NDLI: Cloud Insights

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A Comprehensive Methodology for Detecting Stress and Performance of Students using Machine Learning

A Deep Learning Model for Classification of Gender and Age from Facial Images

A Machine Learning Methodology for Diagnosing Chronic Kidney Disease and Severity Analysis

AI Chatbot Framework as a Service

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An AI Based Social Distance Monitoring System

An Embracive Study of Image Caption Generation using Pre-Trained Neural Networks

Automatic License Number Plate Recognition System

Brain Tumor Detection using Deep Learning Techniques

Cartoonifygan: Generative Adversarial Network for Image Cartoonization

Contrastive Analysis of Supervised and Unsupervised Learning Techniques for Voice Pathology Detection and Classification

Covid-19 Diagnosis from CT Scans using Deep Learning

Credit Card Fraud Detection using Machine Learning Approach

Decentralized Crypto Exchange

Deep Learning-Based Air Pollution Prediction in Smart Cities

Detection of Landslide using Machine Learning

EPR Portal for Plastics

Epilepsy Seizure Detection using EEG Signal

EventPub: A Project Report

Face Mask Detection using YOLO V5

Fake Profile Detection on Social Networking Websites

Feature Based Automatic Image Stitching

Finger Vein Biometric Recognition using Convolutional Neural Network

Fire Detection in Video Surveillance Applications

Forensic Face Sketch Construction and Recognition

Handwritten Signature Verification

Image Restoration using Deep Learning

Integrate Cucumber with Selenium Webdriver for Website Automation

Intelligent System for Descriptive Answer Evaluation

Intrusion Detection System Based on Machine Learning

KL Onboarding : Project Management System

KL One It: One Stop Platform for IT Tickets

KL Pulse: Employee and Leave Management System

Location Based Student Monitoring System

MDS Operations: A Project Report

ML Based Plant Leaf Disease Prediction

Malware Detection using Machine Learning

NFT Marketplace

Notify Publisher: A Project Report

Phishing Attack Detection using Machine Learning

Portal for Regulation of Air Pollution in Non-Attainment Cities (Prana)

Real-Time Accident Detection using VIT-B/32

Real-Time Facial Expression Detection using Convolutional Neural Network

Secure-Vote: A Voting Dapp on the Metis Stardust Blockchain

Skin Disease Detection using Deep Learning

Smart Online Voting System

Sudoku Solver using ANT-Colony-Optimization Algorithm

TekactPub: A Project Report

Tomato Leaf Disease Detection using Deep Learning

Traffic Sign and Light Detection using YOLO V5

Trigger Publisher: A Project Report

Uptime - "No Time for Downtime"

Vehicle Detection using Deep Learning

Video-Based Action Recognition using Deep Learning

Violence Detection using Deep Learning Techniques

Web Automation using Selenium with Cucumber Framework

Yoga Pose Detection and Correction

Structural Engineering & Construction Management (SECM)

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Urban Planning (UP)

Cloud Insights

Content Provider	TKM College of Engineering
Advisor	Vaheetha Salam
Author	S.V., Nithin
Abstract	CLOUD INSIGHTS, is a web platform that tracks and evaluates all of a company’s cloud resources. Although all platforms offer consumer monitoring, there is no way to keep track of several resources in one place. This application solves the issues by providing a single platform for monitoring several resources. The primary goal of development is to keep track of the company’s cloud usage. Because my company is increasingly using the Azure platform, and all of our applications use it, we created the initial version of Azure platform support. We can add many Azure accounts and manage them all from one location. Everything in this application has been designed in accordance with the SRS requirements. It displays all of the subscriptions’ detailed consumption as well as resource level usage. All cloud platforms will be supported in the forthcoming edition. We are in the process of planning the next version. Cloud Insights is a self-adjusting monitoring server that may be used for both agent-based and centralized monitoring. Custom monitors and agents can be added to Cloud Insights. When a specific event occurs or a specific threshold is crossed, the monitors have an idea of an implicit action to be executed. These actions enable cloud applications to self-heal when they encounter problems. Manual involvement may be required for some actions. In these circumstances, an action is nothing more than a notification.
Language	English
Publisher Date	2022-05-01
Access Restriction	Open
Subject Keyword	Intelligent Lens Data Center Management Big Data Cloud Service Consumers Azure Platform Application Programming Interface (API) Python
Content Type	Text
Resource Type	Thesis

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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