SmartyCo: Managing Cyber-Physical Systems for Smart Environments

International audienceCyber-Physical Systems (CPS) are composed of heterogeneous devices, communicating with each other and interacting with the physical world. Fostered by the growing use of smart devices that are permanently connected to the Internet, these CPS can be found in smart environments such as smart buildings, pavilions or homes. CPS must cope with the complexity and heterogeneity of their connected devices while supporting end-users with limited technical background to configure and manage their system. To deal with these issues, in this paper we introduce SmartyCo, our approach based on Dynamic Software Product Line (DSPL) principles to configure and manage CPS for smart environments. We describe its underlying architecture and illustrate in the context of smart homes how end-users can use it to define their own CPS in an automated way. We then explain how such an approach supports the reconfiguration of smart devices based on end-users rules, thus adapting the CPS w.r.t. environment changes. Finally, we show that our approach is well-suited to handle the addition and removal of CPS devices while the system is running, and we report on our experience in enabling home inhabitants to dynamically reconfigure their CPS

Template-based ontology population for Smart Environments configuration

Smart Environment is one of several domains in which Semantic Web technologies are applied nowadays. Ontologies, in particular, are used as core modeling languages for representing devices, systems and environments. Developing such ontologies, that typically involve several device descriptions (individuals) and related information, i.e., individuals of classes contributing to the device model, is often done by a manual, time consuming, and error-prone approach. Flexible and semi-automatic tools are therefore needed to enhance ontology population and to enable end-users to fruitfully configure their Smart Environments without the intervention of an ontology expert. This paper presents a template based approach, which increases accuracy, ease of use, and time-effectiveness of the ontology population process by reducing the amount of user-given information of about an order of magnitude, with respect to the fully manual approach. User-required information only pertains device features (e.g., name, location, etc.) and never implies knowledge of Semantic Web technologies, thus enabling end-user configuration of smart homes and buildings. Experimental results with a prototypical implementation confirm the viability of the approach on a real-world use cas

Context-aware Dynamic Discovery and Configuration of 'Things' in Smart Environments

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Currently, such Internet-connected objects or `things' outnumber both people and computers connected to the Internet and their population is expected to grow to 50 billion in the next 5 to 10 years. To be able to develop IoT applications, such `things' must become dynamically integrated into emerging information networks supported by architecturally scalable and economically feasible Internet service delivery models, such as cloud computing. Achieving such integration through discovery and configuration of `things' is a challenging task. Towards this end, we propose a Context-Aware Dynamic Discovery of {Things} (CADDOT) model. We have developed a tool SmartLink, that is capable of discovering sensors deployed in a particular location despite their heterogeneity. SmartLink helps to establish the direct communication between sensor hardware and cloud-based IoT middleware platforms. We address the challenge of heterogeneity using a plug in architecture. Our prototype tool is developed on an Android platform. Further, we employ the Global Sensor Network (GSN) as the IoT middleware for the proof of concept validation. The significance of the proposed solution is validated using a test-bed that comprises 52 Arduino-based Libelium sensors.Comment: Big Data and Internet of Things: A Roadmap for Smart Environments, Studies in Computational Intelligence book series, Springer Berlin Heidelberg, 201

The simplicity project: easing the burden of using complex and heterogeneous ICT devices and services

As of today, to exploit the variety of different "services", users need to configure each of their devices by using different procedures and need to explicitly select among heterogeneous access technologies and protocols. In addition to that, users are authenticated and charged by different means. The lack of implicit human computer interaction, context-awareness and standardisation places an enormous burden of complexity on the shoulders of the final users. The IST-Simplicity project aims at leveraging such problems by: i) automatically creating and customizing a user communication space; ii) adapting services to user terminal characteristics and to users preferences; iii) orchestrating network capabilities. The aim of this paper is to present the technical framework of the IST-Simplicity project. This paper is a thorough analysis and qualitative evaluation of the different technologies, standards and works presented in the literature related to the Simplicity system to be developed

Sensor function virtualization to support distributed intelligence in the internet of things

It is estimated that-by 2020-billion devices will be connected to the Internet. This number not only includes TVs, PCs, tablets and smartphones, but also billions of embedded sensors that will make up the "Internet of Things" and enable a whole new range of intelligent services in domains such as manufacturing, health, smart homes, logistics, etc. To some extent, intelligence such as data processing or access control can be placed on the devices themselves. Alternatively, functionalities can be outsourced to the cloud. In reality, there is no single solution that fits all needs. Cooperation between devices, intermediate infrastructures (local networks, access networks, global networks) and/or cloud systems is needed in order to optimally support IoT communication and IoT applications. Through distributed intelligence the right communication and processing functionality will be available at the right place. The first part of this paper motivates the need for such distributed intelligence based on shortcomings in typical IoT systems. The second part focuses on the concept of sensor function virtualization, a potential enabler for distributed intelligence, and presents solutions on how to realize it

Supporting development and management of smart office applications: a DYAMAND case study

To realize the Internet of Things (IoT) vision, tools are needed to ease the development and deployment of practical applications. Several standard bodies, companies, and ad-hoc consortia are proposing their own solution for inter-device communication. In this context, DYnamic, Adaptive MAnagement of Networks and Devices (DYAMAND) was presented in a previous publication to solve the interoperability issues introduced by the multitude of available technologies. In this paper a DYAMAND case study is presented: in cooperation with a large company, a monitoring application was developed for flexible office spaces in order to reliably reorganize an office environment and give real-time feedback on the usage of meeting rooms. Three wireless sensor technologies were investigated to be used in the pilot. The solution was deployed in a "friendly user" setting at a research institute (iMinds) prior to deployment at the large company's premises. Based on the findings of both installations, requirements for an application platform supporting development and management of smart (office) applications were listed. DYAMAND was used as the basis of the implementation. Although the local management of networked devices as provided by DYAMAND enables easier development of intelligent applications, a number of remote services discussed in this paper are needed to enable reliable and up-to-date support (of new technologies)