With CMOS transistor size scaling leakage power consumption becomes an increasing problem for electronics system design. Mobile devices spend most of their time in idle mode. Idle circuit power consumption has high impact on the battery life of these devices, which will limit their applications. Low power design techniques such as power gating and supply voltage scaling were proposed to reduce leakage power. However these techniques introduce noises to a system and makes it more susceptible to errors. There are three important design parameters in an pervasive system: performance, power consumption and reliability. Higher performance enables more sophisticated applications, low power consumption prolongs the battery life and high reliability is a necessary requirement for critical tasks. The aim of this project is to provide low cost and effective circuit design techniques to improve the reliability of low power designs.
Recent advancements in wireless communication and wireless sensor network have opened up significant opportunity in futuristic healthcare and heath monitoring system development. Using sophisticated sensors and the wireless communication infrastructure monitoring a patient on a continuous basis will be feasible in the future. Typically such a system can be viewed as a layered structure consisting of 1) intelligent sensors layer, 2) network layer and 3) service layer. In the first layer a set of sensors (wearable or environmental) are deployed for collecting the vital signs of the patient under monitoring. These collected data are transmitted via the network layer to a central facility. WLAN/cellular/GSM/3G network could be used for serving this purpose. In the service layer the central facility processes these data to check for any abnormality of the received vital sign signals and accordingly the appropriate healthcare service is informed to take immediate action. Although very effective this structure faces the problem of transmission of huge amount of data over the network layer and effective management of the data at the central facility. The quality of transmitted medical data cannot be compromised by any means by using compression techniques since this may lead to false information about the condition of the patient under monitoring. Thus the main research effort has been dedicated to improve the quality and bandwidth in the network layer. Additionally maintenance of the data in the central facility needs intelligent database development.
We envisage that a way out is to add intelligent processing circuitry in the sensor layer itself which can monitor the patientââ¬â¢s vital signs on a continuous basis and only transmit the signal to the central facility when it finds a departure of the vital signââ¬â¢s pattern from the regular pattern. The raw medical data can be stored in a local computer using home wireless infrastructure. This approach reduces the burden on the network layer significantly. If required, the central facility can call for the raw data stored in the home computer over the network layer. However, processing the vital signs on a continuous basis is an extremely challenging problem in signal processing. Although there are several techniques developed for processing these data, they are very much computationally intensive and thus require significant amount of power. But in a wireless sensor network the biggest problem is the power and area. Thus these techniques are not likely to be suitable for embedding the associated circuitry within the sensor layer. To materialise our envisaged system, it is necessary to reduce the complexity of the required signal processing tasks (ââ¬Ålight-weight signal processingââ¬?) and associated architectural optimisation in such a way that each of the processing circuit consumes as small power as possible. In the extreme case we envisage that the circuits may work through energy harvesting.
Keeping this fact in mind we have initiated a research project for development of signal processing algorithms and associated ultra low-power architecture development for separating ââ¬Åaââ¬? vital sign signal from composite of similar kind of signals. This is a typical scenario when environmental sensors are used to monitor a patient who is visited by his/her relatives/friends. In this case the environmental sensor will receive a composite signal of several similar kinds of vital sign signals from which the circuit embedded in the sensor need to separate the only ââ¬Ånecessaryââ¬? signal corresponding to the person under monitoring. Since the person under monitoring can be mobile (within the room) it also needs to track the person on a continuous basis. The main challenge in this case is to find a clever algorithm of reduced complexity and associated ultra low-power architecture development.
We would like to continue this work in this area since this leads to joint algorithm-circuit optimisation which eventually enables us to develop ââ¬Årealââ¬? pervasive healthcare system satisfying the stringent criteria of ââ¬Åpervasivenessââ¬?.
Open Impact is a project to help collect evidence about the impact of research that has been undertaken in UK universities and to provide it to a range of stakeholders (government, funders, press etc) through an independent third party agency (a learned society). The project focuses on a specific discipline (Computer Science) mediated through a particular society (the British Computer Society). In particular, this project will produce software that helps to make institutional repositories effective in collecting evidence of the impact of their institutionsââ¬â¢ research ââ¬â evidence that justifies the investment that government and research funders have made and that promotes the role of Universities in society.
Developments in ePortfolios enable greater power and flexibility in displaying achievements. Current initiatives side-step the problem of inter-institutional certification rather than dealing with it. Although proprietary solutions are starting to appear, they tend to be organisation- rather than user- centric.
This project seeks to address the issue of design for a suitable user-centric "eCertificate" system by working with representatives of the community to establish use case scenarios, to verify this design by building a demonstrator, and then by testing the demonstrator within the group. The demonstrator will be based on a code library which will be developed, and both will be placed in the public domain.
Body Area Wireless Sensor Networks (BAWSNs) have numerous applications. These typically involve the sensing of physiological data in a number of sensor nodes placed at various points on the body, the communication of this data to a central node and the use of intelligence algorithms to make decisions on the basis of the data. The sensor nodes are required to be small and light, preventing the use of bulky batteries. In order to maximise the length of time for which the sensor nodes can operate without requiring recharging, their energy consumption must be minimised. There are two main causes of sensor node energy consumption, namely the processing of data and the transmission of data. Clearly, reducing the amount of data that is processed and transmitted by a node can be reduce the energy consumption. However, there is typically a trade-off between the amount of data that is processed by a node and the amount of data that it transmits. For example, distributed intelligence and compression algorithms can be used to reduce the amount of data that is transmitted by a node, at the cost of increasing the amount of data processing performed. Furthermore, the contributions of sensing, communication and intelligence are inherently linked. For example, distributed intelligence algorithms require the communication of data between the sensor nodes that are involved in making decisions. Therefore this project aims to jointly consider the sensing, communication and intelligence of BAWSNs in order to strike attractive trade-offs between the processing and communication requirements of sensor nodes.
There is demand for Body Area Wireless Sensor Networks (BAWSNs) in which the sensor nodes are small and light, preventing the use of bulky batteries. In order to maximise the length of time that the sensor nodes can operate without being recharged, their energy consumption needs to be minimised. Since the energy consumed when transmitting has a significant contribution to the energy consumption of typical wireless sensor nodes, it is desirable to consider sophisticated error correction schemes, which allow reliable communications to be maintained when the transmission energy per data bit is reduced significantly. However, these error correction schemes are associated with some processing complexity, which consumes energy and erodes the transmission energy savings that are afforded. This project aims to analyse the processing energy consumption associated with sophisticated error correction schemes, allowing the optimal trade-off between processing energy and transmission energy to be found. In this way, the net energy consumption of wireless sensor nodes can be minimised.
Embedded systems based on system-on-chip (SoC) are making their way into more and more devices, from household appliances to hand-held devices, from satellite applications to automobiles, sensors, etc. Since many of these systems are battery powered, power consumption is a prime design issue to extend battery life. Also, to optimize system performance the design of efficient on-chip communication architecture is a crucial design requirement.
An emerging requirement of the current and the future SoCs is the ability to operate in the presence of soft errors caused by radiation. However, addressing the power minimization and reliability improvement simultaneously is difficult because lowering voltage to reduce power consumption has been reported to exponentially increase the number of transient faults or soft errors. Such power reduction also causes degradation of system performance as operating frequency is also reduced. Therefore, with increasing complexity of applications and short time-to-market requirements, the design of low power, efficient and reliable system is a truly challenging task.
The aim of this project is to develop efficient on-chip communication architectures for multiprocessor SoCs and to devise system-level design techniques, which are able to simultaneously meet both low power consumption and reliability requirements. The impact of soft errors on reliability is investigated at application-level rather than at architectural-level. Based on the investigation, novel power minimization technique has been developed meeting a specified acceptable-level reliability and real-time performance for a given soft error rate. Furthermore, the impact of application system tasks mapping on reliability has been studied. Underpinning this study, a novel design optimization technique has been developed to jointly minimize power consumption through voltage scaling and the number of soft errors experienced through application task mapping. The effectiveness of the proposed techniques is evaluated using different applications, including MPEG-2 video decoder and random task graphs.
The EPSRC funded Advanced Knowledge Technologies Interdisciplinary Research Collaboration (AKT IRC) has been a significant success in terms of papers published, grants awarded, students trained, and international impact. The Review Panel rated the project as "outstanding" scoring 34 out of a maximum possible 35 on the seven review criteria used to assess the results of projects by the EPSRC. The purpose of this proposal is to take some of the most important results from AKT and organise a next stage of research. This in turn will serve as a precursor to a longer-term ambition; the establishment of Web Science as a discipline. This initiative we are undertaking with the Web's inventor Professor Sir Tim Berners-Lee and MIT.
The development of new Semantic Web technologies (many developed and researched in the AKT IRC) points to a new generation of Web capability that can explore and query, assemble and integrate content in a context-aware, focused fashion. The basic idea is that we move from a document centric view of the Web to one in which data and information are the principle objects of interest. This data may relate to people, scientific structures, financial transactions or any domain that can be represented on the Web.
With the emergence of a Web of data it is essential to address three key research problems; (1) how to build ontologies quickly that are capable of exploiting the potential of large-scale user participation, (2) how we query an unbounded web of linked data, (3) how to visualise, explore, browse and navigate this mass of data.
The proposal is to undertake fundamental research in the areas 1-3 identified above. This fundamental research is supported via two application domains; one in the area of public sector information, a second in the domain of transport. The application domains will provide the context in which to gather realistic requirements, understand the social aspects that determine the success or otherwise of the systems constructed, test the adequacy of solutions, and showcase the promise of the results obtained in pursuing the research objectives outlined.
The project aim is to produce an open source Windows based screen magnifier that will run from a USB pen drive and work in line with the NonVisual Desktop Access (NVDA) free and open source screen reader for use by visually impaired users.
Although magnification in various forms is available on Windows XP and Vista with complete screen magnification on Windows 7 it is felt that these systems do not offer a portable solution with links to an open source screen reader or such options as:
This project will build on the work of the LATEU funded Access Tools with the accessible USB pen drive menu and inclusion of other free and open source applications.
PicBoard has already been developed as a Windows based application and is used to create and print communication charts. It is a ââ¬Ålow-techââ¬? Alternative and Augmentative Communication (AAC) solution that has many uses, including supporting children with cerebral palsy and adults who have had a stroke. PicBoard has also been installed in several hospitals in Ukraine, for both adult and young clients. The Mulberry Symbols used with Picboard can be found on the Straight Street website.
The original version of PicBoard was written in Borland Delphi (for Windows platforms). Due to the increasing use of many other platforms ( e.g. Linux, Mac, PDA/smartphones), the Paxtoncrafts Charitable Trust now feel the software needs to be rewritten as a web application to reach a wider audience.
While some 'high-tech' solutions exist to help with communication (such as dynamic speech output devices), many clients are not able to use these (for example, many pre-school children with such disabilities), so an interactive web based tool that can support the development of customised speech charts, communication books and wall signs etc can be invaluable to many individuals, families, friends and therapists.
The major benefit of making this AAC solution a web application will also be the collaborative nature of producing charts. Currently, individual efforts are made by therapists at each PC, but this project will allow charts to be stored to a global library for everyone to peruse. The time devoted to producing such charts is very time-consuming and this will become a rich resource for therapists.
This project will use the combined benefits of Open Source and Open Content to bring an important resource to clients who cannot access such communication tools due to cost barriers. JISC OSS Watch will be advising on this aspect of the project.