Human Activity Recognition (HAR) is currently recognized as a key element of a more general framework designed to perform continuous monitoring of human behaviors in the area of Ambient Assisted Living (AAL), well-being management, medical diagnosis, elderly care, rehabilitation, entertainment and surveillance in smart home environments. In this paper, an innovative HAR system, exploiting the potential of wearable devices integrated with the skills of deep learning techniques, is presented with the aim of recognizing the most common daily activities of a person at home. The designed wearable sensor embeds an Inertial Measurement Unit (IMU) and a Wi-Fi section to send data on a cloud service and to allow direct connection to the Internet through a common home router so that the user themselves could manage the installation procedure. The sensor is coupled to a CNN network designed to make inferences with the minimum possible resources to keep open the way of its implementation on low-cost or embedded devices. The system is conceived for daily activity monitor and nine different activities can be highlighted with an accuracy of 97%.

ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. It provides a multi-agent architecture with a set of predefined and configurable agents performing the typical tasks of data mining applications. In particular, its architecture can manage different users’ applications; it maintains a high level of execution quality by distributing the agents of the applications on a dynamic set of computational nodes. Moreover, it provides reports about the analysis results and the collected data, which can be accessed through either a web browser or a dedicated mobile APP. After an introduction about the actor model and the software framework used for implementing the software library, this article underlines the main features of ActoDatA and presents its experimentation in some well-known data analysis domains.

The most important technological trend of the last years has been the rise of social networking systems to social phenomena involving hundreds of millions of people, attracting users from several social groups. Social networking systems blur the distinction between the private and working spheres, and users use such systems both at home and in the workplace, both professionally and with recreational goals. Social networking systems can be equally used to organize a work meeting, a dinner with colleagues or a birthday party with friends. For example, the chat systems that are embedded in social networking platforms are often the most practical way to contact a colleague to ask an urgent question, especially in technologically oriented companies. Moreover, several traditional information systems have been modified in order to include social aspects. Currently, social networking platforms are mostly used without corporate blessing, maintaining their status as feral systems.