Une bibliothèque Python conçue pour les agronomes, chercheurs et développeurs travaillant sur les données agricoles au Bénin et en Afrique de l'Ouest.
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Updated
Oct 6, 2026 - Python
Une bibliothèque Python conçue pour les agronomes, chercheurs et développeurs travaillant sur les données agricoles au Bénin et en Afrique de l'Ouest.
AgriTech Application - eAgriWallet [An Android app that can help farmers get access to farm inputs, connect with available Agrovets through a Google Map Location and grow their money wallet for them to receive payment for their produce and too use the wallet to pay for their farm inputs]
AI-powered farming assistant combining IoT sensors, machine learning, and real-time data to give every smallholder farmer precision agriculture in their pocket.
🤖 Terrafarms ML Models
A real-time data application delivering location-specific weather forecasts, crop health insights, and actionable agricultural advisories to help farmers optimize yield and mitigate climate risk.
CropWise UK is an AI-driven platform that recommends the most suitable crops for UK cities using soil, climate, and pollution data. It combines machine learning, rule-based reasoning, and geospatial analytics to provide accurate, actionable, and sustainable planting insights for farmers, researchers, and policymakers.
Stronger harvests start with the right inputs. Browse seeds, protection, tools, and services—then complete your purchase securely on Selar.
A web app which classify the soil using its textural composition (Sand, Silt and Clay). It returns the type of soil and also plot the ternary graph for that soil. This app helps determining the soil type easily and without manual calculations.
This project is detailed website of Agricultural Dairy Farm company, the company seeks to automate the milk production records to make it easier for monitoring the production at the farm.
AI-powered web app for detecting tomato/potato leaf diseases with bilingual English/Tamil remedy suggestions
AgriLink is a digital agriculture platform connecting farmers, aratdars, and retailers. It enables crop listing, live bidding, product trading, inventory management, weather-based crop suggestions, order management, and real-time communication to make Bangladesh’s agricultural supply chain more efficient and transparent.
AI-powered farming assistant — instant crop disease detection, soil-based crop & fertilizer advice, real-location weather, and a multilingual chatbot. Built with Flask, TensorFlow/PyTorch & Groq.
A web app based on classification algorithm (KNN) which recommends the best suitable crop using the soil nutritional data and weather data. The model has 99.96% accuracy and it is very beneficial for farmers to make more informed decision about which crop to grow.
AgriPlus is an online website that help farmers, harvesters, producers and consumers to connect directly.
This project is an IoT-based intelligent plant monitoring and control system designed to automate the care of plants using sensor data and adaptive logic. It also enables users to have manual control over the plant ecosystem for better management.
AI-powered precision agriculture platform for site-specific weed management. Uses ResNet-50 CNN (94.7% accuracy, 23ms inference) to detect weed species from field images and generate zone-wise herbicide treatment plans — reducing chemical usage by up to 67%.
A smart agriculture information system that provides real-time weather updates and farming-related information to help users make informed agricultural decisions.
Dual-axis solar tracking drying system using 4 LDR sensors with threshold-based control for agricultural drying
The Farmers Service Centre (FSC) is a one-stop shop designed to enhance the agricultural productivity and income of smallholder farmers in rural areas. It offers a wide range of services, including input sales, equipment leasing, commodities aggregation, storage facilities, and advisory services.
AI-powered precision agriculture platform for site-specific weed management. Uses ResNet-50 CNN (94.7% accuracy, 23ms inference) to detect weed species from field images and generate zone-wise herbicide treatment plans — reducing chemical usage by up to 67%.
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