Title: Fusion of information and analytics: a discussion on potential methods to cope with uncertainty in complex environments (big data and IoT)
Authors: Éloi Bossé; Basel Solaiman
Addresses: Expertises Parafuse Inc., 1006 Blvd Pie XII, Québec, QC, G1W 4N1, Canada; Electrical and Computer Engineering, McMaster University, 1280 Main St W, Hamilton, ON L8S 4L8, Canada ' Image and Information Processing Department (iTi), IMT-Atlantique, Technopôle Brest Iroise CS 83818, 29238 Brest Cedex France
Abstract: Information overload and complexity are core problems to most organisations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organisations. Fusion of information and analytics technologies (FIAT) are key enablers for the design of current and future decision support systems to support prognosis, diagnosis, and prescriptive tasks in such complex environments. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of integrating frameworks for these techniques coming from multiple disciplines. This paper presents a discussion of potential integrating frameworks as well as the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex environments such as in big data and internet of things (IoT).
Keywords: information fusion; analytics; decision support; situation analysis; complex systems; big data; internet of things; IoT.
International Journal of Digital Signals and Smart Systems, 2018 Vol.2 No.4, pp.279 - 316
Received: 09 May 2018
Accepted: 06 Dec 2018
Published online: 06 Aug 2019 *