Smart Home has gained widespread attention due to its flexible integration into everyday life. Pervasive sensing technologies are used to recognize and track the activities that people perform during the day, and to allow communication and cooperation of physical objects. Usually, the available infrastructures and applications leveraging these smart environments have a critical impact on the overall cost of the Smart Home construction, require to be preferably installed during the home construction and are still not user-centric. In this paper, we propose a low cost, easy to install, user-friendly, dynamic and flexible infrastructure able to perform runtime resources management by decoupling the different levels of control rules. The basic idea relies on the usage of off-the-shelf sensors and technologies to guarantee the regular exchange of critical information, without the necessity from the user to develop accurate models for managing resources or regulating their access/usage. This allows us to simplify the continuous updating and improvement, to reduce the maintenance effort and to improve residents’ living and security. A first validation of the proposed infrastructure on a case study is also presented.

To respond to the growing needs of evolution and adaptation coming from the modern open connected world, applications must continuously monitor their own execution and the surrounding context. The events to be observed, belonging to guaranteed functional and non-functional properties, can themselves vary in scope and along time. Therefore the monitor must be easily configurable and able to serve differing event consumers. To address these requirements, we developed the Glimpse monitoring infrastructure conceived having flexibility and generality as main concerns. The paper introduces the architecture of Glimpse and shows how it can support runtime performance analysis through a simple example

Nowadays, more and more industrial organizations are using Business Process Model and Notation (BPMN) for process modeling. Key performance Indicators (KPIs) are seton such process models so to get a quantitative assessment of critical success metrics. A timely and reliable monitoring of KPIs is instrumental to Business Process (BP) management, and several frameworks are being proposed for such purpose. Business process monitoring solutions can be embedded into the Business Process Modeling (BPM) execution framework or integrated as additional facilities. This paper presents an integrated framework that allows for modeling, execution and analysis of business process based on a flexible and adaptable monitoring infrastructure. The main advantage of the proposed approach is that it is independent from any specific business process modeling notation and execution engine and allows for the definition and evaluation of user-specific KPI measures.