CropGuard is a cutting-edge AI-driven platform for enhanced crop management, focusing on disease detection and crop recommendation. By analyzing images of plants, CropGuard's model accurately identifies a wide range of diseases, from bacterial blight and rust to leaf mold and viral infections. It offers detailed information on each disease, including causes, prevention methods, and treatments, helping users effectively manage and mitigate crop issues. The platform also features an advanced crop recommendation system. Users input data like temperature, humidity, soil pH, water availability, and season, and the system suggests the most suitable crops for their conditions. This helps optimize yield and resource use by providing tailored crop suggestions based on environmental data. Additionally, CropGuard includes a conversational AI assistant that answers crop-related questions, offers advice on maintaining healthy crops, and provides guidance on agricultural practices. Designed to be user-friendly, CropGuard integrates seamlessly into farming workflows, offering actionable insights that drive better crop management decisions. Overall, CropGuard aims to improve agricultural productivity and sustainability with its innovative AI technology and practical features. Whether addressing crop diseases or selecting the best crops for your farm, CropGuard provides intelligent solutions for informed farming.

It is an innovative web application tailored for students, aspiring programmers, and anyone eager to improve their understanding of Data Structures and Algorithms (DSA). This project aims to create an engaging and comprehensive learning experience by providing a plethora of resources at users' fingertips.Users can explore various DSA concepts, view illustrative images, and practice coding problems to enhance their understanding and problem-solving skills.With DSA Companion, users will not only learn the theoretical aspects of DSA but also gain practical skills that will be invaluable in coding interviews and real-world programming scenarios. Whether you're a beginner or looking to refine your skills, DSA Companion is your go-to resource for mastering Data Structures and Algorithms.

MediConnect aims to redefine how medical records are managed, accessed, and analyzed by leveraging the power of blockchain, IPFS (InterPlanetary File System), and AI. Our innovative platform addresses critical challenges in healthcare data management, such as security, transparency, accessibility, and actionable insights, while empowering patients and healthcare providers alike. In the current healthcare ecosystem, medical records are often fragmented, prone to breaches, and difficult to access in real-time. MediConnect resolves these issues through the following: Decentralized Record Management: By utilizing IPFS, we store medical records in a decentralized, tamper-proof, and highly secure environment. This ensures sensitive data is always accessible to authorized users without relying on a central database that could be a single point of failure. Smart Contract-Based Security: Blockchain technology underpins our system with smart contracts enforcing strict data access controls. Every access attempt is logged immutably, providing full transparency to patients and stakeholders about who accessed the data and why. AI-Driven Insights: Our platform integrates with OpenAI to analyze patient data and provide meaningful, real-time summaries. When a new report is uploaded, our AI highlights key changes and updates the patient’s existing health summary. This enables healthcare providers to make faster, more informed decisions. Patient Empowerment: Patients retain full ownership of their data. They can grant or revoke access to healthcare providers, insurers, or researchers, ensuring their privacy and autonomy are respected.

AstroMind: Your AI-Powered Space Mission Assistant 🚀 AstroMind is an educational AI assistant designed to make space exploration fun and interactive. It consists of multiple AI agents that work together to fetch real-time space facts from NASA, ESA, and SpaceX, generate sci-fi stories using real space data, simulate space missions with detailed blueprints, and suggest relevant space visuals. By integrating these capabilities, AstroMind provides an engaging learning experience for students, educators, and space enthusiasts. Whether you're exploring Mars rover data, crafting a sci-fi adventure, or planning a mission to Jupiter, AstroMind brings the wonders of space closer to everyone through AI-powered storytelling and simulations.

Access to timely medical assistance is a significant challenge, especially in urgent situations where immediate guidance is crucial. Delays in finding trustworthy medical advice can lead to anxiety, poor decision-making, and potential health risks. Our solution is an AI-powered medical assistant designed to provide instant and reliable healthcare guidance. This intelligent system uses AI-driven symptom analysis to assess the severity of a condition and suggest appropriate actions. For minor issues, it provides first-aid recommendations, while for more serious cases, it enables real-time consultations with certified healthcare professionals. Additionally, the assistant integrates geolocation services, helping users find nearby hospitals, pharmacies, and emergency facilities. With multi-language support and personalized health record integration, it ensures accessible and accurate medical assistance for diverse users. By combining technology with healthcare, our solution aims to bridge gaps in medical accessibility, offering fast and effective guidance when it matters most.

The MVP Product Document for XAI in Supply Chain Optimization with IBM Granite presents a lightweight yet impactful prototype designed to enhance transparency and decision-making in supply chain management. This demonstrates how explainable AI (XAI) can improve forecasting, inventory management, and risk assessment in the textile and retail industry. The solution focuses on four core features: demand forecasting, which predicts future sales while providing clear justifications (e.g., seasonal trends, historical sales patterns); inventory optimization, which recommends ideal stock levels based on lead times, demand fluctuations, and supplier reliability; a risk alert system, which proactively flags supply chain disruptions with real-time root-cause analysis; and a scenario simulator, allowing users to tweak key variables (e.g., demand increase, supplier delays) to assess potential impacts dynamically. The technical stack includes IBM Granite for AI explainability, Python and Pandas for backend data processing, Streamlit for a simple and interactive front-end, and Plotly/Matplotlib for advanced data visualizations. Users can upload CSV/Excel datasets (or use sample data) to generate real-time insights into sales trends, stock levels, supplier risks, and demand forecasts. Designed with a minimalist, data-driven UI supporting dark/light modes, this prototype is tailored for quick decision-making in supply chain networks. Future development plans include integration with ERP systems (SAP, Oracle), multi-user authentication, and expanded AI-driven logistics optimization, ensuring scalability and deeper industry impact.