My Projects

Projects from my work, studies, and personal interests.

2025

Current work at FOQUS Vision

AI Vision Platform

FOQUS

FOQUS combines self-learning AI and computer vision for quality control in food and manufacturing industries. The platform connects QUBE for quality inspection and AI model training with OptIQ for inline inspection. As an AI Software Engineer, I work on AI software and integrations. The FOQUS website presents the solutions, team, and applications for manufacturers.

2025
Growbot
Graduation Project

Growbot

The GrowBot is an autonomous greenhouse robot designed to optimize crop growth through real-time data collection and AI analysis. It navigates independently between plant rows, measuring environmental factors like temperature, humidity, and soil moisture. Using computer vision and machine learning, it assesses plant health, detects issues early, and tracks growth. Based on this data, it suggests or triggers adjustments to improve growing conditions. GrowBot supports sustainable agriculture by enabling precise, data-driven cultivation and reducing manual intervention.

2025
Web Project

Curriculum Vitae Website

My personal CV website, built with Next.js, React, and Mantine. I use it to share my work experience and projects. It supports English and Dutch, light and dark themes, and a downloadable CV.

2024
Minor A Systems

Advancements in Greenhouse Automation

This machine vision system was developed as part of research into automated harvesting of bell peppers. It uses computer vision techniques and deep learning models to detect and localize ripe peppers in real-time from RGB images. The system was trained to identify different ripeness stages. Built using frameworks like YOLO, OpenCV, the project demonstrates practical application of AI in agriculture, contributing to more efficient and selective harvesting processes in controlled environments such as greenhouses.

2023
Traineeship

AI Detection

During my internship at Mechatronic Machinery, I developed an AI-powered platform for object detection and localization, earning a final grade of 9.0. The system enables robots to identify and accurately locate objects for automated picking tasks, opening new possibilities in smart industrial automation. The platform allows users to easily train and deploy AI networks, making advanced machine vision more accessible.