A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living

The ORIS Tool: Quantitative Evaluation of Non-Markovian Systems

“…Using the graphical interface, the user can quickly develop a model and validate its operation using the interactive simulator or through the evaluation of quantitative requirements; once validated, the model can be exported from ORIS as Java code using the API of the SIRIO library. This integration allows the user to introduce quantitative evaluation of parametric non-Markovian models into larger software projects, such as tools for computer-aided design of critical infrastructures [21], [25], autonomic systems using models at runtime [15], ambient assisted living applications [20]. In contrast, tools such as TimeNET or GreatSPN allow graphical editing of a model, but not its integration in other software projects; and tools such as PRISM or Storm require input models specified with text-based formalisms.…”

“…We illustrate how ORIS can be exploited in quantitative evaluation of non-Markovian models by reviewing some selected cases of application [55], [24], [14], [25], [13], [20], [11], in various domains and with different usage patterns.…”

“…ORIS has been developed for several years and put to the test of practice in various application domains, addressing different modeling and evaluation challenges [55], [24], [14], [25], [13], [20], [11]. Overall, ORIS is now a well-engineered software tool, fully implemented in Java, designed so as to accommodate agile implementation of new features for Petri net models and new solution techniques for their underlying stochastic processes.…”

“…Specifically, in Sections 2 and 3, we illustrate how to construct STPN models and perform quantitative analysis of their underlying stochastic processes, respectively, using a running example from the literature on software rejuvenation to describe the typical modeling and evaluation workflow in ORIS (including derivation of distributions of GEN durations), the class of properties that can be analyzed, and the limits of the analysis methods. In Section 4, we review selected case studies where ORIS has been applied to the quantitative evaluation of models of real-time software [24], [55], railway signalling systems [13], repair procedures for gas and water distribution networks [14], [25], and activity recognition [20], [11]. Finally, conclusions are drawn in Section 5.…”

Model-Based Quantitative Evaluation of Repair Procedures in Gas Distribution Networks

“…The approach enumerates stochastic state classes that can be reached within a time limit t max , each class encoding the current marking plus the joint support and the joint PDF of the times-to-fire of the enabled transitions and an additional timer measuring the elapsed time. Marking probabilities at t ∈ [0, t max ] are computed from the probability that each class is the last node reached within t. The approach is implemented in the ORIS Tool (Biagi et al 2017a; ORIS Tool 2018), which has been proven in use and successfully applied in a variety of applications (Biagi et al 2017b;Carnevali et al 2015Carnevali et al , 2018.…”