|Bibliography||Hirmer, Pascal; Wieland, Matthias; Schwarz, Holger; Mitschang, Bernhard; Breitenbücher, Uwe; Sáez, Santiago Gómez; Leymann, Frank: Situation recognition and handling based on executing situation templates and situation-aware workflows. |
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-19, english.
Springer, October 11, 2016.
Article in Journal.
|CR-Schema||J.6 (Computer-Aided Engineering)|
H.3.1 (Content Analysis and Indexing)
|Keywords||Situation Recognition; IoT; Context; Integration; Cloud Computing; Workflows; Middleware|
Today, the Internet of Things has evolved due to an advanced interconnectivity of hardware devices equipped with sensors and actuators. Such connected environments are nowadays well-known as smart environments. Famous examples are smart homes, smart cities, and smart factories. Such environments should only be called ßmart" if they allow monitoring and self-organization. However, this is a great challenge: (1) sensors have to be bound and sensor data have to be efficiently provisioned to enable monitoring of these environments, (2) situations have to be detected based on sensor data, and (3) based on the recognized situations, a reaction has to be triggered to enable self-organization, e.g., through notification delivery or the execution of workflows. In this article, we introduce SitOPT---an approach for situation recognition based on raw sensor data and automated handling of occurring situations through notification delivery or execution of situation-aware workflows. This article is an extended version of the paper "SitRS - Situation Recognition based on Modeling and Executing Situation Templates" presented at the 9th Symposium and Summer School of Service-oriented Computing 2015.
|Full text and|
|Department(s)||University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems|
|Entry date||October 11, 2016|