SIXTH: A Middleware for Supporting Ubiquitous Sensing in Personal Health Monitoring

Carr, Dominic; O’Grady, Michael J.; O’Hare, Gregory M. P.; Collier, Rem W.

doi:10.1007/978-3-642-37893-5_47

Cited by 9 publications

(10 citation statements)

References 10 publications

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“…Other projects such as the projects presented in [9][11] formalize a middleware oriented to e-Health environment or other research papers as the presented in [10] which makes a revision about different middleware's, exposing its features, strengths and weakness.…”

Section: Related Workmentioning

confidence: 99%

“…The main cons of these projects, which propose a software solution layer (middleware) to improve the integration of wearable devices, are that are focused in a specific scope such as to provide an approach for a specific communication protocol [9] or for a specific area as e-Health [11] (focusing on a specific functionality). Furthermore, other relevant projects presented in the review [10] intend to accomplish with certain requirements such as openness, scalability, mobility and heterogeneity, but none meets with all requirements.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Towards a Model-Driven Approach for Sensor Management in Wireless Body Area Networks

Ruíz-Zafra¹,

Noguera²,

Benghazi³

2014

Internet and Distributed Computing Systems

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Abstract. Nowadays, new portable devices are constantly being launched with their ever greater application to an ever growing number of domains. These devices or wearables (from wearable computing) are present in many different areas ranging from healthcare to entertainment, and provide a series of features to enhance the quality of everyday life. When used in conjunction with other wearables, they give rise to wireless body area networks (WBAN) or body area networks (BAN). The large variety of devices along with the lack of standardized services, which means that each designer or engineer must customize the API design, forces developers to implement source code mostly from scratch in order to cope with the heterogeneity of wearables and support their integration on a wider system. The result of these drawbacks is that new device integration is hampered and the time spent on the software development process is increased and these problems are addressed in this paper. We propose a modeldriven approach based on a meta-model which has been designed to define and specify interaction with sensors. Our main aim is to distance developers from specific implementation and to cope with heterogeneous designs. The resulting models, which are instances of the proposed meta-model, are specified in a custom language which we call the wearable markup language (WML). We also introduce the coordinator, i.e. component-based software for handling sensor models and improving the integration of new sensors.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Towards a Model-Driven Approach for Sensor Management in Wireless Body Area Networks

Ruíz-Zafra¹,

Noguera²,

Benghazi³

2014

Internet and Distributed Computing Systems

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“…SIXTH has previously been utilized in a variety of application domains, including mobile sensing with augmented reality 17 and personal health monitoring. 18 The primary SIXTH components include the following:…”

Section: Sixth Sensor Middlewarementioning

confidence: 99%

“…These sources can be mined in concert to create a wider context for detected activity. SIXTH has previously been utilized in a variety of application domains, including mobile sensing with augmented reality and personal health monitoring …”

Section: The Snomac Prototypementioning

confidence: 99%

Semantic network management for next‐generation networks

Matheus¹,

Boran²,

Carr

et al. 2018

Computational Intelligence

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To accommodate the proliferation of heterogeneous network models and protocols, the use of semantic technologies to enable an abstract treatment of networks is proposed. Network adapters are employed to lift network specific data into a semantic representation. Semantic reasoning integrates the disparate network models and protocols into a common data model by making intelligent inferences from low-level network and device details. Automatic discovery of new devices, monitoring of device state, and invocation of device actions in a generic fashion that is agnostic of network types is enabled. A prototype system called SNoMAC is described that employs the proposed approach operating over UPnP, TR-069, and heterogeneous sensors. These sensors are integrated by means of a sensor middleware named SIXTH that augments the capabilities of SNoMAC to allow for intelligent management and configuration of a wide variety of sensor devices. A major benefit of this approach is that the addition of new models, protocols, or sensor types merely involves the development of a new network adapter based on an ontology. Additionally, the semantic representation of the network and associated data allows for a variety of client interfaces to facilitate human input to the management and monitoring of the system.By the year 2021, the Internet of Things (IoT) is expected to encompass 3.5 times as many connected devices as there are people on Earth. 1 In addition to the sheer volume of devices, there is the added complexity of dealing with the unchecked proliferation of new network data models and protocols. To deal with these issues, network and active media applications will not only require high performance and scalability but will also need the means for quickly and dynamically evolving to accommodate the changing universe of devices. Doing this effectively necessitates a new approach for integrating network models and protocols that facilitates the intelligent management of devices across layers and at various levels of abstraction. This allows devices to be handled generically as collections while maintaining the specifics necessary to monitor and control them individually. This paper advocates an approach to solving this problem that leverages the benefits afforded by semantic web technologies, combined with the advantages of intelligent middleware. This automates much of the organization and integration of heterogeneous devices and provides a platform upon which a wide variety of applications can be built.Semantic web technologies enable the definition of formal data models called "ontologies" that provide a number of conceptual and computational benefits. This includes data model alignment, heterogeneous data integration, built-in data abstraction mechanisms, automated inferencing, dynamic meta-modeling, and automatic consistency checking. These ontologies form the base upon which semantic tools such as SPARQL, 2 SWRL, 3 and OWL, 4 or a hybrid of these, can make intelligent inferences about both devices themselves and their networ...

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“…SIXTH [33] is a Java-based middleware for the Sensor Web. It allows sensor-driven applications and enables the dynamic tasking of sensor nodes to suit shifting application demands in near real time.…”

Section: Iot Middlewarementioning

confidence: 99%

Software Toolkits: Practical Aspects of the Internet of Things—A Survey

Wang

Zhou

et al. 2015

International Journal of Distributed Sensor Networks

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The Internet of Things (IoT) is neither science fiction nor industry hype; rather it is based on solid technological advances and visions of network ubiquity that are zealously being realized. The paper serves to provide guidance regarding the practical aspects of the IoT. Such guidance is largely missing in the current literature in which the focus has been more on research problems and less on issues describing how to set up an IoT system and what software toolkits are required. This paper aims to bridge this gap by providing guidance in terms of the software toolkits that can be utilized by IoT practitioners and research students to set up a practical IoT system. The IoT is the combination of multiple techniques; a onefold technology cannot become the IoT. This is conducted in a multilayer approach that covers node and operating systems, middleware, databases, IoT energy harvesting method, and so forth. We hope that this survey serves to be useful to researchers and practitioners in practical aspects of IoT.

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SIXTH: A Middleware for Supporting Ubiquitous Sensing in Personal Health Monitoring

Cited by 9 publications

References 10 publications

Towards a Model-Driven Approach for Sensor Management in Wireless Body Area Networks

Towards a Model-Driven Approach for Sensor Management in Wireless Body Area Networks

Semantic network management for next‐generation networks

Software Toolkits: Practical Aspects of the Internet of Things—A Survey

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