Regresar

Data fusion and homogenization: Two key aspects for building digital twins of smart spaces

Abstract:

Digital twins are virtual replicas of physical objects, systems, or processes. With the advancement of artificial intelligence and internet of things, digital twins have become an increasingly valuable tool in the context of smart spaces to improve efficiency, reduce costs, and enhance user experience. However, one of the main challenges for the successful implementation of digital twins is combining data from multiple sources in a homogeneous format so they can be operationalized together to generate more accurate, comprehensive, and valuable information. This chapter thoroughly describes the implementation of a digital twin of a smart space using different technologies from the FIWARE ecosystem that help combat data fusion and homogenization problems. This process involves several steps, including data selection, preprocessing, integration, and interpretation. In addition, a case study on low-emission zones is presented, which can be easily replicated in different scenarios within a smart city. Lastly, we discuss the advantages of using FIWARE as the underlying technology in our implementation to overcome the data fusion and homogenization challenge.