogniVisio a versatile solution for image classification task. © 2024 IEEE.

关键词： Image recognition

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Smart Attendance System using Geolocation 15

Smart Attendance System using Geolocation

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Bailke, Preeti Gujarathi, Om Gundecha, Sanskar Gore, Om Jadhav, Asawari Chaudhari, Jayesh Vishwakarma Institute of Technology Pune India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798331300579

This research describes a mobile attendance system that was created with Flutter and Appwrite and includes the three crucial components of location, teacher certification, and fingerprint authentication. The solution uses GPS location to assure precise attendance tracking, instructor verification to ensure authorized access, and biometric fingerprint authentication to stop fraudulent attendance. Our analysis shows increased security and accuracy, providing a dependable answer for attendance control in educational institutions. This study intends to help both students and educational institutions by advancing the field of attendance tracking systems. © Grenze Scientific Society, 2024.

关键词： Biometrics

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Driver's Safety Measures: A Blind Spot and Drowsiness Detection System using IoT Components and Python Library 15

Driver's Safety Measures: A Blind Spot and Drowsiness Detect...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Mundargi, Zarinabegam Ingale, Bhushan Jadhav, Makarand Kamble, Omkar Kayade, Parth Lanjewar, Harsh Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Pune411037 India

ISBN: (纸本)9798331300579

This research paper examines the implementation of advanced driver safety measures focused on drowsiness and blind spot detection, utilizing innovative technologies including OpenCV, Firmata, and PyMata. As traffic accidents continue to be a significant concern worldwide, proactive measures to enhance driver safety are crucial. The study explores the development and integration of drowsiness detection systems and blind spot detection technologies in vehicles to mitigate the risk of accidents caused by these factors. This research paper provides a comprehensive overview of the current state of driver safety measures involving drowsiness and blind spot detection. It highlights the advancements, challenges, and opportunities in these areas, ultimately contributing to the development of safer transportation systems and reducing the risk of accidents caused by drowsiness and blind spot-related factors. © Grenze Scientific Society, 2024.

关键词： Safety factor

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