AI-Based Food Quality Monitoring System
This research project focuses on developing an intelligent monitoring system using artificial intelligence to evaluate food quality in real-time across production and processing environments. The
Research Projects
Ongoing and completed research initiatives focused on advancing food safety, toxicology, and environmental health.
The research projects at Rahlil Center focus on addressing real-world challenges in food systems, environmental sustainability, and toxicological safety.
Each project integrates scientific methodologies, modern technologies, and collaborative approaches to deliver impactful and practical solutions that contribute to global health and food security.
Computer Vision for Automated Food Contamination Detection
This project aims to develop an automated contamination detection system using advanced computer vision technologies in food production environments. High-resolution imaging and deep learning models
Data-Driven Toxicological Risk Assessment in Food Systems
This research project focuses on developing data-driven approaches for toxicological risk assessment in food systems, combining environmental data, chemical analysis, and predictive modeling techniques. The
AI-Based Food Quality Monitoring System
This research project focuses on developing an intelligent monitoring system using artificial intelligence to evaluate food quality in real-time across production and processing environments. The
Data-Driven Toxicological Risk Assessment in Food Systems
This research project focuses on developing data-driven approaches for toxicological risk assessment in food systems, combining environmental data, chemical analysis, and predictive modeling techniques. The
Computer Vision for Automated Food Contamination Detection
This project aims to develop an automated contamination detection system using advanced computer vision technologies in food production environments. High-resolution imaging and deep learning models
Collaborate on Research Projects
We welcome partnerships with academic institutions and organizations for future research initiatives and scientific collaboration.