🔍 Generate realistic synthetic datasets for diverse business sectors using the leblanc Python library, perfect for training and analysis.

The SCARECRO (Sensor Collection and Remote Environment Care Reasoning Operation) documentation and source code files for integrating a variety of off-the-shelf IoT sensors into a broader collection, storage, and visualization framework.

[IROS25] Offical Code for "FruitNeRF++: A Generalized Multi-Fruit Counting Method Utilizing Contrastive Learning and Neural Radiance Fields" - Inegrated into Nerfstudio

Herramienta de ML offline para cultivos regados en Guatrache. Sin internet, sin datos externos, con respeto a la autonomía menonita.

BaleUAVision: High-resolution UAV dataset for automated hay bale detection and counting. Includes 2,599 annotated images, flight metadata, orthomosaics, segmentation formats (COCO, YOLO, CSV, masks) and YOLOv11 benchmark.

Software de processamento de laudos de análise de solo voltado para a cultura da soja a partir do manual de adubação e calagem para os estados do RS e SC de 2016

Automated Python pipeline for geostatistical analysis and soybean yield mapping using kriging and machine learning for precision agriculture.

This project is a complete web application built to help farmers efficiently manage their dairy and poultry farms. It provides tools and insights that enable data-driven decision-making to improve operations and business outcomes.

Detection models and Python scripts for insect detection on yellow sticky traps.

Multi-spectral satellite data analysis system combining Sentinel-2 imagery with deep learning for early crop disease detection in precision agriculture applications.

Computer Vision pipeline designed for precision agriculture applications, featuring automated dataset processing, advanced data augmentation, hyperparameter optimization, and edge-optimized model deployment for real-time crop and weed detection.

A backend server built using FastAPI

Research-project: IoT-integrated precision irrigation combining automated sensors, intercropping, and gravity-drip systems. Validated 36.9% water savings through laboratory experimentation and mathematical modeling.

DroneUI is a Python-based system that allows farmers to manually control a DJI Tello EDU drone, capture video of tomato crops, and automatically detect signs of leaf disease using a custom-trained YOLOv11 model. It features a user-friendly interface built with PyQt6 and generates detailed flight reports with visual and statistical summaries.

AI-powered smart agricultural IoT monitoring system using Raspberry Pi sensors and Llama 3.2 LLM for offline crop management. Provides real-time environmental data analysis and natural language farming insights without internet dependency.

[IROS24] Offical Code for "FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework" - Inegrated into Nerfstudio

Python library for AI-driven agricultural zoning with ISO 42001 compliance.

Official Repository for CWD30 Dataset

A scalable, open-source environmental control system using Arduino and Python for precision automated indoor farming.

Modular AWS pipeline for ingesting .xlsx reports to the Glue Data Catalog—ideal for agriculture, ops, or field data workflows.