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Sensory Ecology

Data, Networks, and the Biological World

  • Welcome!
  • Syllabus
  • Class Schedule
  • Assignments
    • Midterm
    • Hyperlocal Sensing
    • Data potluck
    • Ambient Recordings
    • Build an API
    • Final project
  • Inspirations
  • Resources

Ambient Recordings (Cataland, Jason)

SPREADSHEET OF COPIED SERIAL MONITOR DATA: ECODATA

My original setup was a simple Arduino board with a photocell receptor to capture the amount of light that entered into my apartment. It would print out a value int eh serial monitor based on how much light was being captured by the photocell. The data ranged from 1-1023. All of my values within the twenty minute range with readings very 20 seconds were in the 500s which meant a moderate/normal amount of light. While this did collect environmental data, it did not exactly match the type/application of data I wanted to learn more about. While there could have been an error in the setup, I still did not suspect a huge fluctuation based on my qualitative observations.

This setup was also not portable for the long run, so I began to brainstorm other ideas of how I can continue to collect more environmental data that could be more applicable to my interest. I began trying to sense and capture audio within the subway system. After researching multiple ways of best practice, I found an Arduino part that I wanted to utilize. I ordered this part and wanted to find a temporary solution until then. I found an app Decibel X that was able to register and collect sound decibels/data. I collected data from a wide range of stations (Columbus Circle/50th Street, Broadway-Lafayette, West 4th). I found the data to be interesting but not a consistent output that something like a serial monitor could grant me. I was not able to easily monitor change overtime but it was a good starting point.

My original photocell data was important for the utilization of bringing in the Arduino board and corresponding light information. Arduino board/physical computing have never been my strong suit, but I knew I could still collect more meaningful data. While the light data was a good introduction point, I was skeptical about the legitimacy and applicability of it. I was more excited and intrigued by the train decibel data. Once I am able to utilize the audio component for Arduino, I am hoping to get a more continuous register of decibel data within my serial port.

My upcoming goals would be to be able to get a functioning audio capturing Arduino board as well as being able to have some visualization of it. For the midterm project, I want to have the Arduino board register sound decibels and if it reaches too high a level, it will output some warning.

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