Anomaly Detection for Food Supply Chains
This project focussed on a mix of public and commercially held food safety data to build machine learning models that could detect food safety anomalies and link them to products made by different food producers. This research was developed into a commercial product as a module that formed a part of our partners food safety management tool. This module is called AI Scan.
Algorithms to detect anomalous food safety incidents were successful and a product was launched based in part from our research.
|Effective start/end date||3/06/19 → 30/11/20|
- University of Portsmouth
- Primority Ltd (lead)