The hybridization of renewable energy resources is a known topic in sustainable technology. Many projects are going on based on the topic. The use of Photovoltaic, wind energy, and other renewable resources can be helpful to optimize the load in the utility grid. Countries like Europe and other western countries have electricity storage, whether the developing countries are still struggling to make sure the stable utility grid connection to the distribution network system. In this research, we would like to discuss the different energy production processes sustainably. As we know, the energy sources are volatile and cannot always assure stable production to keep the requirements or demand properly. We want to use the combination of the sources in a way so that we can make the balance between the demand and the supply system. This research will be an overview in terms of technical and financial sites. Also, by using the different combinations of the Internet of things and data analysis method, we will see the correlation between the different sources and their production. Based on the production data, we can determine the financial feasibility and the outcome of the system. The main problem of renewable energy sources is uncertainty. In terms of wind energy, the velocity is also not stable according to the location. We want to show a predictive model by using the intelligent formula by which we can maintain the hybrid system. The production data from different sources will tell us their contribution to the system. This contribution will help us monitor the system and control which sources have more contribution on the demand side. The predictive model will have consisted of renewable sources such as photovoltaic, wind, utility grid, and inverter systems. In the research, the tool such as Artificial Intelligence can be implemented by sustainable management. The arrangement information is prepared to extricate data and based on resources. The renewable sources data are variant according to their location and it has an impact in terms of energy production. Data acquisition and analysis could help the current technologies such as smart grid, microgrid, and their control systems. This exploration aims to introduce a predictive foundation for the management of enormous volumes of data through large Information instruments (sensors) to help the coordination of environmentally friendly power. The main difference between the conventional electricity system and the renewable energy system is the variability of sources, with conventional sources such as utility grids and diesel generators and renewable sources consisting of photovoltaic (PV), wind, etc.
Due to the tremendous growth of Internet of Things (IoT) applications - e.g. smart homes, smart grids, smart factories – and the emerging integration into industrial systems, the cyber threat landscape for IoT and IIoT applications is rapidly evolving. Security by Design principles are still widely neglected in the design of IoT devices and protocols. For consumer IoT, the privacy of the applicant can be compromised when devices are inappropriately secured. With regard to Industrial IoT, the usage of insecure IIoT protocols such as MQTT can have a severe impact on the industrial environment such as failure or impairment of production systems. We evaluate the prevalence of exposed IoT and IIoT devices related to the protocol MQTT by means of the search engine Shodan. The approach, design and results of our analysis are summarized in this paper.
The Internet of Things and the Smart Home have become an increasingly important topic in recent years. The growing popularity of Smart Home Devices such as Smart TVs, Smart Door Locks, Smart Light Bulbs, and other devices is causing a rapid increase of vulnerabilities. Also, there are several vulnerabilities in software and hardware that make the security situation more complex and troublesome. Many of these systems and devices also process personal or secret data and control critical industrial processes. The need for security is extremely high. Owners and administrators of modern IoT devices are often overwhelmed with the task of securing their systems. Today, the spectrum of Smart Home technologies is growing faster than security can be guaranteed. Unsecured vulnerabilities endanger the security and privacy of consumers. This paper aims to examine the security and privacy aspects of Wi-Fi Connected and App-Controlled IoT-Based Smart Home Devices. For this purpose, the communication between the device, app, and the manufacturer's servers, as well as the firmware of the individual devices, will be examined. In particular, this paper highlights why it is important to make consumers aware of the security and privacy aspects of Smart Home devices. Finally, it will be shown which dangers exist when using these devices, how the use of these devices affects the privacy and security of the device and its users, and whether the devices comply with the European General Data Protection Regulation.
Since its invention, the Internet has changed the world, but above all, it has connected people. With the advent of the Internet of Things, the Internet connects things today much more than people do. A large part of the Internet of Things consists of IoT controlled Smart Home devices. The Internet of Things and the Smart Home have become an increasingly important topic in recent years. The growing popularity of Smart Home devices such as Smart TVs, Smart Door Locks, Smart Light Bulbs, and others is causing a rapid increase in vulnerable areas. In the future, many IoT devices could be just as many targets. The many new and inexperienced manufacturers and the absence of established uniform standards also contribute to the precarious situation. Therefore, new methods are needed to sensitize and detect these threats. In this paper, different existing approaches like those of the National Institute of Standards and Technology (NIST) and the Open Web Application Security Project (OWASP) are combined with concepts of this work like the Smart Home Device Life Cycle. In the context of this paper, a universal 31-page question-based test procedure is developed that can be applied to any Smart Home device. Based on this new, innovative security checklist, the communication between device, app, and the manufacturer's servers, as well as the firmware of IoT devices, can be analyzed and documented in detail. In the course of this paper, also a handout in the abbreviated form will be created, which serves the same purpose.
The aim of this paper is to describe the new concept of a Master level university course for computer science students to address the issues of IoT and Smart Home Security. This concept is well suited for professional training for interested customers and allows the creation of practical exercises. The modular structure of the course contains lectures and exercises on the following topics: 1. Introduction - IoT and Smart Home Technology and Impact 2. Homematic Technology and Smart Home Applications 3. Loxone Technology and Smart Home Applications 4. Raspberry Pi and Smart Home Applications 5. Security of IoT and Smart Home Systems and contains laboratory exercises of diverse complexities.