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A Connected World: System-Level Support Through Biosensors.

Eric S McLamore1,2, Shoumen P A Datta3,4

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Summary
This summary is machine-generated.

Future biosensor design must prioritize societal needs and quality of service. Integrating data science and decision science with sensor science is crucial for developing effective biosensors-as-a-service systems.

Keywords:
biosensordecision supportknowledge networkmeaningful usequality of service

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Area of Science:

  • Biomedical Engineering
  • Health Informatics
  • Systems Science

Background:

  • Biosensors are critical for protecting future generations' health.
  • Systems-level decision support necessitates biosensors providing societal value.
  • Cyber-physical systems and biosensors are increasingly integrated with decision support.

Purpose of the Study:

  • To review recent developments in cyber-physical systems and biosensors for decision support.
  • To identify processes connecting user needs with biosensor engineering via informatics.
  • To advocate for integrating data science and decision science with sensor science.

Main Methods:

  • Literature review of cyber-physical systems and biosensor developments.
  • Analysis of informatics approaches for user needs and biosensor engineering.
  • Identification of key processes for connecting user needs and engineering.

Main Results:

  • Recent advancements link cyber-physical systems and biosensors with decision support.
  • An informatics approach can bridge user needs and biosensor engineering.
  • Formal integration of data science and decision science with sensor science is needed.

Conclusions:

  • Focusing on quality of service early in biosensor design enhances meaningful value.
  • Biosensor development is a cautionary tale influenced by economics of scale.
  • Achieving biosensors-as-a-service requires understanding system complexity and user needs.