Artificial intelligence

AI-Powered Pest Detection System for Watermelon Crops

AI-powered computer vision system for early pest detection

Client: Coopel LTDA
Duration: 1 year
Status: In Development

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Technology Stack

Python
TensorFlow
AI Model Training
TypeScript
React

Detailed Description

Developed an AI-powered computer vision system for early pest detection in watermelon crops. Using trained models (Python, TensorFlow) and real-time camera feeds, the system identifies anomalies to boost rural farming efficiency. Built a Node.js backend, cloud processing pipeline, and monitoring dashboard. This project supports digital transformation in Colombian agriculture through a local cooperative initiative.

The Challenge

Create an automated pest detection system that improves agricultural efficiency and supports digital transformation in Colombian rural cooperatives.

Our Solution

We developed an AI-powered computer vision system using TensorFlow-trained models, real-time processing, and a monitoring dashboard for early pest detection.

Results Achieved

System in development that promises to significantly improve agricultural efficiency and contribute to the digital transformation of the Colombian agricultural sector.

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