Agent‐oriented activity recognition in the event calculus : An application for diabetic patients. / Kafali, Remzi; Romero Lopez, Alfonso; Stathis, Konstantinos.

In: Computational Intelligence, Vol. 33, No. 4, 11.2017, p. 899–925.

Research output: Contribution to journalArticle

Published

Documents

Abstract

We present a knowledge representation framework on the basis of the Event Calculus that allows an agent to recognize complex activities from low-level observations received by multiple sensors, reason about the life cycle of such activities, and take action to support their successful completion. Activities are multivalue fluents that change according to events that occur in the environment. The parameters of an activity consist of a unique label, a set of participants involved in the performing of the activity, and a unique goal associated with the activity revealing the activity's desired outcome. Our contribution is the identification of an activity life cycle describing how activities can be started, interrupted, suspended, resumed, or completed over time, as well as how these can be represented. The framework also specifies activity goals, their associated life cycle, and their relation with the activity life cycle. We provide the complete implementation of the framework, which includes an activity generator that automatically creates synthetic sensor data in the form of event streams that represent the everyday lifestyle of a type 1 diabetic patient. Moreover, we test the framework by generating very large activity streams that we use to evaluate the performance of the recognition capability and study its relative merits.
Original languageEnglish
Pages (from-to)899–925
Number of pages27
JournalComputational Intelligence
Volume33
Issue number4
Early online date9 Aug 2017
DOIs
StatePublished - Nov 2017
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 27703000