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A Codesign Framework for the Development of Next Generation Wearable Computing Systems.

Francesco Porreca1, Fabio Frustaci1, Raffaele Gravina1

  • 1Department of Computer, Electronics, Modeling and Systems Engineering, University of Calabria, 87036 Rende, Italy.

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Summary
This summary is machine-generated.

This study introduces a new framework for developing green and smart wearable devices using Field Programmable Gate Arrays (FPGAs) and Microcontroller Units (MCUs). The framework optimizes performance and power efficiency for complex, on-device data processing.

Keywords:
FPGAHW/SW codesign frameworkIoTgreen electronicswearable computing system

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Area of Science:

  • Computer Engineering
  • Electrical Engineering
  • Wearable Technology

Background:

  • Wearable devices utilize diverse hardware platforms like ASICs, GPUs, DSPs, MCUs, and FPGAs, each presenting trade-offs in efficiency, flexibility, and power consumption.
  • Optimizing hardware for complex algorithms in far-edge computing within wearables is crucial for performance and battery life.
  • The integration of Field Programmable Gate Arrays (FPGAs) and Microcontroller Units (MCUs) offers a promising balance of computational power and energy efficiency.

Purpose of the Study:

  • To develop a versatile software development framework specifically designed for mixed FPGA/MCU platforms in wearable systems.
  • To enable efficient development of complex algorithms for far-edge computing in resource-constrained wearable devices.
  • To promote the creation of green electronics by enhancing power efficiency and extending battery life in wearables.

Main Methods:

  • A novel framework was conceptualized and developed, analogous to existing software development frameworks but tailored for heterogeneous FPGA/MCU architectures.
  • The framework's efficacy was validated using a practical, real-world application scenario within a wearable system.
  • Performance metrics, including execution speed and power consumption, were rigorously evaluated.

Main Results:

  • The developed framework demonstrated significant enhancements in execution speed compared to conventional approaches.
  • A notable reduction in power consumption was achieved, contributing to improved energy efficiency.
  • The validation confirmed the framework's capability to support complex algorithms in far-edge computing environments.

Conclusions:

  • The proposed framework effectively addresses the challenges of developing sophisticated wearable systems on mixed FPGA/MCU platforms.
  • This approach facilitates the creation of smart, green wearable electronics with extended operational longevity.
  • The framework represents a significant advancement in optimizing performance and power efficiency for on-device processing in wearables.