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Context-aware Control Platform for Sensor Network Integration in IoT and Cloud

Daniel MEREZEANU*, Gheorghe VASILESCU, Radu DOBRESCU
Faculty of Automatic Control and Computer Science,
University Politehnica of Bucharest,
313, Splaiul Independentei, 060042, Romania
danmerezeanu@gmail.com

* Corresponding author

Abstract: The main goal of the paper is to integrate three emergent technologies (Wireless Sensor Networks, Internet of Things and Cloud Computing) in a framework supporting context-aware sensing, computing and communication capabilities into industrial applications. In this regard, the paper presents original solutions for a context-aware three-tier system architecture, that provides context information sensing and processing, an access mechanism for interfacing sensor networks with IoT and Cloud and a four-level architecture to perform industrial process control, that includes the modules of a context-aware control platform. These solutions are validated with a proof of concept application implemented on a IBM Bluemix IoT platform.

Keywords: Wireless Sensor Networks; Internet of Things Cloud Computing; context-aware systems; access mechanism; sensor-cloud interface; web services.

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CITE THIS PAPER AS:
Daniel MEREZEANU*, Gheorghe VASILESCU, Radu DOBRESCU,
Context-aware Control Platform for Sensor Network Integration in IoT and Cloud, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(4), pp. 489-498, 2016.

  1. Introduction

Sensor networks have rapidly imposed usefulness in a variety of applications, such as in control of industrial processes, in environmental monitoring, or in active and assisted living. We find them in Supervisory Control and Data Acquisition (SCADA) systems, mostly as Wireless Sensor and Actor Networks (WSANs). However, because SCADAs used more and more programs with expensive proprietary hardware, software and communication protocols, new solutions that make use of the common Internet protocols have proven to be more effective. In this complex open service environment, the way to integrate heterogeneous sensor networks is very important. Some authors advanced the name of Ubiquitous Sensor Network Environment (USN) [10]. USN provides integration of data from various sensors, sensor data and context information processing, sensor network monitoring and intelligent events handling. USN enables the competitive Internet of Things (IoT), mediating interactions with the outside world in pervasive ways.

IoT consists of large-scale, distributed multi-agents placed in dynamically changing environments that present wireless connectivity. In the same time, with the development of wireless based Internet devices presenting ubiquitous availability, more and more entities included in IoT are becoming context-aware. These devices can perceive their surroundings based on the gathered context information.

If in its beginning IoT vision was to enable devices to transfer data from various objects into the web, today this vision aims at enabling smart and context-aware applications at global scale extension of pervasive computing paradigm. Therefore, context-aware architectures must be designed to respond to the various demands of users and applications by offering the possibility to acquire, analyze and interpret relevant context information, and to offer adequate feedback to contextual changes.

The purpose of this paper is to propose a competitive architecture of a context aware system that can allow the access of agents connected in sensor networks to the IoT, starting from the evidence that such objects have data and ubiquitous web services need to access, learn and interpret this data.

In the same time, the opportunities to use Cloud Computing facilities were analysed, as well as the distribution of platform modules of the proposed platform in different layers of the Sensor Network-IoT-Cloud global software architecture. The proposed architecture provides the technology to connect these three conceptual paradigms in process control applications. A proof of concept IoT application is described finally.

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https://doi.org/10.24846/v25i4y201610