iComplai speaks at the IAFP European Symposium
On this year’s IAFP International Symposia, iComplai CEO Asli Solmaz-Kaiser will be speaking about "Early Warning System and Prediction of Food Safety Risks".
A member-based association of more than 4,500 food safety professionals, IAFP is committed to advancing food safety worldwide by providing a forum for food safety professionals to exchange information on protecting the food supply.
This year’s symposium will be held in Munich between 4-6 May. iComplai’s speech will be held on May 4th at 11:30. The abstract as follows:
Abstract
Introduction: Increasing liberalization of the global economy has led to an increase in food imports, underscoring the importance of effective food risk management. Early warning and prediction of food hazards are critical to food safety for preventing (high-cost) product recalls and protecting consumer health.
Purpose: This study aimed at providing a fully-automated cloud platform for the development and use of data-driven AI-infused services, such as anomaly detection and food recall prediction, for creating a traceable, preventive and safer food risk management, from farm to fork.
Methods: The proposed solution leverages the use of structured and unstructured big data on food safety (i.e., over 240 million test results from 60+ online sources). Using the latest Artificial Intelligence (AI) and Machine Learning (ML) technologies, such as Natural Language Processing (NLP), data is first checked for quality and integrity, pre-processed and classified using taxonomy mapping. The prepared data is then used together with the previous 13+ billion possible historical data to train and test an AI engine coupled with an early warning system to detect anomalies, assess and foresee risks and corresponding impact. Various ML models (regression/classification) has been evaluated and the most appropriate in terms of accuracy and interpretability was selected. The AI engine trains itself continuously and improves the accuracy of the forecast quality over time.
Results: The use of AI-infused capabilities demonstrated measurable quantitative and qualitative results: 1) The time and consequently cost saving of a risk analyst approximates around €30k per year and person. 2) Prevention and saving of potential food recall of around €10 million.
Significance: The presented study enables food producers to switch from a reactive to proactive anticipation of potential food safety risks and effectively evaluate their possible effects, thereby reducing and reducing the risk of recalls and consumer health issues.
See complete abstract here:
https://iafp.confex.com/iafp/euro22/onlineprogram.cgi/Paper/28352