Techniques for Combining Data From Multiple Sensors

Abstract

Quality data delivery and communication in an ultra-latent and real-time manner are some its stringent requirements for Internet of Things (IoT). In IoT, raw data is sensed from real-world and transformed into a usable form. Collection of this raw data from multiple sensors as compared to a single one, it is found to be of better quality and high accuracy. This method of collecting same type of data is called data or sensor fusion. In this paper a meticulous study on the role of data fusion have been done with respect to its application with Internet of Things, Machine Learning (ML) and Mobile Edge Computing (MEC).This paper discusses the mechanism, multi-modal fusion techniques, past proposed standard data fusion models and related issues, along with its application with support of machine learning and Edge Computing Lastly, the paper discusses about the concept of Edge Intelligence to deliver reliable outputs with future directions and issues.