From farm to fork, Agrifarm's got the score - connecting the agri-supply chain like never before! 👩🏻‍🌾👨🏻‍🌾

Team - AgriFarm 🍅

Hi there, we are the team behind Agrifarm - Tuhina Tripathi, Anouska Jhunjhunwala, and Ujan Pradhan. We are passionate about technology and agriculture, and have combined our skills to create a web application that optimizes the agricultural supply chain like never before. Our platform, built with Tailwind CSS, React JS, Vite, HTML, CSS, and Javascript, is powered by machine learning algorithms that predict the demand for various agricultural products and provide valuable insights to farmers to plan their production accordingly. We are proud to be transforming the industry by connecting farmers, middlemen, cold storage facilities, and customers, and making agriculture more efficient and sustainable.

Problem Statement❔:

The agricultural supply chain faces numerous challenges, such as the lack of effective communication and coordination between farmers, middlemen, cold storage facilities, and customers. This often leads to inefficiencies in the supply chain, including oversupply or undersupply of products, loss of quality and value, and increased transportation costs.

Our Solution ✔️:

Our proposed solution, AgriFarm, is a web application that aims to optimize the agricultural supply chain by connecting farmers, middlemen, cold storage facilities, and customers. The platform will leverage machine learning algorithms to predict the demand for various agricultural products and provide valuable insights to farmers to plan their production accordingly.

Technical Complexity: 👩🏽‍💻

Our project involves the use of several programming languages and tools to build a fully functional web application that optimizes the agricultural supply chain.

Programming languages and tools used:

1. Machine learning algorithms using Python: Our project will leverage machine learning algorithms to predict the demand for various agricultural products and provide valuable insights to farmers to plan their production accordingly. We will be using Python libraries such as scikit-learn, pandas, and numpy for this purpose.

2. Web app with HTML and Tailwind CSS: We will be using HTML and Tailwind CSS to create an intuitive and user-friendly web app for farmers, middlemen, cold storage facilities, and customers.

3. Flask API: We will be using Flask, a Python-based web framework, to develop a RESTful API that will facilitate communication and coordination between various stakeholders in the agricultural supply chain.

Web App 💻:

React.App.-.Google.Chrome.2023-04-21.13-48-14.mp4

Price Predictor 💵:

AgriFarm.Price.Predictor.-.Google.Chrome.2023-04-21.13-47-28.mp4

Conclusion 📃:

AgriFarm aims to revolutionize the agricultural industry by optimizing the supply chain and improving communication and coordination between farmers, middlemen, cold storage facilities, and customers. With the power of machine learning, AgriFarm can provide valuable insights to farmers, reduce waste, and improve the quality of the products.

1. Improved efficiency: AgriFarm aims to streamline the agricultural supply chain by improving communication and coordination between farmers, middlemen, cold storage facilities, and customers.

2. Increased profitability: By optimizing the supply chain, AgriFarm aims to reduce waste, minimize transportation costs, and improve the quality of the products, ultimately leading to increased profitability for farmers and middlemen.

3. Improved food security: AgriFarm can ensure a steady supply of high-quality products to customers, even during times of uncertainty, thereby contributing to improved food security.