From Internet of Things to Internet of Intelligence

Research in Intelligent Agents is yielding interesting results, some of which have been translated into commercial ventures. Intelligent Agents are executable software components that represent the user and perform tasks on behalf of the user, and when the task terminates, the Agents send the result to the user. Agents are best suited for the Internet: a collection of computers interconnected together in a worldwide network. A number of Agent systems have been implemented and the simulation test results obtained do show the feasibility of Intelligent Agents and Agent systems. Agents’ technology gives rise to new application areas such as Automatic banking or Automatic Teller Machines (ATM), Imaging, Remote Teaching and Telemarketing, Telemedicine, and E-Commerce, among others. Several organizations have turned to the Internet to market their products to customers. Searching the vast amount of information online on the Internet is not only time-consuming but costly as well. Intelligent Agents are the user’s representative on the Internet. The Agents surf the Internet gathering information on behalf of the user, executing user tasks, and sending the results to the user after the task termination. The simulation test results do show that Intelligent Agents have the ability to navigate the Internet to carry out specific tasks on behalf of the user. The Internet of Things (IoT), a worldwide interconnected network of devices equipped with sensors that continuously gather, process, and share information, is a perfect platform for the implementation and operation of Intelligent Agents. The application of Intelligent Agents in the Internet of Things would provide a seamless platform to implement solutions to address challenges facing humanity. This chapter was aimed at reviewing the application of Intelligent Agents in Internet of Things to provide an environment or platform for execution of Internet of Intelligence.

The dependencies, interdependencies, and interrelationships between artificial intelligence (AI) and Internet of Things (IoT) are discussed in this chapter. The interaction between these fields creates a new convergence that permits standardisation, interoperability, and security. The focus of this chapter is on applications, underlying technologies, 6G network systems, and D2D communication within the framework of an intelligent and integrated ecosystem for computing, communication, coordination, and decision making. This chapter highlights some of the core 6G technologies that are anticipated to make it possible for IoT and AI to seamlessly converge.

Future wireless networks will have to manage billions of devices at once, and each one needs a high throughput to serve a range of applications, including speech, real-time video, high-definition video, and others. Due to the excessively high interference levels and poor performance of user equipment (UEs) at the cell boundary, cellular networks are unable to handle such heavy connections. Additionally, human users are the primary target audience for conventional cellular networks. The Internet of Things, the Internet of Everything, Smart X, and other machine-type communication systems are projected to play a significant part in future wireless networks. The main difficulty facing machine-type communications is connecting billions of units in an effective and scalable manner. Cellular topologies with centralized technology do not seem to operate in such scenarios because each cell can only support a certain number of UEs. In order to serve numerous UEs and make distributed signal processing simpler, cell-free (CF) networks with decentralized technologies have been suggested. The combination of CF networks and massive MIMO (mMIMO) technology yields a new concept: Cell-Free Massive MIMO (CF mMIMO) Networks. This chapter gives an overview of Cell-Free Massive MIMO Networks and the underlying technologies. Thus, CF mMIMO is a disruptive technology for the next generations of densified wireless systems. Since cell-free massive MIMO is a developing technology, a number of issues and questions still need to be tackled before rolling out it into practice. In this chapter, we will highlight the various issues concerning CF mMIMO with clear explanation. We will divulge into issues like signal processing schemes, channel estimation, pilot assignment schemes, power controls, and access point (AP) selection schemes among others.

Intelligent Agents are software entities that roam freely on the Internet and execute tasks as specified by the user or user commands. This chapter is aimed at providing an overview of the application of Intelligent Agents and Internet of Things in smart cities for traffic management. The combination of Intelligent Agents and IoT could provide a seamless means of managing traffic congestion and rerouting. The ability of the agents to access stored information (data) and to carry the data to different locations within the network demonstrates the agents’ capability to collect information and communicate the same. The Intelligent Agents co-located with IoT devices along the roads, collects and processes traffic data, the data which consists of traffic congestion, etc. is transmitted to the vehicle, which is analysed and used to determine the optimal route or in rout selection and for traffic management in smart cities.

The Industrial Internet of Things (IIoT) is an ever-evolving and rapidly growing field that has the potential to transform industries and businesses worldwide. In recent years, there has been a significant increase in the adoption of IIoT technologies, leading to a vast amount of data being generated and analyzed to improve processes and efficiency, as well as increase productivity. As the IIoT continues to advance, it is important to understand the emerging trends and future directions of this technology. One of the emerging trends is the integration of artificial intelligence (AI) and machine learning (ML) with IIoT devices, which enables the devices to learn and adapt to new situations, resulting in better decision-making and more efficient operations. This trend is expected to continue and grow, resulting in more sophisticated and intelligent IIoT systems. Another trend is the move toward edge computing, where data processing and analysis are carried out at the edge of the network, closer to the source of the data. This approach enables faster response times and reduces the need for data to be transmitted back and forth between devices and the cloud, leading to improved performance and reduced latency. In addition, the IIoT is expected to play an increasingly important role in the development of smart cities and infrastructure. The integration of IIoT devices with city infrastructure, such as traffic lights and public transport systems, can improve efficiency, reduce congestion, and enhance public safety. Future directions for the IIoT include the development of more sophisticated sensors and devices, as well as improvements in data analytics and visualization. Additionally, there is a growing need for standardized protocols and frameworks to enable interoperability between IIoT devices from different vendors.

The Internet of Intelligence (IoI) is a next-generation networking paradigm that integrates artificial intelligence (AI) and the Internet of Things (IoT) to create a more intelligent and interconnected world. The IoI will enable a wide range of new applications and services, such as smart cities, intelligent transportation, and personalized healthcare. However, the IoI also poses significant security challenges. This chapter provides an overview of the key technologies for information security for the IoI. It discusses the unique security challenges of the IoI and presents a number of promising security solutions. The abstract also highlights some of the key research directions in IoI security.

With the world’s population growing at alarming rates and arable lands on which to grow crops to feed humanity becoming smaller and smaller, it is time we develop smart agriculture and e-commerce to feed the ever-growing population. The combination of Intelligent Agents and Internet of Things (IoT) could offer ways/means to grow crops and to conduct commerce to feed the ever-growing world population. Intelligent Agents are software components that freely roam the Internet collecting, processing, and communicating data on behalf of the user. The Internet of Things represented by a collection of sensors/devices continually collecting, processing, and communicating data is a perfect platform to implement smart agriculture and e-commerce. This book chapter aims at applying Intelligent Agents and Internet of Things to smart agriculture and e-commerce; put in another way, the chapter aims at the combination of Intelligent Agents and Internet of Things in smart agriculture and e-commerce to serve or provide food security for humanity.

An environment for devices to collect, process, and communicate information is made possible by the Internet of Intelligence. The data that is shared could be private, sensitive, financial, or necessary for regular business operations. Using intrusion detection and prevention techniques is necessary to prevent unauthorized access and ensure the proper operation of the Internet of Intelligence. Intrusion detection is frequently used as a second line of defense to safeguard computer networks, in addition to intrusion prevention techniques such as authentication, firewalls, and cryptography that are used as a first line of defense. The crucial topic of security management is the main emphasis of this chapter. One of the most important issues in network security management today is intrusion detection. A few current systems are reexamined to highlight their benefits and drawbacks. The technology of multi-agent systems can be helpful for effectively developing and maintaining secured networks. Features such as autonomy, adaptability, and flexibility of the intelligent agent system allow the management of wireless network evolution in a more controlled way.

Embedded supercomputing has emerged as a promising technology for enhancing the performance and energy efficiency of edge devices such as Internet of Things (IoT) devices, smartphones, and embedded systems. By integrating high-performance computing capabilities in a small form factor, embedded supercomputers can enable real-time data processing, machine learning, and image recognition in edge devices, which can significantly improve their functionality and value. This review provides an in-depth analysis of the current state-of-the-art research and developments in embedded supercomputing for edge devices. It covers various aspects of the field, including hardware architecture, software frameworks, benchmarking, power management, applications, as well as security and privacy. This chapter begins by describing the hardware architecture of embedded supercomputers, including the processing units, memory hierarchy, and interconnects. It then provides an overview of the software frameworks for developing applications on embedded supercomputers, including programming models, software tools, and libraries. This is followed by a discussion of the benchmarking methodologies used for evaluating the performance and energy efficiency of embedded supercomputers, including a description of the power management techniques used for optimizing their energy consumption. The review then provides a detailed analysis of the applications of embedded supercomputing in various fields, such as real-time data processing, machine learning, and image recognition. Finally, it describes the security and privacy challenges of embedded supercomputing and the mechanisms used for addressing them. Overall, it highlights the key advancements, challenges, and future directions in this area, and identifies opportunities for further research and innovation.

These days, people want the world in their hands. Some technologies like ambient intelligence gathering satisfy the maximum need of a smart world, but they are not tightly coupled with the Internet. This naturally makes the people need another technology extension. Internet of Things (IoT) is an ideal emerging technology to influence the Internet and communication technologies. Simply, ‘Internet of Things’ connects living and non-living things ‘through the Internet’. Traditionally, in the object-oriented paradigm, everything in the world is considered as an object, but in the IoT paradigm, everything in the world is considered as a smart object and allows them to communicate with each other through Internet technologies physically or virtually. IoT refers to the use of standard Internet protocols for interaction between humans to things and things to things in an embedded network. Although the security needs are well-recognised, it is still not fully clear how existing IP-based security protocols can be applied to this new setting. In this chapter, we discuss the various security challenges in an IoT system. This chapter also provides standard IP-based security protocols and its implementation model, which can be used as a security system for IoT. This chapter also provides the convergence of IoT, artificial intelligence, and Intelligent Agents leading to what is known as the Internet of Intelligence.