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The purpose of this paper is to introduce run time monitoring infrastructures and to analyze trace data inside a well-established component-based methodology. The goal is to show the concept among different monitoring requirements by defining a general reference architecture that can be adapted to different scenarios. Starting from design artifacts, generated by a system engineering modeling tool, and source code automatically generated from UML models, a custom Hardware monitoring sub-system infrastructure will be presented. This sub-system will be able to generate run-time artifacts for run-time verification. We will show how the framework provides round-trip support in the development chain, injecting monitoring requirements from design models down to code and its execution on the platform and trace data back to the models, where the expected behavior will then be compared with the actual behavior. This approach will be used towards optimizing design models for specific properties (e.g, for system performance), using a specific constraint approach compliant with UML standards. Industrial and custom use cases will be used to demonstrate the effectiveness of this approach in real scenarios.

Raman spectroscopy is a well-established technique for rapid analysis for Cultural Heritage characterization. It represents one of the most used and reliable technique because non invasive and usable, even on-site, without any sample preparation. Overall in the last decade, several methods have been tested with the purpose of obtaining an automatic classification process of spectra of unknown materials. Machine learning methods and in particular Neural Networks are the most recently exploited on this topic. Unfortunately, the availability of real Raman spectra is often limited considering the amount of data necessary for the use of these approaches. In this work we propose a pipeline for augmenting data with a GAN reinforcement, with the aim of creating a dataset large enough to take advantage of such. Furthermore, three types of neural networks (binary-NN, categorical-NN and CNN) are trained with the aforementioned dataset and compared with each other, taking into consideration their accuracy. The results show that the enhanced data augmentation with GANs significantly increases the accuracy of the networks.

The Ada Ravenscar profile is a subset of the Ada language which restricts Ada tasking features in order to provide the determinism required by hard real-time systems. Some of the Ravenscar rules are based on specific Ada constructs, which are not available in other languages, but the reasoning behind each rule can be applied also to different ones. The main objective of this paper is to show how the Ravenscar profile can be adapted to work in a system where the tasking features are managed by RTEMS, and C/Ada languages work together. Furthermore, a tool developed to automate Ravenscar compliance checks is presented and applied in the context of some experimental verification activities.

The presented Ph.D. project deals with the definition of an Electronic System-Level methodology, and the development of related prototype tools, for the exploitation of FPGA with the Dynamic Partial Reconfiguration feature. The goal of the project is to provide a Design for the ReConfigurability approach able to identify, at design-time, a set of system configurations that allow satisfying functional and non-functional requirements. Such configurations are then exploited, at run-time, by a system manager that is also able to take into account the reconfiguration cost to fully evaluate pro and cons of such a process. While the proposed Ph.D. project is still under development, its current status is described highlighting the planned works.

This work focuses on the definition of a home automation system based on power line communication. A low cost and non invasive system has been developed and tested with successful results. It is based on the Cypress CY8CPLC10, an integrated power line communication chip which embeds both a PHY modem and a network protocol stack. The information management and data generation processes are demanded to a microcontroller, in this first prototype, being implemented with a standard commercial board. Combining the use of a microcontroller with a power line modem and a dedicated software application it is possible to manage sensors and actuators in the neighbors through the power grid and without modifying the existing electrical and network systems.

Heterogeneous parallel devices are becoming widely diffused in the embedded systems application field since they allow to improve time performances and other orthogonal metrics (e.g., cost, power, size, etc.) at the same time. In such a context, the introduction of safety requirements, as dictated by the relevant standards (i.e., DO-178 B/C and RTCA/DO-254 in airborne systems, ARINC 653 for avionics software, ISO-26262 in automotive domain, etc.) while considering shared resources on a heterogeneous parallel HW platform, adds further challenges to industrial and academic research. This kind of platforms that execute tasks with different levels of criticality are commonly called mixed-criticality embedded systems. So, the main problem in their management is to ensure that low criticality tasks do not interfere with high criticality ones. The final goal is to allow several applications to interact and coexist on the same platform. For this, the exploitation of virtualization technologies (i.e., hypervisors) allows to guarantee isolation and to satisfy certification requirements but introduces scheduling overhead and new HW/SW partitioning challenges. In such a scenario, this work focuses on a framework for modeling, analysis, and validation of mixed-criticality and real-time systems based on an existing "Model-Based Electronic System Level HW/SW Co-Design" methodology. The main contribution of this work is the integration of the considered framework with Xamber tool in order to provide systems implementations by exploiting a design space exploration able to consider Xtratum-based SW partitions.

This paper presents the porting activities related to a famous agent-based middleware (MW) for Wireless Sensor Networks (WSN), i.e. Agilla. After discussing main WSN-MW features, the paper describes in detail the procedure used to port such a MW from TinyOS 1.x to TinyOS 2.x. The porting has been successfully completed and then validated by means of several Agilla applications. The new code, called Agilla2, is now available to the research community.

VISION is an innovative infrastructure providing real-time sensing services, with particular emphasis on 3D video, with mobile and context-aware operation. Hence, it has addressed the numerous challenges raised by the limitations of current technology for wireless sensor networks. VISION exploits the 60 GHz ultra-wide band radios to enable broadband transmissions, miniaturized devices and reduced interference. Due to the inherent high resource consumption of broadband wireless necessary for real-time 3D video, VISION sensor network has been optimized at all layers. Novel techniques to manage the huge number of nodes required by ubiquitous sensing, and innovative tools to support the development process of intelligent services have been designed. Full cross-layer adaptability to external conditions assure the system will be able to manage the available resources to provide the best achievable quality of service guaranteeing graceful degradation for video, audio and sensing applications. The innovative sensor nodes based on above concepts are described in this paper, in relation to the selected scenario of Fire Rescue. The full hardware/software architecture is described and the challenges are discussed.

Crazy Square is an interactive environment for music learning that is specifically developed for children approaching music and a musical instrument for the first time. Audio signal processing algorithms are required for the game to work properly such as pitch detection and beat detection. In this paper an analysis of Pitch Detection Algorithms (PDAs) responding to Crazy Square requirements is presented and performance results are analysed. The algorithm implemented in the interactive environment proposed is discussed.