Dealing with Communication Channels within IEC61499 Component-Based Systems

Traditional approaches for developing automation systems consider system itself hardly can be changed. Current challenges in automation applications include the need of autoreconfiguration in response to process changes or event triggering. In order to face these requirements, new automation methodologies are necessary. Component-based technologies, initially defined for achieving efficient, structured and reusable designs can also be used to achieve adaptation. In this work, an IEC 61499-based framework that uses the concept to deal with reconfiguration issues is presented. The final output of the framework is a distributed system IEC61499 compliant. A new concept, the communication channel, is introduced providing a new abstraction layer to deal with communication between components. The joint use of automation components and communication channels allows defining complex automation systems in an easy way.

Domain-Specific Languages for Workflows.A Systematic Literature Review

This paper aims to provide an overview of the complete process in the development of a Domain-Specific Language (DSL). It explains the construction steps such as preliminary research, language implementation, and evaluation. Moreover, it provides details for different key components which are commonly found in the DSLs such as the abstraction layer, DSL metamodel, and the applications. It also explains the general limitations related to the Domain-Specific Languages for Workflows.

An Abstraction Layer Exploiting Voice Assistant Technologies for Effective Human—Robot Interaction

A lot of people have neuromuscular problems that affect their lives leading them to lose an important degree of autonomy in their daily activities. When their disabilities do not involve speech disorders, robotic wheelchairs with voice assistant technologies may provide appropriate human–robot interaction for them. Given the wide improvement and diffusion of Google Assistant, Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa, etc., such voice assistant technologies can be fully integrated and exploited in robotic wheelchairs to improve the quality of life of affected people. As such, in this paper, we propose an abstraction layer capable of providing appropriate human–robot interaction. It allows use of voice assistant tools that may trigger different kinds of applications for the interaction between the robot and the user. Furthermore, we propose a use case as a possible instance of the considered abstraction layer. Within the use case, we chose existing tools for each component of the proposed abstraction layer. For example, Google Assistant was employed as a voice assistant tool; its functions and APIs were leveraged for some of the applications we deployed. On top of the use case thus defined, we created several applications that we detail and discuss. The benefit of the resulting Human–Computer Interaction is therefore two-fold: on the one hand, the user may interact with any of the developed applications; on the other hand, the user can also rely on voice assistant tools to receive answers in the open domain when the statement of the user does not enable any of the applications of the robot. An evaluation of the presented instance was carried out using the Software Architecture Analysis Method, whereas the user experience was evaluated through ad-hoc questionnaires. Our proposed abstraction layer is general and can be instantiated on any robotic platform including robotic wheelchairs.

Online and transparent self-adaptation of stream parallel patterns

Several real-world parallel applications are becoming more dynamic and long-running, demanding online (at run-time) adaptations. Stream processing is a representative scenario that computes data items arriving in real-time and where parallel executions are necessary. However, it is challenging for humans to monitor and manually self-optimize complex and long-running parallel executions continuously. Moreover, although high-level and structured parallel programming aims to facilitate parallelism, several issues still need to be addressed for improving the existing abstractions. In this paper, we extend self-adaptiveness for supporting autonomous and online changes of the parallel pattern compositions. Online self-adaptation is achieved with an online profiler that characterizes the applications, which is combined with a new self-adaptive strategy and a model for smooth transitions on reconfigurations. The solution provides a new abstraction layer that enables application programmers to define non-functional requirements instead of hand-tuning complex configurations. Hence, we contribute with additional abstractions and flexible self-adaptation for responsiveness at run-time. The proposed solution is evaluated with applications having different processing characteristics, workloads, and configurations. The results show that it is possible to provide additional abstractions, flexibility, and responsiveness while achieving performance comparable to the best static configuration executions.

Graphene based Web Framework for Energy Efficient IoT Applications

Energy efficiency is a crucial factor to be considered while designing sensor network based Internet of Things (IoT) applications due to the compromise in terms of power constraint in these devices. The overall network and IoT device lifetime may be increased significantly by enhancing the energy conservation schemes. Design changes, duty cycle optimization at the MAC layer and various other solutions are proposed to achieve efficiency in energy utilization. In IoT sensing applications based on cloud computing, these challenges are overcome by means of integrating the constrained application mechanism with abstraction layer as proposed in this paper. The round trips for graph-based data representation and data delivery are reduced by incorporating the cloud services with an efficient web framework in order to achieve efficient data management and energy conservation in the IoT sensing applications. In specific applications, the aforementioned objectives may be achieved by the integration of potential technologies. Google cloud services along with Graphene web framework, RIOT OS and Z1 IoT motes are used for developing a testbed in the constrained applications at the abstraction layer for interfacing the proposed implementation. The sensor networks in IoT applications have achieved significant reduction in energy consumption and delay of data delivery using the proposed method when compared to the existing baseline approaches.

Unmanned aerial vehicle abstraction layer: An abstraction layer to operate unmanned aerial vehicles

This article presents a software layer to abstract users of unmanned aerial vehicles from the specific hardware of the platform and the autopilot interfaces. The main objective of our unmanned aerial vehicle abstraction layer (UAL) is to simplify the development and testing of higher-level algorithms in aerial robotics by trying to standardize and simplify the interfaces with the unmanned aerial vehicles. Unmanned aerial vehicle abstraction layer supports operation with PX4 and DJI autopilots (among others), which are current leading manufacturers. Besides, unmanned aerial vehicle abstraction layer can work seamlessly with simulated or real platforms and it provides calls to issue standard commands such as taking off, landing or pose, and velocity controls. Even though unmanned aerial vehicle abstraction layer is under continuous development, a stable version is available for public use. We showcase the use of unmanned aerial vehicle abstraction layer with a set of applications coming from several European research projects, where different academic and industrial entities have adopted unmanned aerial vehicle abstraction layer as a common development framework.