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Over the past few decades, there has been an ever-increasing penetration of Renewable Energy Generation in the power grid. However, unlike in the past, where fossil fuel generating plants are mostly located in remote areas, and in the proximity of the source of energy, the most common of the renewable generations, such as solar power systems, are haphazardly sited close to the loads because the source of energy, the sun, exists almost everywhere. This unplanned siting of renewable generating systems aggravates the power distribution lines congestion that already exists due to the power distribution deregulation. This paper presents a procedure that takes advantage of utilization and proper placement of Photovoltaic (PV) power systems to alleviate power line congestion. In this procedure, the base case load flow, without the solar generating system, is performed on the distribution network. And the bus with the lowest voltage is identified; this low voltage bus is indicative of congestion in the lines connecting the identified bus. A PV power system is then tied to that bus; the capacity of the PV generation is varied heuristically to determine the optimality that mitigates the congestion on the lines. The procedure is followed to test a 9-bus IEEE power system, and the results are presented.

The Internet of Things (IoT) is growing at a very fast pace and being increasingly adopted in many scenarios of industrial applications such as energy (smart grid), automobile (smart cars), healthcare (smart healthcare), manufacturing (smart manufacturing and supply chain) and other application such as homes (smart home) and cities (smart city). Nonetheless, these IoT technologies (devices, systems, protocols, and applications) are faced with many security-related issues. IoT Systems have different layers that are vulnerable to various kinds of attacks. To defend against these attacks, one must consider appropriate security approaches and mechanisms to ensure privacy, security, and trust within the various components and layers that make up the IoT system. Appropriate security mechanism is needed at every layer of an IoT system to keep them secure. Hence, finding suitable mechanism for each IoT layer is a necessity to keep IoT systems secure in the 21st-century applications and implementations. The paper first investigates the IoT layers and protocols, their vulnerability issues, and methods to resolve the issues from existing literatures. We then present a blockchain-based security architecture for the internet of things and practically investigated its security feature through implementation of various security mechanism. Analysis and discussion of the blockchain implementation results are carried for the purpose of meeting the security, privacy, and trust requirements of IoT.

The concept of smart cities has been gaining attention globally for the past decade. A smart city is one that makes a conscious effort to use smart technologies (such as IoT and CPS) to improve the quality of life of its residents. The Internet of cities is a global network of smart cities. Such a network has hundreds of member cities around the world that could benefit, improve the health of local populations, and collaborate in order to improve cost and energy efficiency of city operation. This paper presents a brief introduction to the Internet of cities.

The use of digital devices and systems such smart phones, computers, the Internet, and social media has resulted in a massive volume of data which is exponentially increasing daily. Such data is processed using multiple techniques, collectively known as big data analytics. Big data analytics is the process of examining large amounts of data (big data) to uncover hidden patterns, correlations, and other insights. Analyzing big data enables organizations and businesses to make better and faster decisions. This paper briefly presents the fundamental concepts of big data analytics and its tools.

The concept of IT Consumerization has received a lot of attention since the introduction of Bring-Your-Own-Device (BYOD) management practice. It is using privately-owned ÌT resources such as devices or software for business purposes. It is a wave that no organization can afford to ignore. It seems unstoppable or inevitable because of the proliferation of tablets, laptops, smartphones, cloud storage, social tools, and mobile apps in the workplace. Using the same technologies for both work and private life comes at a price. This paper provides a brief introduction to IT consumerization.

Computational intelligence (CI) refers to recreating human-like intelligence in a computing machine. It consists of a set of computing systems with the ability to learn and deal with new situations such that the systems are perceived to have some attributes of intelligence. It is efficient in solving realworld problems which require reasoning and decision-making. It produces more robust, simpler, and tractable solutions than the traditional techniques. This paper provides a brief introduction to computational intelligence.