A Visual Paradigm for Defining Task Automation

In the last years, researchers are devoting many efforts to improve technological aspects of the Internet of Things (IoT), while little attention has dedicated to social and practical sides. Professional developers program the behavior of smart objects. In addition, often the functionality exposed by a single object are not able, alone, to exhaustively support the end users' tasks. The opportunities offered by IoT can be amplified if new highlevel abstractions and interaction paradigms enable also non-technical users to compose the behavior of multiple objects. To fulfill this goal, we present a model to express rules for smart object composition, which includes new operators for defining rules coupling multiple events and conditions exposed by smart objects, and for defining temporal and spatial constraints on rule activation. Such model has been implemented in a Web application whose composition paradigm has been designed during an elicitation study with 25 participants

Empowering CH experts to produce IoT-enhanced visits

This demo presents EFESTO-5W, a platform for the definition of IoT-enhanced visits to Cultural-Heritage (CH) sites. Its main characteristic is an End-User Development paradigm applied to the IoT technologies and customized for the CH domain, which allows different stakeholders to configure the behavior of smart objects for creating more engaging visit experiences

Empowering CH experts to produce IoT-enhanced visits

This demo presents EFESTO-5W, a platform for the definition of IoT-enhanced visits to Cultural-Heritage (CH) sites. Its main characteristic is an End-User Development paradigm applied to the IoT technologies and customized for the CH domain, which allows different stakeholders to configure the behavior of smart objects for creating more engaging visit experiences

End-user composition of interactive applications through actionable UI components

Developing interactive systems to access and manipulate data is a very tough task. In particular, the development of user interfaces (UIs) is one of the most time-consuming activities in the software lifecycle. This is even more demanding when data have to be retrieved by accessing flexibly different online resources. Indeed, software development is moving more and more toward composite applications that aggregate on the fly specific Web services and APIs. In this article, we present a mashup model that describes the integration, at the presentation layer, of UI components. The goal is to allow non-technical end users to visualize and manipulate (i.e., to perform actions on) the data displayed by the components, which thus become actionable UI components. This article shows how the model has guided the development of a mashup platform through which non-technical end users can create component-based interactive workspaces via the aggregation and manipulation of data fetched from distributed online resources. Due to the abundance of online data sources, facilitating the creation of such interactive workspaces is a very relevant need that emerges in different contexts. A utilization study has been performed in order to assess the benefits of the proposed model and of the Actionable UI Components; participants were required to perform real tasks using the mashup platform. The study results are reported and discussed

Exploring Archaeological Parks by Playing Games on Mobile Devices

Explore! is an m-learning system that combining e-learning and mobile computing allows middle school students to interact with learning materials in different ways while playing a game in an archaeological park. Design is based on user-centred and participatory approaches. The evaluation of Explore! through systematic field studies has shown that it is able to transform the visit to archaeological parks into a more complete and culturally rich experience. Thanks to the generality of the software infrastructure, games to be played in different parks can be easily created; to this aim, an Authoring Tool to be used by history experts and/or teachers has been developed

User-defined semantics for the design of IoT systems enabling smart interactive experiences

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Automation in computing systems has always been considered a valuable solution to unburden the user. Internet of Things (IoT) technology best suits automation in different domains, such as home automation, retail, industry, and transportation, to name but a few. While these domains are strongly characterized by implicit user interaction, more recently, automation has been adopted also for the provision of interactive and immersive experiences that actively involve the users. IoT technology thus becomes the key for Smart Interactive Experiences (SIEs), i.e., immersive automated experiences created by orchestrating different devices to enable smart environments to fluidly react to the final users’ behavior. There are domains, e.g., cultural heritage, where these systems and the SIEs can support and provide several benefits. However, experts of such domains, while intrigued by the opportunity to induce SIEs, are facing tough challenges in their everyday work activities when they are required to automate and orchestrate IoT devices without the necessary coding skills. This paper presents a design approach that tries to overcome these difficulties thanks to the adoption of ontologies for defining Event-Condition-Action rules. More specifically, the approach enables domain experts to identify and specify properties of IoT devices through a user-defined semantics that, being closer to the domain experts’ background, facilitates them in automating the IoT devices behavior. We also present a study comparing three different interaction paradigms conceived to support the specification of user-defined semantics through a “transparent” use of ontologies. Based on the results of this study, we work out some lessons learned on how the proposed paradigms help domain experts express their semantics, which in turn facilitates the creation of interactive applications enabling SIEs.Peer reviewedFinal Published versio

Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids

In smart electrical grids, fault detection tasks may have a high impact on society due to their economic and critical implications. In the recent years, numerous smart grid applications, such as defect detection and load forecasting, have embraced data-driven methodologies. The purpose of this study is to investigate the challenges associated with the security of machine learning (ML) applications in the smart grid scenario. Indeed, the robustness and security of these data-driven algorithms have not been extensively studied in relation to all power grid applications. We demonstrate first that the deep neural network method used in the smart grid is susceptible to adversarial perturbation. Then, we highlight how studies on fault localization and type classification illustrate the weaknesses of present ML algorithms in smart grids to various adversarial attacksComment: Accepted in AdvML@KDD'2