Abstract
Dramatic changes in the way we collect and process data has facilitated the emergence of a new era by providing customised services and products precisely based on the needs of clients according to processed big data. It is estimated that the number of connected devices to the internet will pass 35 billion by 2020. Further, there has also been a massive escalation in the amount of data collection tools as Internet of Things devices generate data which has big data characteristics known as five V (volume, velocity, variety, variability and value). This article reviews challenges, opportunities and research trends to address the issues related to the data era in three industries including smart cities, healthcare and transportation. All three of these industries could greatly benefit from machine learning and deep learning techniques on big data collected by the Internet of Things, which is named as the internet of everything to emphasise the role of connected devices for data collection. In the smart grid portion of this paper, the recently developed deep reinforcement learning techniques and their applications in Smart Cities are also presented and reviewed.
Highlights
To date, the economic, architectural, and fundamental changes in traditional internet have transformed the social environment and the business ecosystem
This paper demonstrates the diversity of applications of the Internet of Everything (IoE) as a cyber-physical network in which data are transferred and stored, and machine learning as techniques to manipulate data and construct meaningful knowledge in three separate domains
We demonstrate these applications in the fields of health, smart electrical grids, and green supply chain management (GSCM)
Summary
The economic, architectural, and fundamental changes in traditional internet have transformed the social environment and the business ecosystem. In health, acquiring knowledge and actionable perceptions from complex, multi-dimensional and heterogeneous data is a primary challenge in transforming health care. The IoE is a modern smart technology paradigm envisioned as a universal connection network of machines and smart devices capable of networking with each other, business processes, people and the social environment. IoE sensors and devices are generating massive amounts of high-dimensional and heterogeneous data that need to be stored and processed. This paper will explore the challenges and issues of IoE and machine learning techniques in three different and diverse business domains, such as health management, supply chain management and the smart grid to demonstrate the applicability and functionality of the technology and the methodology.
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