Looking back and moving forward: how anomaly detection and similar events reduce unwanted outcomes

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Data is the modern-day oil, with huge value often lying dormant or unseen. The safety industry is no exception. EHS professionals are presented with increasing amounts of data and a growing number of sources – from social media to ever expanding IOT and system integrations.

The opportunity to find valuable insights can easily be missed due to the amount and frequency of changing data. One way to automatically gain data insights faster and more efficiently is to introduce anomaly detection methods and similar event tools. These provide a powerful channel to automatically detect changes or shifts in safety data or similar patterns of events that previously would go unseen.

Join Rob Leech for an engaging and interesting session on a subject relevant for all EHS professionals. Be part of the start of this conversation, exploring the possibilities for using anomaly detection and similar event patterns to increase insights that are currently ‘unobserved’.

Definition: Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert.


Rob Leech
Product development director
Airsweb, now part of the EcoOnline Group
View Biography
Kellie Mundell
Digital editor, IOSH magazine