The development and high growth of the Internet of Things (IoT) have improved quality of life and strengthened different areas in society. Many cities worldwide are looking forward to becoming smart. One of the most popular use cases in smart cities is the implementation of smart parking solutions, as they allow people to optimize time, reduce fuel consumption, and carbon dioxide emissions. Smart parking solutions have a defined architecture with particular components (sensors, communication protocols, and software solutions). Although there are only three components that compose a smart parking solution, it is important to mention that each component has many types that can be used in the deployment of these solutions. This paper identifies the most used types of every component and highlights usage trends in the established analysis period. It provides a complementary perspective and represents a very useful source of information. The scientific community could use this information to decide regarding the selection of types of components to implement a smart parking solution. For this purpose, herein we review several works related to smart parking solutions deployment. To achieve this goal, a semi-cyclic adaptation of the action research methodology combined with a systematic review is used to select papers related to the subject of study. The most relevant papers were reviewed to identify subcategories for each component; these classifications are presented in tables to mark the relevance of each paper accordingly. Trends of usage in terms of sensors, protocols and software solutions are analyzed and discussed in every section. In addition to the trends of usage, this paper determines a guide of complementary features from the type of components that should be considered when implementing a smart parking solution.

Finding a parking space in a city is one of the most common activities of a driver. This becomes more difficult when the city is unknown or has huge vehicular congestion. A solution to address this issue is called smart parking. Smart parking solutions rely on Internet of Things (IoT) and several technologies to achieve their purpose. This paper proposes an architecture for deploying a smart parking solution based on Long-Range Wide Area Network (LoRaWAN) sensors, LoRaWAN and a cluster of Kubernetes. This approach provides an open architecture able to share information with other parties through a REST API interface. Likewise, it contains a mobile and a web application for user interaction. This solution provides an administration interface for managing parking lots. The user interface lets a user to find, view information, display available spaces and rate a parking lot in real time. This solution could be used as an application as service parking system. The proposed architecture is fully portable and scalable due to the use of Kubernetes.

IoT systems contribute to digital transformation through the development of smart concepts. However, the IoT has also generated new security challenges that require security tools to be adapted, such as risk analysis methodologies. With this in mind, the purpose of our study is based on the following question: Which factors of IoT devices should be considered within risk assessment methodologies? We have addressed our study with a 4-phase design-research methodology (DRM) that allows us, based on systematic literature review, to experiment and draw upon expert judgment; as a final product, we obtain a risk assessment methodology based on the characteristics of IoT devices. At the end of this study, we establish seven main constructs—Organization, Risk Behaviors, Dependency, Attack Surface, Susceptibility, Severity and Uncertainty—over which security risk in IoT systems can be evaluated.

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