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Week 4

November 22, 2022​

  1. Discard the first reading in both timeseries and FFT data.
  2. Write Liquid FFT to grafana. Put FFT in Node in hold.
    1. use the time of data RX for all entries corresponding to the measurement.
    2. Refine the current_timeseries table based on the new refactor.
    3. Create a table for Liquid FFT for the latest measurement.
    4. Create a widget in grafana for displaying FFT data from the step above.
    5. Deployment of Grafana in another environment.
  3. Setting up TDEngine tables with code itself.
  4. Insert BME and other sensor data into TDEngine.

November 23, 2022​

  1. Issue with multiple sockets servers getting data.
  2. Reset the root node if the socket connection fails.

November 25, 2022​

  1. Discuss ESP32 code optimization methods (link)

  2. discard the first ten measurements in LIS3DH and IIS3DWB.

  3. Collimator: Graph the output of matlab vs collimator to compare.

  4. Collimator: Post data from Collimator to TDEngine cloud. We can explore the following approaches.

    1. Connecting data

      • Use CSV files directly from the Grafana CSV plugin

        • Gave me an error in reading the CSVs locally and URL from the same files uploaded to Google drive. Used a small test csv file and got a similar error just for a different line. Will have to look further into this issue. csv error image

      • Send data to TDEngine cloud and connect grafana to TDEngine cloud.

      • Next: Send data from collimator simulation iteself to send data to TDEngine cloud via RESTful API from a python block.

    2. Designing the dashboard

      • Time column in the CSVs can be converted into timestamps. Then grafana feature to select the time range can be used to select the portion of the graph to display.
      • A dropdown to select which attribute to display in matlab-collimator comparison. (same learnings can be utilized in displaying multiple nodes in the IoT dashboard)

November 28, 2022​

  1. Creating Collimator vs. matlab comparison graph using TDEngine cloud and Grafana cloud.
  2. Show BME280 and temperature data in grafana.
  3. Explore TDEngine cloud and grafana cloud so the dashboard will be running in cloud.
  4. Format Raspberry Pi with ubuntu to replace the ubuntu laptop
  5. Insert current FFT data into TDEngine.

November 29, 2022​

  1. Created Grafana cloud dashboard for sensor mesh using TDEngien cloud tables.

November 30, 2022​

Sudhir, Ranjit​

  1. Moving forward with TDEngine cloud and Grafana cloud.

    1. TDEngine cloud plan info: https://cloud.tdengine.com/login
    2. Grafana cloud plan info: https://grafana.com/pricing/
      1. Free tier seems to allow upto 3 free users.
      2. Pro tier $8/user/month. Sudhir suggested use of a single account gqc@gqc.com and the credentials will be shared.

  2. Commit linux_DSP_app code to github.

  3. Finish Mesh to send sensor data + Socket server in C + TDEngine + FFT

  • Send sensor data
  • Socket server in C
  • TDEngine database
  • FFT application
  1. TDEngine timeseries tables should handle both 1024 and 2048 sized data. << Sample size will be constant for single deployment >>
Last updated on by Pavan