Data Models and Contextual Information
Identificadores
URI: https://hdl.handle.net/10481/97293Metadatos
Mostrar el registro completo del ítemEditorial
Springer
Fecha
2024Referencia bibliográfica
De, S., Wang, W., Bermudez-Edo, M. (2024). Data Models and Contextual Information. In: Ziegler, S., Radócz, R., Quesada Rodriguez, A., Matheu Garcia, S.N. (eds) Springer Handbook of Internet of Things. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-031-39650-2_16
Resumen
The Internet of Things (IoT) and its applications emphasize the need for being context-aware to be able to sense the changing environmental conditions and to make use of the rich contextual information for analysis. The huge volume and high-velocity characteristics of IoT data necessitates that representation of IoT data takes into consideration the contextual information at scale during every step of the data processing life cycle, from production to storage, publication, and search. This chapter categorizes and describes the diverse forms of IoT data that are obtained from heterogeneous sensing sources. It also presents a framework for describing and analyzing the different types of contextual information that need to be associated with the IoT data in order to drive context-aware management and intelligent analytics. In addition, mechanisms for storing big IoT data and its contextual information are described, and common search and discovery methods for making IoT data accessible to applications and analysis components are presented.