Agrimate is a multiplatform application that enables total, accurate, and smart farming through the integration of Machine Learning, AI, and IoT for productivity, profitability, and food security. It assists farmers in applying for funding, working with an Aggregator to share post-harvest profits.
Planting Recommendation base on land data and Diseases Detection for optimized crop management.
IoT devices automate watering based on NPK and soil moisture, while Market Price Prediction predicts commodity prices.
It covers pre to post-farming and utilizes AI, such as CNN, Naive Baiyes, and Linear Regression.
As part of product design team, conducted extensive literature review, competitive analysis, field research, and engaging with farmers honed our understanding of user needs and pain points directly.
Furthermore, we tested the application using Time-based Efficiency and Effectiveness and the System Usability Scale (SUS) with two iterations to fine-tune and enhance its performance and user experience. Learn about aligning features and interfaces with available technology, including ML and IoT, ensured feasibility for implementation through discuss with tech team.
Example Process :
The results of the test found that farmers in the garut district with more than 120 farmers felt very helpful with a 10% comparison with the previous harvest. By overcoming various problems that exist in farmers, government, and aggregators who are not only end to end users but to the business that develops in it.
