Semantic-driven Configuration of Internet of Things Middleware

We are currently observing emerging solutions to enable the Internet of Things (IoT). Efficient and feature rich IoT middeware platforms are key enablers for IoT. However, due to complexity, most of these middleware platforms are designed to be used by IT experts. In this paper, we propose a semantics-driven model that allows non-IT experts (e.g. plant scientist, city planner) to configure IoT middleware components easier and faster. Such tools allow them to retrieve the data they want without knowing the underlying technical details of the sensors and the data processing components. We propose a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of automated context-aware configuration of filtering, fusion, and reasoning mechanisms in IoT middleware according to the problems at hand. We incorporate semantic technologies in solving the above challenges. We demonstrate the feasibility and the scalability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized into any other middleware platform. We evaluate CASCoM in agriculture domain and measure both performance in terms of usability and computational complexity.Comment: 9th International Conference on Semantics, Knowledge & Grids (SKG), Beijing, China, October, 201

A Design of Wireless Sensor Networks for a Power Quality Monitoring System

Power grids deal with the business of generation, transmission, and distribution of electric power. Recently, interest in power quality in electrical distribution systems has increased rapidly. In Korea, the communication network to deliver voltage, current, and temperature measurements gathered from pole transformers to remote monitoring centers employs cellular mobile technology. Due to high cost of the cellular mobile technology, power quality monitoring measurements are limited and data gathering intervals are large. This causes difficulties in providing the power quality monitoring service. To alleviate the problems, in this paper we present a communication infrastructure to provide low cost, reliable data delivery. The communication infrastructure consists of wired connections between substations and monitoring centers, and wireless connections between pole transformers and substations. For the wireless connection, we employ a wireless sensor network and design its corresponding data forwarding protocol to improve the quality of data delivery. For the design, we adopt a tree-based data forwarding protocol in order to customize the distribution pattern of the power quality information. We verify the performance of the proposed data forwarding protocol quantitatively using the NS-2 network simulator

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun

A Distributed Sensor Data Search Platform for Internet of Things Environments

Recently, the number of devices has grown increasingly and it is hoped that, between 2015 and 2016, 20 billion devices will be connected to the Internet and this market will move around 91.5 billion dollars. The Internet of Things (IoT) is composed of small sensors and actuators embedded in objects with Internet access and will play a key role in solving many challenges faced in today's society. However, the real capacity of IoT concepts is constrained as the current sensor networks usually do not exchange information with other sources. In this paper, we propose the Visual Search for Internet of Things (ViSIoT) platform to help technical and non-technical users to discover and use sensors as a service for different application purposes. As a proof of concept, a real case study is used to generate weather condition reports to support rheumatism patients. This case study was executed in a working prototype and a performance evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4, No.1, January - March, 201

Micro Sensor Node for Air Pollutant Monitoring: Hardware and Software Issues

Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems

Air Pollution Monitoring System based on Wireless Networks - Simulation

Air pollution is one of environmental issues that cannot be ignored. Industrial growth and urbanization results in the air pollutants concentrations in many areas. These pollutants can cause damages in human health and other living organisms. The available pollutant emission monitoring systems, such as Opsis, Codel, Urac and TAS-Air metrics are typically expensive. In addition, these systems have limitations to be installed on chimney due to their principle of operation. This causes other areas surrounding the factories being unmonitored and hence cause healthy issues. This paper proposes an industrial air pollution monitoring system based on the technology of wireless sensor networks (WSNs). This system is integrated with the global system for mobile communications (GSM) and its communication protocol used is zigbee. The system consists of sensor nodes, a control center and data base through which sensing data can be stored for history and future plans. The proposed system can be deployed to the industries for monitoring carbon monoxide (CO), sulfur dioxide (SO2) and dust concentration caused by industrial emissions due to process.   Keywords: Zigbee, wireless sensor network, air pollution, GSM, network topology

A mobile application for assessment of air pollution exposure

In this paper the architecture of a mobile air quality monitoring system is introduced. A mobile application will act as a personal assistant, monitoring and giving advices about gas pollutants daily exposure. Currently in development stage as part of a larger air quality monitoring system project, the application will enable users to monitor their daily exposure to gas pollutants by combining user location data and urban air quality information provided by the network of fixed monitoring stations of the city of Palermo