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Farmers often struggle with low crop yields due to missing weather updates, late disease detection, and limited guidance on suitable crops. Expert support is not always available, especially in rural areas. This project addresses these challenges with a mobile app that provides real-time weather insights, AI-based disease detection from images, and smart crop suggestions to support better farming decisions..

→ The system enables users to capture crop images through the smartphone camera, which are analyzed using a deep learning model to identify diseases and recommend appropriate treatments. The application also provides weather-based crop suggestions and an intuitive interface introducing major crop categories and common diseases. By integrating environmental data with image-driven diagnostics, the solution aims to enhance decision-making, reduce crop losses, and improve overall farm productivity.

Farmers often struggle with low crop yields due to missing weather updates, late disease detection, and limited guidance on suitable crops. Expert support is not always available, especially in rural areas. This project addresses these challenges with a mobile app that provides real-time weather insights, AI-based disease detection from images, and smart crop suggestions to support better farming decisions..

→ The Rural Farmer Support App is a multilingual mobile application designed to empower farmers in rural communities. It provides real-time weather updates, personalized crop recommendations, and government scheme alerts based on the user’s location and preferred language. By offering localized and easy-to-understand farming insights, the app enables farmers to make informed decisions, improve crop yield, and increase income.

Credit card fraud is a major challenge for financial institutions, resulting in significant financial losses and compromised customer trust. Fraudulent transactions are rare compared to legitimate ones, creating a highly imbalanced dataset that makes accurate detection difficult. Traditional rule-based systems often fail to identify new or evolving fraud patterns.

→ Detecting fraudulent credit card transactions using machine learning techniques. It addresses the challenge of highly imbalanced datasets by applying preprocessing steps, feature scaling, and data balancing methods such as SMOTE and class weighting

Many people are interested in Ayurveda but struggle to find reliable, easy-to-understand information about remedies, lifestyle practices, and wellness guidance in one place. Existing resources are often scattered, non-interactive, or difficult for modern users to navigate, making it hard to connect ancient Ayurvedic wisdom with today’s healthcare needs.

→ AyurSutra is a web-based Ayurvedic healthcare platform that brings ancient wellness knowledge into a modern, user-friendly interface. It helps users explore Ayurvedic concepts, remedies, and lifestyle tips in an organized way, making traditional healthcare more accessible, understandable, and relevant for everyday use.