01766nas a2200241   4500000000100000000000100001008004100002260001200043653002900055653002300084653002300107653001500130100002800145700002300173700002100196700002000217245005400237856008100291300001000372490000600382520112200388022001401510       2023                            d  c09/202310aComplex Event Processing10aIntelligent Agents10aInternet of things10aOntologies1 aIván Bernabé-Sánchez1 aAlberto Fernández1 aHolger Billhardt1 aSascha Ossowski00aProblem Detection in the Edge of IoT Applications  uhttps://www.ijimai.org/journal/sites/default/files/2023-08/ijimai8_3_8_0.pdf  a85-970 v83 aDue to technological advances, Internet of Things (IoT) systems are becoming increasingly complex. They are characterized by being multi-device and geographically distributed, which increases the possibility of errors of different types. In such systems, errors can occur anywhere at any time and fault tolerance becomes an essential characteristic to make them robust and reliable. This paper presents a framework to manage and detect errors and malfunctions of the devices that compose an IoT system. The proposed solution approach takes into account both, simple devices such as sensors or actuators, as well as computationally intensive devices which are distributed geographically. It uses knowledge graphs to model the devices, the system’s topology, the software deployed on each device and the relationships between the different elements. The proposed framework retrieves information from log messages and processes this information automatically to detect anomalous situations or malfunctions that may affect the IoT system. This work also presents the ECO ontology to organize the IoT system information.  a1989-1660