Anomaly Detection in a Boxed Beef Supply Chain

Abstract

An approach to simulating and analysing sensor events in a boxed beef supply chain is presented. The simulation component reflects our industrial partner’s transport routes and parameters under normal and abnormal conditions. The simulated transport events are fed into our situational awareness system for detecting temperature anomalies or potential box tampering. The situational awareness system features a logic-based modeling language and an inference engine that tolerates incomplete or erroneous observations. The paper describes the approach and experimental results in more detail.