The aim of Ambient Assisted Living (AAL) is to help people (e.g., elderly, children) to have an independent and monitored life with the use and assistance of technology. For this population, specific technologies have been developed; many of those technologies (i.e., hardware, software) use sensors and embedded systems. Although there are many studies that address AAL approaches, no systematic literature reviews have been presented that cover hardware and software working together and take into account specific disabilities. Therefore, in this paper a systematic literature review of primary studies related to AAL is presented, which is focused on establishing software and hardware relations working together in order to solve or support specific disabilities. In this study, 3297 articles were extracted, from them only 48 were selected after applying the corresponding inclusion and exclusion criteria.

The Internet of Things (IoT) is a technological paradigm involved in a diversity of domains with favorable impacts on people’s daily lives and the development of industry and cities. Nowadays, one of the most critical challenges is developing software for IoT systems since the traditional Software Engineering methodologies and tools are unproductive in the face of the complex requirements resulting from the highly distributed, heterogeneous, and dynamic scenarios in which these systems operate. Model-Driven Engineering (MDE) emerges as an appropriate approach to abstract the complexity of IoT systems. However, there are no domain-specific languages (DSLs) aligned to standardized reference architectures for IoT. Furthermore, existing DSLs have an incomplete language to represent the IoT entities that may be needed at the edge, fog, and cloud layers to monitor IoT environments. Therefore, this paper proposes a domain-specific language named Monitor-IoT, which supports developers in designing multi-layer monitoring architectures for IoT systems with high abstraction, expressiveness, and flexibility. Monitor-IoT consists of a high-level visual modeling language and a metamodel aligned with the ISO/IEC 30141:2018 reference architecture. In addition, it provides a language capable of modeling architectures with a wide variety of digital entities and dataflows (synchronous and asynchronous) between them across the edge, fog, and cloud layers to support the monitoring of a diversity of IoT scenarios. The empirical evaluation of Monitor-IoT through the application of an experiment, which contemplates the use of the Technology Acceptance Model (TAM), demonstrates the intention of the participants to use this tool in the future since they consider it easy to use and useful.

Assistive Technology (AT) maintains and improves the individual’s functioning and independence, thereby promoting their well-being.

In the XXI century, electronic commerce is considered as an alternative to reduce costs, increase the productivity, among other benefits, all of them perceived through the digitalization of billing. Although there is a large amount of literature on this field, such literature is not focused on electronic invoicing platforms with notification delivery. Thus, the present systematic literature review has been performed, it is based on a reliable, auditable and rigorous methodology in order to know and clarify the state of the art in the subject associated to electronic invoicing, technological aspects related and notification systems. The analysis of the 39 selected papers from a total of 1202, shows the absence of studies that relate the use of notifications into e-invoicing systems.

Cloud Computing represents a new trend in the development and use of software. Many organizations are currently adopting the use of services that are hosted in the cloud by employing the Software as a Service (SaaS) model. Services are typically accompanied by a Service Level Agreement (SLA), which defines the quality terms that a provider offers to its customers. Many monitoring tools have been proposed to report compliance with the SLA. However, they have some limitations when changes to monitoring requirements must be made and because of the complexity involved in capturing low-level raw data from services at runtime. In this paper, we propose the design of a platform-independent monitoring middleware for cloud services, which supports the monitoring of SLA compliance and provides a report containing SLA violations that may help stakeholders to make decisions regarding how to improve the quality of cloud services. Moreover, our middleware definition is based on the use of models@run.time, which allows the dynamic change of quality requirements and/or the dynamic selection of different metric operationalizations (i.e., Calculation formulas) with which to measure the quality of services. In order to demonstrate the feasibility of our approach, we show the instantiation of the proposed middleware that can be used to monitor services when deployed on the Microsoft Azure© platform.

Cloud computing is being adopted by commercial and governmental organizations driven by the need to reduce the operational cost of their information technology resources and search for a scalable and flexible way to provide and release their software services. In this computing model, the Quality of Services (QoS) is agreed between service providers and their customers through Service Level Agreements (SLA). There is thus a need for systematic approaches with which to assess the quality of cloud services and their compliance with the SLA. In previous work, we introduced a generic method for Monitoring cloud Services using models at RunTime (MoS@RT), which allows the monitoring requirements or the metric operationalizations of these requirements to be changed at runtime without the modification of the underlying infrastructure. In this paper, we present the design of a monitoring infrastructure that supports the proposed method with its instantiation to a specific platform and reports the results of an experiment carried out to evaluate the perceived efficacy of 58 undergraduate students when using the infrastructure to configure the monitoring of cloud services deployed on the Microsoft Azure platform. The results show that the participants perceived MoS@RT to be easy to use, useful, and they also expressed their intention to use the method in the future. Although further experiments must be carried out to strengthen these results, MoS@RT has proved to be a promising monitoring method for cloud services.