Home > Press > iPower, a systematic approach to design system architectures with power, area and cost in mind from day one
The route from application specifications to optimized system design: the use of iPower in the healthcare domain for arrhytmia patient monitoring. The application specifications enable power, volume and cost diagnosis and optimization. |
Abstract:
mec and Holst Centre present a powerful method called iPower that allows designing system architectures with optimized power consumption, area and cost. Truly optimized performances are achieved by combining know-how on energy harvesting, low-power electronics and application-level optimization techniques. The method can be used by system designers in application domains such as healthcare, automotive and smart buildings.
With iPower, a system architecture can be designed while taking into account power, area and cost from day one. This is useful for designing today's autonomous systems in domains like healthcare, e.g. heart and brain monitoring systems; automotive, e.g. engine monitoring and intelligent tires; and smart buildings, e.g. smart metering and lighting control. Applications like these become more complex, demand more power and at the same time must be as small and low-cost as possible.
The iPower method starts from application specifications such as system area and cost, radio transmission time periods and analog-to-digital converter sampling intervals. Based on these parameters, system power, area and cost diagnosis and optimization are carried out. The output is a selection of components that form the most optimum system. Design and testing of the optimized system may be performed to validate and improve the method's accuracy. The obtained information can be used to continuously steer the research and development cycle.
Key step in the design flow is the power, area and cost optimization. This step is illustrated in the healthcare domain for arrhytmia patient monitoring. The electronics dimensions and price are taken as input for the area and cost estimation; the application conditions for energy harvesting and electronics are the inputs for the power consumption optimization. For these input parameters, iPower then selects the lowest in power consumption components from an existing database and the power modes for each electronic component, e.g. radio, microcontroller..., so that the overall power consumption at the architectural level is minimized. This way, the power consumption of the initial arrhytmia monitoring system could be significantly reduced.
iPower combines over five years of research experience in energy harvesting and low-power electronics design with effective modeling techniques at component and architectural levels. Future work will focus on extending the applicability of the developed method towards new system architectures and application domains. In addition, more power consumption/generation, volume and cost reduction optimization techniques at architectural level will be considered.
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Barbara Kalkis
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