Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Enriching conflict resolution environments with the provision of context information

It is a common affair to settle disputes out of courts nowadays, through negotiation, mediation or any other mean. This has also been implemented over telecommunication means under the so-called Online Dispute Resolution methods. However, this new technology-supported approach is impersonal and cold, leaving aside important issues such as the disputants’ body language, stress level or emotional response while being based on forms, e-mails or chat rooms. To overcome this shortcoming in this paper it is proposed the creation of intelligent environments for conflict resolution that can complement the existing tools with important knowledge about the context of interaction. This will allow decisionmakers to take better framed decisions based not only on figures but also on important contextual information, similarly to what happens when parties communicate in the physical presence of each other.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012) and PEst-OE/ EEI/UI0752/2011. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009).info:eu-repo/semantics/publishedVersio

Is Context-aware Reasoning = Case-based Reasoning?

The purpose of this paper is to explore the similarities and differences and then argue for the potential synergies between two methodologies, namely Context-aware Reasoning and Case-based Reasoning, that are amongst the tools which can be used for intelligent environment (IE) system development. Through a case study supported by a review of the literature, we argue that context awareness and case based reasoning are not equal and are complementary methodologies to solve a domain specific problem, rather, the IE development paradigm must build a cooperation between these two approaches to overcome the individual drawbacks and to maximise the success of the IE systems

Is Context-aware Reasoning = Case-based Reasoning?

The purpose of this paper is to explore the similarities and differences and then argue for the potential synergies between two methodologies, namely Context-aware Reasoning and Case-based Reasoning, that are amongst the tools which can be used for intelligent environment (IE) system development. Through a case study supported by a review of the literature, we argue that context awareness and case based reasoning are not equal and are complementary methodologies to solve a domain specific problem, rather, the IE development paradigm must build a cooperation between these two approaches to overcome the individual drawbacks and to maximise the success of the IE systems

Handling Emergent Conflicts in Adaptable Rule-based Sensor Networks

This thesis presents a study into conflicts that emerge amongst sensor device rules when such devices are formed into networks. It describes conflicting patterns of communication and computation that can disturb the monitoring of subjects, and lower the quality of service. Such conflicts can negatively affect the lifetimes of the devices and cause incorrect information to be reported. A novel approach to detecting and resolving conflicts is presented. The approach is considered within the context of home-based psychiatric Ambulatory Assessment (AA). Rules are considered that can be used to control the behaviours of devices in a sensor network for AA. The research provides examples of rule conflict that can be found for AA sensor networks. Sensor networks and AA are active areas of research and many questions remain open regarding collaboration amongst collections of heterogeneous devices to collect data, process information in-network, and report personalised findings. This thesis presents an investigation into reliable rule-based service provisioning for a variety of stakeholders, including care providers, patients and technicians. It contributes a collection of rules for controlling AA sensor networks. This research makes a number of contributions to the field of rule-based sensor networks, including areas of knowledge representation, heterogeneous device support, system personalisation, and in particular, system reliability. This thesis provides evidence to support the conclusion that conflicts can be detected and resolved in adaptable rule-based sensor networks

Contextual and Possibilistic Reasoning for Coalition Formation

In multiagent systems, agents often have to rely on other agents to reach their goals, for example when they lack a needed resource or do not have the capability to perform a required action. Agents therefore need to cooperate. Then, some of the questions raised are: Which agent(s) to cooperate with? What are the potential coalitions in which agents can achieve their goals? As the number of possibilities is potentially quite large, how to automate the process? And then, how to select the most appropriate coalition, taking into account the uncertainty in the agents' abilities to carry out certain tasks? In this article, we address the question of how to find and evaluate coalitions among agents in multiagent systems using MCS tools, while taking into consideration the uncertainty around the agents' actions. Our methodology is the following: We first compute the solution space for the formation of coalitions using a contextual reasoning approach. Second, we model agents as contexts in Multi-Context Systems (MCS), and dependence relations among agents seeking to achieve their goals, as bridge rules. Third, we systematically compute all potential coalitions using algorithms for MCS equilibria, and given a set of functional and non-functional requirements, we propose ways to select the best solutions. Finally, in order to handle the uncertainty in the agents' actions, we extend our approach with features of possibilistic reasoning. We illustrate our approach with an example from robotics

Non-invasive estimation of stress in conflict resolution environments

The current trend in Online Dispute Resolution focuses mostly on the development of technological tools that allow parties to solve conflicts through telecommunication means. However, this tendency leaves aside key issues, namely our concern with respect to context information that was previously available in traditional Alternative Dispute Resolution processes. The main weakness of this approach is that conflict resolution may become a cold process, focused solely on objective questions. In order to overcome this inconvenience, we move forward to incorporate context information in an Online Dispute Resolution platform. In particular, we consider the estimation of the level of stress of the users by analyzing their interaction patterns. As a result, the conflict resolution platform or the mediator may weight to what extent a party is affected by a particular matter, allowing one to adapt the conflict resolution strategy to a specific problem in real time