Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Transfer Scenarios: Grounding Innovation with Marginal Practices

Transfer scenarios is a method developed to support the design of innovative interactive technology. Such a method should help the designer to come up with inventive ideas, and at the same time provide grounding in real human needs. In transfer scenarios, we use marginal practices to encourage a changed mindset throughout the design process. A marginal practice consists of individuals who share an activity that they find meaningful. We regard these individuals not as end-users, but as valuable input in the design process. We applied this method when designing novel applications for autonomous embodied agents, e.g. robots. Owners of unusual pets, such as snakes and spiders, were interviewed - not with the intention to design robot pets, but to determine underlying needs and interests of their practice. The results were then used to design a set of applications for more general users, including a dynamic living-room wall and a set of communicating hobby robots

Low-fi skin vision: A case study in rapid prototyping a sensory substitution system

We describe the design process we have used to develop a minimal, twenty vibration motor Tactile Vision Sensory Substitution (TVSS) system which enables blind-folded subjects to successfully track and bat a rolling ball and thereby experience 'skin vision'. We have employed a low-fi rapid prototyping approach to build this system and argue that this methodology is particularly effective for building embedded interactive systems. We support this argument in two ways. First, by drawing on theoretical insights from robotics, a discipline that also has to deal with the challenge of building complex embedded systems that interact with their environments; second, by using the development of our TVSS as a case study: describing the series of prototypes that led to our successful design and highlighting what we learnt at each stage

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed