ABSTRACT
The definition of IoT proposed by Kevin Ashton has remained as it is since 1999. IoT is formally defined by the International Telecommunication Union (ITU) thus: “A global infrastructure for the information technology society by interconnecting things (physical as well as virtual) by allowing interoperable services, and communication technologies” [1]. This definition is believed to be the basic definition of IoT networks. In [2], it is predicted that there will be a huge increase in interconnected devices from 18 billion to 29 billion during the period 2017 to 2022 and that machine-to-machine (M2M) connectivity will reach 15 billion in 2022. Now, our eyewitness agrees with the increase in IoT devices. It is also expected that about 8 billion to 25 billion active smart gadgets will be interconnected by 2030 and controlled by a single huge information network [3]. As we are on the edge of the 5G era, IoT follows the natural course of improvement that leads to IoT 2.0; that is, high-speed and ultra-latency networks motivate further development of IoT technologies and applications [4]. In [5], several features like interoperability, connectivity, security, and automation are discussed as the major fields of IoT applications. All these features are required to be improved in the context of IoT 2.0. However, the recent development of other technologies and applications such as machine learning (ML), edge computing, fog computing, and Industry 4.0 demands updating and redefining the concept of IoT to IoT 2.0 [4, 6]. The articles published in the public domain focus on the users’ point of view by improving the productivity and service quality of IoT applications [7–9]. In the view of AI-based service development, the quality of service can be enhanced through IoT [10]. IoT interoperability is a crucial issue that has to be enhanced in IoT 2.0 [11]. Apart from this, security and privacy factors are major concerns that have to be resolved in IoT echo systems [12]. In summary, current IoT technology comprises seven domains such as intelligence of machine learning, 5G communication, scalability, security, sustainability, interoperability, and user-friendly IoT [13]. Further, ML-based algorithms are applied in all layers of IoT applications. As per the Joint Research Centre(JRC) report of the European Commission[14], IoT 2.0 should make use of ML techniques to enhance the intelligence of the network and knowledge available to users. The motive of IoT 2.0 is that contents, code, and data delivery should be attained at a higher speed with intensely lower costs. The big picture of IoT 2.0 is the evolutionary progress from custom-built systems to tremendously scalable and broadly applicable product ecosystems. Blockchain could be the probable resolution to ensure IoT security and privacy. The various domains involved in IoT 2.0 are depicted in Figure 1.1.
