Interactive Process Mining in IoT and Human Behaviour Modelling

Autor: J.L. Bayo, Juan José Lull, Mona Ghassemian, Carlos Fernandez-Llatas, Mohsen Shirali
Rok vydání: 2020
Předmět:
Zdroj: Interactive Process Mining in Healthcare ISBN: 9783030539924
Popis: In previous chapters, we saw how Interactive Process Mining (IPM) is key in discovering models from reality, while having a way of validating those models by the expert. In this chapter, we will show how vast amounts of real-time data, obtained through Internet of Things (IoT), may be used in order to create accurate models of human behaviour. This enables the classification of behaviour with different patterns by their heuristic distance. Data from a subject’s location at home across 70 days is used in order to show different types of conduct. The specific classification in groups is shown through workflows to the user, who will be able to validate the behavioural models. A calendar view of the groups, along with maps with the difference between behaviours are also shown. The power to show fine grain information about the subject’s conduct with data from IoT is shown.
Databáze: OpenAIRE