Now showing 1 - 10 of 13
  • Publication
    Implicit interaction : a prerequisite for practical AmI
    Intelligent User Interfaces represent one of the three distinguishing characteristics of AmI environments. Such interfaces are envisaged as mediating between the services available in an arbitrary physical environment and its inhabitants. To be effective, such interfaces must operate in both proactive and passive contexts, implicitly and explicitly anticipating and responding to user requests. In either case, an awareness of the prevailing situation is essential – a process that demands a judicious combination of data and decision fusion, as well as collaborative and centralized decision making. Given the constraints of AmI environments realizing a distributed lightweight computational infrastructure augmented with a need to address user needs in a timely manner poses significant challenges. In this paper, various issues essential to enabling seamless, intuitive and instinctive interaction in AmI environments are explored.
  • Publication
    Ontology-based query recommendation as a support to image retrieval
    Stock photo libraries are the most common means for publishers and advertisers to find images for their media. Searching for the perfect photo can be a time-consuming and frustrating task. This is because searching is often dependent on the descriptors or tags given to each photo by the editors and contributors to the library. The tagging process is subjective, further complicating the search process. We describe an algorithm that uses domain ontologies to improve the interactions with these libraries. Ontologies are used to expand query terms based on users' initial search queries.We present results that demonstrate that the use of ontologies greatly improves users ability to retrieve photos when undertaking a number of search tasks.
  • Publication
    Failure Detection in Wireless Sensor Networks: A Sequence-based Dynamic Approach
    (Association for Computing Machinery, 2014-01-02) ; ;
    Wireless Sensor Network (WSN) technology has recently moved out of controlled laboratory settings to real-world deployments. Many of these deployments experience high rates of failure. Common types of failure include node failure, link failure, and node reboot. Due to the resource constraints of sensor nodes, existing techniques for fault detection in enterprise networks are not applicable. Previously proposed WSN fault detection algorithms either rely on periodic transmission of node status data or inferring node status based on passive information collection. The former approach significantly reduces network lifetime, while the latter achieves poor accuracy in dynamic or large networks. Herein, we propose Sequence-Based Fault Detection (SBFD), a novel framework for network fault detection in WSNs. The framework exploits in-network packet tagging using the Fletcher checksum and server-side network path analysis to efficiently deduce the path of all packets sent to the sink. The sink monitors the extracted packet paths to detect persistent path changes which are indicative of network failures. When a failure is suspected, the sink uses control messages to check the status of the affected nodes. SBFD was implemented in TinyOS on TelosB motes and its performance was assessed in a testbed network and in TOSSIM simulation. The method was found to achieve a fault detection accuracy of 90.7% to 95.0% for networks of 25 to 400 nodes at the cost of 0.164% to 0.239% additional control packets and a 0.5% reduction in node lifetime due to in-network packet tagging. Finally, a comparative study was conducted with existing solutions.
      369Scopus© Citations 39
  • Publication
    Using situation lattices in sensor analysis
    Highly sensorised systems present two parallel challenges: how to design a sensor suite that can efficiently and cost-effectively support the needs of given services; and to extract the semantically relevant interpretations, or “situations”, from the flood of context data collected by the sensors. We describe mathematical structures called situation lattices that can be used to address these two problems simultaneously, allowing designers to both design and refine situation identification whilst offering insights into the design of sensor suites. We validate the accuracy and efficiency of our technique against a third-party data set and demonstrate how it can be used to evaluate sensor suite designs.
      626Scopus© Citations 16
  • Publication
    From physical models to well-founded control
    Mobile sensors are an attractive proposition for environmental sensing, but pose significant engineering problems. Not least amongst these is the need to match the behaviour of the sensor platform to the physical environment in which it operates. We present initial work on using models of physical processes to generate models for autonomic control, and speculate that these can be used to improve the confidence we can place in sensed data.
      914Scopus© Citations 2
  • Publication
    PI : perceiver and interpreter of smart home datasets
    Pervasive healthcare systems facilitate various aspects of research including sensor technology, software technology, artificial intelligence and human-computer interaction. Researchers can often benefit from access to real-world data sets against which to evaluate new approaches and algorithms. Whilst more than a dozen data sets are currently publicly available, their use of heterogeneous mark-up impedes easy and widespread use. We describe PI – the Perceiver and semantic Interpreter – which offers a workbench API for the querying, re-structuring and re-purposing of a range of diverse data formats currently in use. The use of a single API reduces cognitive overload, improves access, and supports integration of generic and domain-specific information within a common framework.
  • Publication
    Ontonym : a collection of upper ontologies for developing pervasive systems
    Pervasive systems present the need to interpret large quantities of data from many sources. Context models support developers working with such data by providing a shared representation of the environment on which to base this interpretation. This paper presents a set of requirements for a context model that addresses uncertainty, provenance, sensing and temporal properties of context. Based on these requirements, we describe Ontonym, a set of ontologies that represent core concepts in pervasive computing. We propose a framework for evaluating ontologies in the pervasive computing domain by combining recognised techniques from the literature, and present a preliminary evaluation of Ontonym using these criteria.
      825Scopus© Citations 36
  • Publication
    High Accuracy Reference-free Ultrasonic Location Estimation
    This paper presents a novel reference-free ultrasonic indoor location system. Unlike most previous proposals, the mobile device (MD) determines its own position based only on ultrasonic signals received at a compact sensor array and sent by a fixed independent beacon. No radio frequency or wired timing reference signal is used. Furthermore, the system is privacy aware and one way in that the receive-only MD determines its own position based on ultrasonic signals received from fixed transmit-only beacons. The MD uses a novel hybrid angle of arrival (AoA)¿time of flight (ToF) with timing lock algorithm to determine its location relative to the beacons with high accuracy. The algorithm utilizes an AoA-based location method to obtain an initial estimate of its own location. Based on this, it estimates the timing offsets (TOs) between the MD clock and the beacon transmissions. The average TO and the known periodicities of the beacon signals are then used to obtain a second more accurate MD location estimate via a ToF method. The system utilizes wideband spread spectrum ultrasonic signaling in order to achieve a high update rate and robustness to noise and reverberation. A prototype system was constructed, and the algorithm was implemented in software. The experimental results show that the method provides 3-D accuracy better than 9.5 cm in 99% of cases, an 80% accuracy improvement over the conventional AoA-only method.
      5350Scopus© Citations 94
  • Publication
    Activity recognition using temporal evidence theory
    The ability to identify the behavior of people in a home is at the core of Smart Home functionality. Such environments are equipped with sensors that unobtrusively capture information about the occupants. Reasoning mechanisms transform the technical, frequently noisy data of sensors into meaningful interpretations of occupant activities. Time is a natural human way to reason about activities. People's activities in the home often have an identifiable routine; activities place at distinct times throughout the day and last for predicable lengths of time. However, the inclusion of temporal information is still limited in the domain of activity recognition. Evidence theory is gaining increasing interest in the field of activity recognition, and is suited to the incorporation of time related domain knowledge into the reasoning process. In this paper, an evidential reasoning framework that incorporates temporal knowledge is presented. We evaluate the effectiveness of the framework using a third party published smart home dataset. An improvement in activity recognition of 70% is achieved when time patterns and activity durations are included in activity recognition. We also compare our approach with Naïve Bayes classifier and J48 Decision Tree, with temporal evidence theory achieving higher accuracies than both classifiers.
      1121Scopus© Citations 75
  • Publication
    Adaptive management of shared resource pools with decentralized optimization and epidemics
    Shared resource pools are facilities featuring a certain amount of resources which can be used by different applications. For managing resources in such pools, the demand of each application can be used. Such a demand, however, is driven by the workload, which varies over time. For that reason, adaptive approaches have been proposed for the management of shared resources pools. Whereas a number of solutions exist in this context, they are either not truly decentralized or do not apply to the problem we are dealing with. In this paper, we then present Darma, an approach for managing shared resource pools in a truly decentralized, adaptive, and optimal way.
      306Scopus© Citations 5