FRESH@NTU Builds on AWS Cloud to Advance Predictive Food Safety Innovation

NTU to Leverage AWS Cloud to Develop Scalable Digital Infrastructure for Food Safety Research 

The Future Ready Food Safety Hub (FRESH), a national initiative led by Nanyang Technological University, Singapore (NTU Singapore), in collaboration with the Singapore Food Agency (SFA) and the Agency for Science, Technology and Research (A*STAR), has received funding from Amazon Web Services (AWS) Cloud to Table (CTT) initiative supporting organizations working at the intersection of the global food system and cloud technology; in service of addressing food insecurity worldwide. With the CTT award, FRESH will develop cloud-based digital infrastructure for food safety. This includes applying artificial intelligence (AI), machine learning (ML), and data analytics to study emerging risks in novel and functional foods such as cultivated meat, precision-fermented ingredients, and plant-based alternatives. The funding supports FRESH’s ongoing efforts to apply science and technology in support of resilient and trusted food systems. 

Building Digital Tools to Support Food Safety Innovation 

FRESH researchers plan to use AWS’s scalable cloud infrastructure to prototype AI and ML-enabled tools that integrate laboratory results, omics datasets, and sensor inputs. These efforts aim to enhance decision-making in food safety evaluation by enabling more rapid and data-rich assessments. 

Planned projects include: 

• Cold Chain Monitoring Prototypes 

  Using IoT and cloud-based analytics, FRESH will explore model systems that detect temperature and humidity anomalies during food transport and storage. These capabilities can support improved cold chain management and contribute to reduced spoilage risk. This echoes successful industry pilots where grocery retailers deploying similar systems have achieved up to 30% reduction in spoilage over six months by intercepting temperature excursions before they impact product integrity[2]. 

• Digital Pre-Screening of Ingredients 

FRESH will evaluate the use of ML models trained on biological and toxicological datasets to support preliminary assessments of novel ingredients. This builds on international best practices and may contribute to more efficient safety evaluations without relying on traditional animal testing methods. 

Exploring the Potential for Pre-Emptive Surveillance 

FRESH’s research aims to complement existing regulatory and food safety frameworks by exploring predictive and data-informed approaches. By analyzing signals from production and supply chains, researchers will study how digital tools could be used to flag potential risks earlier in the process. These models, if validated, may help support long-term innovation in food safety and risk communication. 

Global Relevance and Singapore’s Contributions 

While initial work will be focused on Singapore, the digital approaches being explored could have broader applicability. Many food safety challenges such as assessing new food types or improving supply chain visibility are shared across regions. Through participation in global regulatory science collaborations and the WHO-NTU Joint Action Plan, FRESH will share learnings, tools, and methodologies with international partners. 

“Receiving the AWS Cloud to Table Award enables us to accelerate our work on data-informed food safety innovation,” said a FRESH spokesperson. “By building on AWS, we aim to create scalable research tools that can support public health, enable scientific evaluation of novel foods, and contribute to global knowledge exchange.” 

References 

[1] https://pacificcoastcollaborative.org/wp-content/uploads/2022/12/PCFWC-Case-Study_AI_Final.pdf 
[2] https://advancedlogistics.us/smart-refrigeration-how-iot-is-revolutionizing-cold-chain-logistics-for-fresh-food-supply-chains/ 
[3] https://www.efsa.europa.eu/en/efsajournal/pub/e170710