Project Information
Implementation period: January 2022 – December 2024
Objective: To improve food safety and security by developing and implementing smart digital systems and technologies that monitor, predict, and manage risks across the food supply chain.
Goals:
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Develop intelligent sensor-based systems for food quality monitoring;
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Integrate advanced data analytics and machine learning to predict contamination risks;
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Increase traceability and transparency in food production and distribution;
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Promote collaboration between research institutions and food industry stakeholders.
Publications:
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M. Ionescu, L. Popa, A. Marinescu, “Smart Sensors for Food Quality Monitoring: A Review,” Journal of Food Science and Technology, 2023
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D. Petrescu, C. Radu, “Machine Learning Approaches for Predicting Food Contamination Events,” Food Safety Journal, 2024
Developments:
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Prototype of a smart sensor network for real-time food quality monitoring;
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Predictive models for contamination risks using machine learning algorithms;
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Software platform integrating sensor data with risk assessment tools;
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Workshops and training sessions for industry partners.
Events:
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National conference on Food Safety & Smart Technologies, 2023
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Collaboration meetings with local food producers and regulators
- Dr. Ioana Popescu – Project Coordinator
- Alexandru Marinescu – Senior Researcher
- Mihai Ionescu – Data Scientist
- Cristina Radu – Software Engineer
- Daniel Petrescu – Machine Learning Specialist