Use Cases for Abnormal Behaviour Detection in Smart Homes

While people have many ideas about how a smart home should react to particular behaviours from their inhabitant, there seems to have been relatively little attempt to organise this systematically. In this paper, we attempt to rectify this in consideration of context awareness and novelty detection for a smart home that monitors its inhabitant for illness and unexpected behaviour. We do this through the concept of the Use Case, which is used in software engineering to specify the behaviour of a system. We describe a set of scenarios and the possible outputs that the smart home could give and introduce the SHMUC Repository of Smart Home Use Cases. Based on this, we can consider how probabilistic and logic-based reasoning systems would produce different capabilities

Narrative based Postdictive Reasoning for Cognitive Robotics

Making sense of incomplete and conflicting narrative knowledge in the presence of abnormalities, unobservable processes, and other real world considerations is a challenge and crucial requirement for cognitive robotics systems. An added challenge, even when suitably specialised action languages and reasoning systems exist, is practical integration and application within large-scale robot control frameworks. In the backdrop of an autonomous wheelchair robot control task, we report on application-driven work to realise postdiction triggered abnormality detection and re-planning for real-time robot control: (a) Narrative-based knowledge about the environment is obtained via a larger smart environment framework; and (b) abnormalities are postdicted from stable-models of an answer-set program corresponding to the robot's epistemic model. The overall reasoning is performed in the context of an approximate epistemic action theory based planner implemented via a translation to answer-set programming.Comment: Commonsense Reasoning Symposium, Ayia Napa, Cyprus, 201

A Logical Framework for Behaviour Reasoning and Assistance in a Smart Home

Abstract- Smart Homes (SH) have emerged as a realistic intelligent assistive environment capable of providing assistive living for the elderly and the disabled. Nevertheless, it still remains a challenge to assist the inhabitants of a SH in performing the “right” action(s) at the “right ” time in the “right ” place. To address this challenge, this paper introduces a novel logical framework for cognitive behavioural modelling, reasoning and assistance based on a highly developed logical theory of actions- the Event Calculus. Cognitive models go beyond data-centric behavioural models in that they govern an inhabitant’s behaviour by reasoning about its knowledge, actions and environmental events. In our work we outline the theoretical foundation of such an approach and describe cognitive modelling of SH. We discuss the reasoning capabilities and algorithms of the cognitive SH model and present the details of the various tasks it can support. A system architecture is proposed to illustrate the use of the framework in facilitating assistive living. We demonstrate the perceived effectiveness of the approach through presentation of its operation in the context of a real world daily activity scenario. Index Terms – Event calculus, cognitive modelling

A survey on the evolution of the notion of context-awareness

The notion of Context has been considered for a long time in different areas of Computer Science. This article considers the use of context-based reasoning from the earlier perspective of AI as well as the newer developments in Ubiquitous Computing. Both communities have been somehow interested in the potential of context-reasoning to support real-time meaningful reactions from systems. We explain how the concept evolved in each of these different approaches. We found initially each of them considered this topic quite independently and separated from each other, however latest developments have started to show signs of cross-fertilization amongst these areas. The aim of our survey is to provide an understanding on the way context and context-reasoning were approached, to show that work in each area is complementary, and to highlight there are positive synergies arising amongst them. The overarching goal of this article is to encourage further and longer-term synergies between those interested in further understanding and using context-based reasoning

Ontology-based Activity Recognition Framework and Services

This paper introduces an ontology-based integrated framework for activity modeling, activity recognition and activity model evolution. Central to the framework is ontological activity modeling and semantic-based activity recognition, which is supported by an iterative process that incrementally improves the completeness and accuracy of activity models. In addition, the paper presents a service-oriented architecture for the realization of the proposed framework which can provide activity context-aware services in a scalable distributed manner. The paper further describes and discusses the implementation and testing experience of the framework and services in the context of smart home based assistive living

Supporting context-aware engineering based on stream reasoning

In a world of increasing dynamism, context-awareness gives promise through the ability to detect changes in the context of devices, environment, and people. Equally, with stream reasoning using languages including C-SPARQL, continuous streams of raw data in RDF can be reasoned over for context awareness. Writing many context queries and rules this way can however be error prone, and often contains boilerplate. In this paper, we present a context modelling notation designed to support the creation of context-awareness based on stream reasoning systems. In validating our language there is tool support which, amongst other benefits, can generate context queries in C-SPARQL and context aggregation rules for higher level context knowledge processing. An Android compatible mobile platform context reasoner was developed which can handle these deployable context rules. This methodology and associated tools has been validated as part of an EU funded project

Towards formal modelling and verification of pervasive computing systems

Smart systems equipped with emerging pervasive computing technologies enable people with limitations to live in their homes independently. However, lack of guarantees for correctness prevent such system to be widely used. Analysing the system with regard to correctness requirements is a challenging task due to the complexity of the system and its various unpredictable faults. In this work, we propose to use formal methods to analyse pervasive computing (PvC) systems. Firstly, a formal modelling framework is proposed to cover the main characteristics of such systems (e.g., context-awareness, concurrent communications, layered architectures). Secondly, we identify the safety requirements (e.g., free of deadlocks and conflicts) and specify them as safety and liveness properties. Furthermore, based on the modelling framework, we propose an approach of verifying reasoning rules which are used in the middleware for perceiving the environment and making adaptation decisions. Finally, we demonstrate our ideas using a case study of a smart healthcare system. Experimental results show the usefulness of our approach in exploring system behaviours and revealing system design flaws such as information inconsistency and conflicting reminder services.No Full Tex