Swift population growth and rising demand for energy in the 21st century have resulted in considerable efforts to make the electrical grid more intelligent and responsive to accommodate consumers’ needs better while enhancing the reliability and efficiency of modern power systems. Internet of Things (IoT) has appeared as one of the enabling technologies for smart energy grids by delivering abundant cutting-edge solutions in various domains, including critical infrastructures. As IoT-enabled devices continue to flourish, one of the major challenges is security issues, since IoT devices are connected through the Internet, thus making the smart grids vulnerable to a diverse range of cyberattacks. Given the possible cascading consequences of shutting down a power system, a cyberattack on a smart grid would have disastrous implications for the stability of all grid-connected infrastructures. Most of the gadgets in our homes, workplaces, hospitals, and on trains require electricity to run. Therefore, the entire grid is subject to cyberattacks when a single device is hacked. Such attacks on power supplies may bring entire cities to a standstill, resulting in massive economic losses. As a result, security is an important element to address before the large-scale deployment of IoT-based devices in energy systems. In this report, first, we review the architecture and infrastructure of IoT-enabled smart grids; then, we focus on major challenges and security issues regarding their implementation. Lastly, as the main outcome of this study, we highlight the advanced solutions and technologies that can help IoT-enabled smart grids be more resilient and secure in overcoming existing cyber and physical attacks. In this regard, in the future, the broad implementation of cutting-edge secure and data transmission systems based on blockchain techniques is necessary to safeguard the entire electrical grid against cyber-physical adversaries.

Multiple objects detection and tracking are amongst the most important tasks in computer vision-based surveillance and activity recognition. This paper proposes a real-time multiple objects detection method and compares its performance with three existing methods. `Good Features to Track' algorithm is used to extract feature points from each frame. Based on the motion-based information, feature points corresponding to moving objects are extracted from next frame. Then, the number of moving objects in each frame is determined according to their motion-based information and position, and are later clustered using the k-means algorithm. Clustering of moving objects in this paper is performed using feature vectors made of pixels' intensities, motion magnitudes, motion directions and feature point positions. In terms of accuracy and efficiency, the proposed method is shown to be highly accurate in determining the number of moving objects and also fast in tracking them in the scene.

Nowadays, cloud computing has come to the attention of big companies due to its high potential and flexibility and profitability. The approach followed in cloud computing services is to pay the costs for requested resources for an agreed period of time. In this system, the resource providers have to offer the best tradeoff between the requested resources and the amount of money users can pay, to be profitable for resource owners, in addition to customer satisfaction. Therefore, due to the massive volume of requests scheduling the users' requests is difficult and creating frameworks for scheduling is necessary. Scheduling algorithms attempt to allocate the tasks to the existing resources by considering the quality of services. In this paper, we review and compare various scheduling methods in the cloud computing environment.

Many countries, including South Africa, have introduced policies and incentives to increase their renewable energy capacities in order to address environmental concerns and reduce pollutant emissions into the atmosphere. In addition, consumers in South Africa have faced the ever-increasing price of electricity and unreliability of the grid since 2007 due to the lack of sufficient electricity production. As a result, employing hybrid renewable energy systems (HRESs) have gained popularity. This research focuses on grid-connected HRESs based on solar photovoltaic (PV) panels and wind turbines as a potential way of reducing the dependency of residential sector consumers on the grid. It aims to identify the optimal sizing of renewable energy sources to be cost-effective for consumers over a certain period of time, using Durban as a case study. Two artificial intelligence methods have been used to obtain the optimal sizing for the available PV panels, wind turbines and inverters. The results shown that the combination of PV panels and battery storage can be a profitable option. A system using higher rated power PV panels can start to become profitable in a shorter lifetime, but employing batteries can only be cost-effective if a long enough lifetime is considered.

A crucial part of the smart grid communication network is the Advanced Metering Infrastructure (AMI), connecting a utility company to end-users to support telemetry and remote-control applications. Although different technologies and standards for smart metering systems exist, Power-Line Communication is the preferred technology for AMI networks in dense urban areas, and the G3-PLC, which uses DLMS/COSEM to support data exchange, is the most used standard in PLC-based AMI networks. This paper provides a holistic view of G3-PLC in smart metering systems, including its interaction with the DLMS/COSEM. It also covers the challenges and research opportunities in G3-PLC smart metering systems.

Smart grid is the concept for next-generation power grid that integrates information and communication technology into power grid. Advanced metering infrastructure (AMI) is an important aspect of smart grid, which requires establishment of a two-way communication system between consumers and utility. In this paper, the effect of network topology on the performance of a PLC-based AMI system is investigated. For this purpose, a narrow-band power line communication simulator in accordance with the G3-PLC standard is proposed that implemented using the OMNeT++ network simulator. It is shown that the topology of the AMI network has significant impact on the collision rate of the data concentrator switch.