Open questions will appear on this page for discussion.  After consensus is reached (or after a long time with no discussion), the question will be moved to the resolved category along with its discussion.

Open Questions:

NQ2013-10-29a: How much environmental sensing can be achieved by leveraging the camera on the smartphone?

Resolved Questions:

5 comments on “Sensors
  1. Mike Godin says:

    For oceanographic instrumentation, one standard I am aware of is the Open Geospatial Consortium (OGC) Puck Protocol Standard (see It appears to have been adopted by at least four manufacturers (see, although none of them are offering sub-$250 sensors right now.

  2. Bob Allen says:

    Speaking of instrumentation packages, are there any “industry standards” (accepted/emerging/defacto/etc) for their interfaces (physical/electrical/data format/etc). If yes, can someone provide a URL(s), even if it’s only in a limited context.

    Perhaps even better would be a list of candidates/recommendations for pre-existing instruments that fit the design target (e.g. <$250) as these may influence some physical interface design choices. Thinking only in terms of minimizing the reinventing the wheel where/if it makes sense.

    For example, after seeing Backscatter/Turbidity on the requirements list I went looking for material on various ways of doing same and came up with these on Coastal Wiki:

  3. Mike Godin says:

    Agree, which is why the Sensing Goals list is so short. Aside from basic capabilities that come with any smartphone, the list only includes depth sensing and optical backscatter/turbidity, both of which are relatively simple to implement. Temperature and conductivity sensing would probably represent the next threshold of difficulty to implement, but believe these can be designed to work well with less than US$250 in parts.

  4. James Bellingham says:

    If the goal is making a science vehicle, I think the most challenging part of this will be the sensors (other than a camera). Although most AUVs are expensive, it is also true that core vehicle costs tends to be less than science payload costs. So creating a set of low cost sensors is key to making a scientifically useful system.

    Perhaps the exception is a camera (e.g. GoPro) but although camera imagery is easy to acquire, it is much harder to turn into scientifically useful data. So a camera shifts the costs to post processing.

    Having said that, an engineering testbed does not need particularly high cost sensors, so maybe that is the direction to go.

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