Marilena Dimitrakopoulou in Spotlight for STELAR: Fighting Data Fragmentation
In this episode of the STELAR project’s Data Stories 360° podcast, host Julia Mitrovic, Deputy Head of Communications at Foodscale Hub, engages in a fruitful discussion with Marilena Dimitrakopoulou.
Marilena holds a PhD in Public Health from the University of Patras and has a wealth of expertise in molecular techniques, quality control, and assurance. Her research interests encompass food safety, food fraud, sustainability, and food traceability.
Currently, Marilena serves as a Research Project Manager at Agroknow within the Innovation Department, focusing on AI-driven food safety solutions. She is also an active contributor to STELAR within its Pilot 1, which is dedicated to risk prevention in food supply lines.
Exploring Our Guest's Motivation and Background
What attracted you to the field of food safety and its intersection with artificial intelligence?
What initially drew me to food safety was the critical importance of ensuring that the food we consume is both safe and sustainable. I started working in traceability and quality control, and I realised that ensuring food safety is not just a matter of regulation but a necessity for public health in general and for trusting the global food supply chain.
The introduction of artificial intelligence in this field excites me because it opens up a whole new world of proactive risk assessment and real-time monitoring. Additionally, AI’s ability to process and analyse vast amounts of data in real-time allows us to predict and prevent food safety issues and incidents before they become public health concerns. The fusion of technology and food safety is really exciting for me.
With your background in traceability and quality control, how do you see advancements in AI enhancing real-time food traceability? Could AI help create a more transparent and secure supply chain for both companies and consumers?
Absolutely. I think that artificial intelligence has a unique capability to transform real-time traceability and make it far more efficient and transparent. For example, AI-driven tools can track and verify the journey of a product from farm to fork with incredible accuracy. That is very important for food safety and public health.
Through AI, we can identify potential contamination points or even delays in the supply chain. This creates not only a more secure supply chain for companies but also empowers consumers to make more informed decisions about the products they want to consume. The level of transparency we want in food safety systems is achievable with AI and will foster a deeper level of trust in the food we consume.
Innovation, Regulation, and Data Fragmentation
Considering your expertise in risk assessment for public health, how do you approach balancing innovation in food safety technology with regulatory compliance and standards? There can be a lot of regulatory compliance and standards that one has to follow.
I think that innovation and regulatory compliance do not have to be at odds. In fact, they can complement each other. As we push the boundaries of food safety technologies, we also need to ensure that they align with existing regulations and standards.
One approach is to work closely with regulatory bodies during the innovation process and make sure that AI tools, for example, are developed in a way that meets stringent safety requirements. By using AI to improve traceability and transparency, we are not only enhancing food safety standards but also making it easier to demonstrate compliance with regulations, as every step of the process can be documented and verified.
What are the main challenges that arise from the current fragmentation of data across the food supply chain?
Data fragmentation is a significant challenge. Food supply chains are very complex, and data is often siloed across different stakeholders—farmers, manufacturers, distributors, and even retailers. Each of them has their own systems and ways of recording data, which often leads to inconsistencies and inefficiencies.
For AI to work effectively, especially in risk prediction and real-time monitoring, it needs access to accurate, timely, and comprehensive data. The challenge is breaking down these silos and creating an ecosystem where data flows seamlessly and securely between all parties involved in the food supply chain.
Ensuring Security, Privacy, and Transparency in Food Data
Your food risk intelligence platform at Agroknow, FOODAKAI, analyses data to detect potential hazards early, assuring companies can maintain good food safety standards. What steps are being taken to ensure the privacy and security of sensitive data while combining and analysing data?
Privacy and security are paramount when dealing with sensitive data, especially in the food industry. At Agroknow, we prioritise data security by implementing state-of-the-art encryption and anonymisation techniques. We are also strict about compliance with GDPR and other relevant data privacy laws, ensuring that any data shared through FOODAKAI is handled responsibly.
We also use advanced algorithms to detect potential hazards without compromising the privacy of the parties involved. Balancing data sharing with security is key to creating a safer and more transparent food ecosystem.
How important is the role of consumers in this ecosystem of data? They are increasingly interested in informing themselves about the food they eat. Also, is consumer data, such as product reviews, being leveraged to improve food safety?
Yes, consumers play a crucial role in the food data ecosystem. They are increasingly interested in knowing where their food comes from and the process it goes through. In fact, consumer feedback, including reviews and concerns, can provide valuable real-time insights into potential risks.
By integrating consumer data into platforms like FOODAKAI, we can analyse patterns of complaints or issues related to specific products and trace them back to potential safety hazards. This kind of consumer-driven data can help improve product quality and safety, making it a more powerful tool in the broader food safety ecosystem.
Marilena Dimitrakopoulou Discusses STELAR’s Impact on Food Risk Prevention
Within STELAR, Agroknow leads one of the three pilots - risk prevention in food supply lines. Could you share examples of how this pilot is enhancing the ability to predict and manage emerging risks in the food supply chain?
The STELAR KLMS provides us with natural language processing (NLP) tools to automate the extraction of useful information from text. This text could be public food safety or fraud incidents, for example, which come in different formats and languages.
Another example is that the STELAR KLMS provides us with named entity recognition (NER) tools to automate the extraction of useful information from long and complex regulatory texts, allowing us to collect just the important information in an automated way.
How do you envision the future of food risk prevention as data management technologies continue to evolve?
I think the future of risk prevention will be deeply integrated with artificial intelligence and big data. As data management technologies evolve, I believe we will see more seamless integration of data across the entire food chain—from farm to fork.
I think that artificial intelligence will become more sophisticated in predicting risks with higher accuracy. This will allow stakeholders to prevent issues long before they occur. As consumers continue to demand transparency, we will also see more consumer-facing technologies that allow them to track and verify the safety of their food in real time.
What do you see as the long-term impact of the STELAR project on agriculture and food safety?
I think the most important long-term impact of STELAR will be transformative. By automating the extraction of useful information from various sources across the globe, STELAR will help food companies and authorities better monitor the status of the global supply chain. This will also enable a better reaction when an issue or incident occurs.
Conclusion
Reflecting on the discussion, Marilena shared valuable insights that shed light on the innovative approaches STELAR is pursuing. Her expertise will undoubtedly play a significant role in shaping the project’s future impacts.
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