Model-Driven Engineering for End-Users in the Loop in Smart Ambient Systems

At the heart of cyber-physical and ambient systems, the user should permanently benefit from applications adapted to the situation and her/his needs. To do this, she/he must be able to configure her/his software environment and be supported as much as possible in that task. To this end, an intelligent “engine” assembles software components that are present in the ambient environment at the time and makes unanticipated applications emerge. The problem is to put the user “in the loop”, i.e., provide adapted and intelligible descriptions of the emerging applications, and present them so that the user can accept, modify or reject them. Besides, user feedback must be collected to feed the engine’s learning process. Our approach relies on Model-Driven Engineering (MDE). However, differently from the regular use of MDE tools and techniques by engineers to develop software and generate code, our focus is on end-users. Models of component assemblies are represented and made editable for them. Based on a metamodel that supports modeling and de- scription of component-based applications, a user interface provides multi-faceted representations of the emerging applications and captures user feedback. Our solution relies on several domain- specific languages and a transformation process, based on the established MDE tools (Gemoc studio, Eclipse Modeling Framework, EcoreTools, Sirius, Acceleo). It works in conjunction with the intelligent engine that builds the emerging applications and to which it provides learning data.

Possible Life Saver: A Review on Human Fall Detection Technology

Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed fall detection systems and devices has increased dramatically and some of them are already in the market. Fall detection devices/systems can be categorized based on their architectures as wearable devices, ambient systems, image processing-based systems, and hybrid systems, which employ a combination of two or more of these methodologies. In this review paper, a comparison is made among these major fall detection systems, devices, and algorithms in terms of their proposed approaches and measure of performance. Issues with the current systems such as lack of portability and reliability are presented as well. Development trends such as the use of smartphones, machine learning, and EEG are recognized. Challenges with privacy issues, limited real fall data, and ergonomic design deficiency are also discussed.

Thermal and Lighting Consumption Savings in Classrooms Retrofitted with Shading Devices in a Hot Climate

Most educational buildings in southern Spain do not meet current energy requirements as weak thermal envelopes and the lack of cooling systems lead to severe discomfort in classrooms, especially when temperatures are above 30 °C. Given that global warming is expected to worsen this situation in coming decades, one of the first steps to be taken is to protect window openings from high levels of solar radiation by adding shading devices to reduce indoor temperatures and improve visual comfort. The aim of this research is to evaluate the reduction in thermal and lighting consumption in a classroom where a solar protection system in the form of an egg-crate shading device was installed. Two classrooms—one with an egg-crate device and another with no shading system—were monitored and compared for a whole year. The use of an egg-crate device in these classrooms reduced indoor operative temperatures during warmer periods while also improving indoor natural illuminance levels. Moreover, annual electric air conditioning consumption decreased by approximately 20%, with a 50% reduction in electric lighting consumption. These savings in electricity were largely conditioned by the use patterns observed in these ambient systems.