Although technology advances in a high speed and in different tracks and sectors, among the many major areas of trends of smart technologies are clouds and artificial intelligence. This chapter presents such significant trends in smart technologies with emphasis on clouds and their applications which make the implementation of smart cities efficient. It focuses on the general paradigm for smart technology platforms with five different levels, including edge and fog computing as well as the internet of things. In the chapter, other trends are covered such as data analytics for strategic decision making, artificial intelligence, machine learning, blockchain, open data, and cloud-based data. It also introduces the significance of using predictive analytics and using data for effective deep learning for smart applications.
TopImportant Challenges For Cloud Smart Technologies
Technology is developing in a way that is taking form that is based on integration of different technologies yet segregating them into levels. It is obvious that technology is being developed with a coordinated research world community that knows what everyone is doing. As the world is heading to the 4th industrial revolution, if not already there, where cyber physical systems characterize the future of information and commination technology. This concept dictates the pattern that the next generation technologies for smart cities heads in future directions. This is well formulated through the work of Shreshth Tuli (Tuli et al, 2003)1. Next generation technologies for smart healthcare: challenges, vision, model, trends and future directions.
An important concept that is associated with cloud computing, is what is known as edge computing. Gartner defines edge computing as “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.” As users use the cloud, the resources are large and numerous in general, a lot of servers and hardware devices, a lot of data and databases, and others. The concept of edge computing is to reallocate computing tasks requested by the user to resources that are very close to the user applications. It is not the physical distance only but the levels of technology communications layers, practical, permissions and so on which would delay the computing. In other words, edge computing is about brining computation and data storage closer to the devices where it’s being managed. This way data, especially real-time data, does not suffer latency issues that can affect an application’s performance. Edge computing is a pragmatic necessity as technology is witnessing exponential growth of IoT and smart devices. These devices are connected to the internet for either receiving information from the cloud or delivering data back to the cloud, generating large amounts of data.
The general paradigm for smart technology platforms uses five different levels. Fig 4.1 shows these levels.
Figure 1. Levels of cloud-based smart technology platform
- 1.
Gateway level includes devices that include smartphones, laptop computers and tablets. These devices are used as an interface between the IoT layer and computational resources. Their main role is to collect such data from the primary sources which are generated in the IoT level, package them and do any preprocessing needed and then shipped to the next level where actual computing takes place.
- 2.
Broker level: This level is a critical one since it is the executive that has the role of examining all data and application needs. It mediates and makes key decisions for the computational network. It examines the context of IoT devices and smart sensors, identifies functions to do and kind of application requested. Furthermore, it determines, according to preset specifications and setups, where is best the processing can be done. In other words, it determines the proper edge of the cloud to send both data and control applications so the job can be done at the edge. In fact, there are four sublevel services that comprise this level:
- a.
Intelligent IoT-edge manger: This sublevel is designed to manage and monitor all resources and services such as systems, applications, processes. This includes making programmed decisions where to send the task within the cloud, or to what edge. As developing nations, cities may not have fast and reliable in tent connection all the time, so have the cloud using an edge (a hardware setup connected to the cloud) within easy connections to the city, services and operations become more reliable. A critical function is done by the Application Scheduler through applying policies and techniques to maintain the performance of the system by allocating jobs to the best Edge or Cloud nodes This level formally includes the following: