The correct use of energy can heavily impact on a family monthly bills and can also contribute to reduce the global air pollution production. Despite many available systems for domestic energy consumption, the real understanding of how domestic devices affect the total energy consumption is still a challenge. The Internet of Things (IoT) technology may contribute to the improvement of the energy habits awareness, by connecting sensors and mobile devices to provide people real-time consumption of a domestic environment. Many attempts have been done to integrate environmental sensors, mobile devices and people but this remains a challenge. This paper presents the use of a cheap and easy to apply Non-Intrusive Load Monitoring (NILM) system that show people their historical and real-time domestic energy consumption on mobile devices and sends them alerts if an energy overload is about to occur.
Ensembles are the engines that keep large computing infrastructures and architectures running, such as smart cities and smart campuses, among others. Being critical elements for the correct functioning of an entire system, constant and rigorous assessments or evaluations are performed on different aspects such as performance, quality, design, etc. But among these aspects, energy consumption and environmental impact that the ensembles have are not usually considered. Sustainability is a fundamental characteristic nowadays and ensembles are the elements that most directly affect it. For this reason, assessments should be extended towards the sustainability or “greenability” of ensembles. In this study we propose the use of the “Governance and Management Framework for Green IT”, a framework that we have developed, to conduct the assessment of the greenability of ensembles. Through this framework, we identify which are the goals and metrics that should be considered, as well as the practices and activities that must be assessed to ensure that the ensembles work individually in an eco-sustainable manner, to achieve an entire green system.
Computer security competitions in which teams competitively attack and defend programs in real time are powerful training vehicles, but they are costly to organize and run. The same problem arises in the case of cybersecurity education since practical exercises are hard to design and, once exploited, they cannot be reused by the same students. In this preliminary work, we propose the use of flow-based programming - and specifically the Node-RED tool - to semi-automatically generate resources for cybersecurity competitions and training. The long term goal is defining a library of modules which can be easily combined to build a pool of fresh exercises, which are injected with different vulnerabilities, but at the same time maintain similar levels of difficulty.