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  • The Virtual Sensor Concept - Separating Sensor Software from the Hardware

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    Trevathan447690-Accepted.pdf (1.053Mb)
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    Accepted Manuscript (AM)
    Author(s)
    Trevathan, Jarrod
    Read, Wayne
    Sattar, Abdul
    Schmidtke, Simon
    Sharp, Tony
    Griffith University Author(s)
    Trevathan, Jarrod
    Sattar, Abdul
    Year published
    2020
    Metadata
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    Abstract
    Aquatic environmental sensors are expensive which limits the ability to undertake widescale remote monitoring. In most instances, too much logic and functionality are contained within the sensor device itself. This approach is expensive and computationally restrictive. This paper presents a new architectural paradigm for remotely deployed sensors whereby the calibration logic (and other functionality) is separated from the physical sensor hardware. A sensor device is only responsible for taking raw unprocessed sensor readings, which are transmitted back to a central server. All processing occurs on the server where computational ...
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    Aquatic environmental sensors are expensive which limits the ability to undertake widescale remote monitoring. In most instances, too much logic and functionality are contained within the sensor device itself. This approach is expensive and computationally restrictive. This paper presents a new architectural paradigm for remotely deployed sensors whereby the calibration logic (and other functionality) is separated from the physical sensor hardware. A sensor device is only responsible for taking raw unprocessed sensor readings, which are transmitted back to a central server. All processing occurs on the server where computational capability and sophistication are unbounded. This approach allows for significant flexibility in terms of dynamic calibration adjustments to be applied to sensor data (e.g., in the case of sensor fouling or device decay) and for statistical quality assurance/data production algorithms to be applied. We present an example of how this paradigm can be adopted in this context to a turbidity sensor.
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    Conference Title
    Proceedings of 2020 IEEE SENSORS
    DOI
    https://doi.org/10.1109/SENSORS47125.2020.9278631
    Funder(s)
    ARC
    Grant identifier(s)
    LP190101083�
    Copyright Statement
    © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Artificial intelligence
    Image processing
    Publication URI
    http://hdl.handle.net/10072/401961
    Collection
    • Conference outputs

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