(Archived) - M2M

Learning Semantic Features from Web Services

mantunes — Wed, 27 Jul 2016 17:06:19 +0000

In recent years the technological world has grown by incorporating billions of small sensing devices, collecting and sharing real-world information. As the number of such devices grows, it becomes increasingly difficult to manage all these new information sources. There is no uniform way to share, process and understand context information. It is our personal belief that IoT and M2M scenarios will only achieve their full potential when all the devices will work and learn together without human interaction. In this paper we review the most relevant semantic metrics and propose a new unsupervised model that minimizes sense-conflation problem. Our solution was evaluated against Miller-Charles dataset, outperforming our previous work in every metric.

Smart Cloud of Things: An Evolved IoT Platform for Telco Providers

mantunes — Wed, 20 Jan 2016 11:05:23 +0000

Although many environments are powered by smart solutions, users do not
have a simple way to gather their collective knowledge and program devices’
behaviour. Telecommunication (Telco) providers wish to act as the facilitator,
but still lack proper components for enabling integrated services over their
networks, even though this work is already in active standardisation. In
this work we present the architecture of a IoT solution developed in close
collaboration with Telco providers, its evolution, which we call SCoT (Smart
Cloud of Things), and the best practices from the several pilots we have been
running. The architecture builds upon ETSI standards, combined with a rich
service execution environment, providing facilitated orchestration of services
and devices, as well as integrated portals for end users access.

Scalable Semantic Aware Context Storage

mantunes — Mon, 21 Sep 2015 16:50:34 +0000

The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes' diversity and propose a novel d-dimension organization model. Our evaluation shows that d-dimension model improves scalability and semantic extraction.

Semantic features for context organization

mantunes — Mon, 21 Sep 2015 16:43:35 +0000

In recent years the technological world has grown by incorporating billions of small sensing devices, collecting and sharing real-world information. As the number of such devices grows, it becomes increasingly difficult to manage all these new information sources. There is no uniform way to share, process and understand context information. In previous publications we discussed efficient ways to organize context information that is independent of structure and representation. However, our previous solution suffers from semantic sensitivity. In this paper we review semantic methods that can be used to minimize this issue, and propose an unsupervised semantic similarity solution that combines distributional profiles with public web services. Our solution was evaluated against Miller-Charles dataset, achieving a correlation of 0.6.

Unified platform for M2M Telco Providers

mantunes — Tue, 09 Sep 2014 14:13:24 +0000

Although many environments are powered by M2M solutions, users do not have a simple way to gather their collective knowledge and program devices' behaviour. Also, Telco providers still lack proper components for enabling integrated services over their networks. We present the final architecture of the APOLLO project, which developed a full blown enhanced M2M platform encompassing sensors, management and applications platform for a major Telco provider. APOLLO builds on top of ETSI M2M specifications and rich service execution environments providing easy orchestration of services to end-users.

Semantic-based Publish/Subscribe for M2M

mantunes — Tue, 09 Sep 2014 13:54:58 +0000

The number of connected devices is expected to soar in the coming years, each one of them collects and distributes real-world information though various systems. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this informa-tion, however none of them have been widely adopted. Publish/ subscribe paradigm has proven to be an adequate abstraction for large scale information dissemination, but none of current variations is well suited for context information. In a previous publication we addressed these challenges, however our solution has some drawbacks: poor scalability and semantic extraction. The aim of this paper is twofold. First, we discuss an efficient way to deal with representation schemes diversity and propose a d-dimensional context organization model. Second, we propose a semantic-based publish/subscribe system that is well suited for M2M scenarios. Our evaluation shows that d-dimensional organization model outperforms our previous solution in both speed and space requirements.

Scalable Semantic Aware Context Storage

mantunes — Fri, 04 Jul 2014 13:32:02 +0000

In recent years the Internet has grown by incorpo-rating billions of small devices, collecting real-world information and distributing it though various systems. As the number of such devices grows, it becomes increasingly difficult to manage all these new information sources. Several context representation schemes have tried to standardize this information, however none of them have been widely adopted. Instead of proposing yet another context representation scheme, we discuss an efficient way to deal with this diversity of representation schemes. We define the basic requirements for context storage systems, analyse context organizations models and propose a new context storage solution. Our solution implements an organizational model that improves scalability, semantic extraction and minimizes semantic ambiguity.

Context Storage for M2M Scenarios

mantunes — Fri, 04 Jul 2014 13:25:44 +0000

As the number of environmental sensors grows, it becomes increasingly difficult to manage, store and process all these sources of information. Several context representation schemes try to standardize this information, however none of them have been widely adopted. Instead of proposing yet another context representation scheme, we discuss efficient ways to deal with this diversity of representation schemes. We defined the basic requirements for flexible context storage systems, proposed an implementation and compared our implementation against two other approaches. Our solution provides more value than the remaining solutions without suffering a significant decrease in performance.

M2Operator

arainho — Wed, 18 Apr 2012 09:59:25 +0000

Inúmeras previsões apontam para que nos próximos anos haja um crescimento significativo do mercado Máquina-a-Máquina. Muitos destes dispositivos estarão ligados à Internet, dando origem à propalada Internet of Things. A crescente integração de múltiplos sensores em dispositivos móveis permite a extracção de uma grande quantidade de informação, potenciando a sua utilização na dedução do(s) estado(s) em que o utilizador, serviços ou outros dispositivos, se encontram. Essa informação contextual extraída da informação sensorial pode e deve ser utilizada na oferta de novos serviços assentes em redes mais eficazes, e com maior taxa de aceitação pelo utilizador. Este artigo pretende descrever cenários de utilização da informação provinda dos mais variados tipos de sensores e evidenciar os modelos de negócio que exponham o papel do Operador no mundo das comunicações Máquina-a-Máquina.

MINDiT: A Framework for Media Independent Access to Things

dcorujo — Wed, 29 Feb 2012 10:39:37 +0000

Deploying Smart Environments often implies a plethora of co-existing devices and services, each with their own set of features, requirements and interfacing characteristics. These intricate scenarios are further exacerbated when such devices are coupled with networking capabilities, globalizing their interaction opportunities to create the so-called Internet of Things. In such interconnected heterogeneous environments, the joint operation of entities requires a flexible framework that enables and simplifies interfacing between elements. In this paper, we propose MINDiT, a framework that provides a common abstract interface towards the communication support with different entities. It incorporates cross-layer mechanisms inspired on the existing IEEE 802.21 technology, suitably modified to facilitate and optimize deployment in scenarios featuring both high-level, and low-powered network-restricted entities. MINDiT was validated through a prototype built over an open-source IEEE 802.21 implementation. We further compared its signaling impact against other solutions, and evaluated its performance over a smart environment featuring a multimedia scenario with multiple devices and services.

A Framework for Flexible Sensor Information Dissemination

msilva — Mon, 16 May 2011 12:42:45 +0000

The integration of the digital world into every aspect of our lives is becoming more and more preeminent. Nowadays, not only humans but also devices and the environments where we dwell are also able to provide their own information, through the usage of sensors. Through their interconnection over communication networks, sensors enable Ambient Intelligent scenarios achieving a true Internet of Things, and crossing the gap between computer systems and the real world. However, the different sensing devices and information generated by them, are of such disparate nature that it becomes increasingly difficult to access and make use of such heterogeneous data. In this paper, we propose a framework which not only considers a media independent information access to sensors and their supplied data, but is also flexible enough to configure and provide different means to best transport collected sensor information via wireless gateways, facilitating its deployment in different scenarios. We demonstrate its usefulness by providing a throughput efficient approach towards the collection and dissemination of sensing data, through sensing information compression and aggregation of multiple sources.