Stream Real‑Time Temperature Data from a ppDAQC Pi‑Plate to InitialState with a Headless Raspberry Pi

The ppDAQC Pi‑Plate is a versatile data‑acquisition interface that seamlessly connects sensors to a Raspberry Pi. With eight analog and eight digital inputs, it supports up to sixteen independent channels of real‑world data, making it ideal for industrial monitoring, research labs, and DIY projects.

Beyond data collection, the board offers digital and analog outputs, allowing you to control processes based on sensor feedback. In many deployments, however, the most valuable feature is remote monitoring. Thanks to the Raspberry Pi’s compact size, low power consumption, and Wi‑Fi capability, you can operate it “headless” – without a keyboard or monitor – in remote locations such as storage closets, greenhouses, or industrial facilities.

When it comes to visualizing this data, you have several options:

1. Display raw readings in a terminal – functional but not very engaging.
2. Write data to a local file and later analyze it with spreadsheets or matplotlib – thorough but time‑consuming.
3. Stream the data to the cloud in real time and view dynamic dashboards – the most efficient and user‑friendly approach.

This article demonstrates option 3 by streaming temperature readings from two DS18B20 sensors to InitialState, then viewing live graphs of the ambient room temperature and a refrigerated chamber used for solder paste.

Step 1: What You’ll Need

Software

1. InitialState account – Sign up at InitialState.com and await approval.

2. Python library – Install the ISStreamer module with pip. From a terminal run:
sudo pip install ISStreamer

Hardware

• Raspberry Pi (any model with Wi‑Fi, preloaded with the ppDAQC Python module).
• ppDAQC board from Pi‑Plates.com.
• Two DS18B20 digital temperature sensors (Amazon, Digi‑Key, etc.).
• Two 4.7 kΩ pull‑up resistors (or two 10 kΩ in parallel if 4.7 kΩ are unavailable).
• Hookup wire and a breadboard or ppPROTO for a semi‑permanent setup.

Step 2: Build the Circuit

Connect each DS18B20 sensor to the ppDAQC board following the diagram below. Use the 4.7 kΩ pull‑up resistor on the data line to the 3.3 V supply. If you use 10 kΩ resistors, connect them in parallel to approximate 5 kΩ.

Software Setup

Create a new Logging Client Key in your InitialState dashboard. Then write the following Python script on your Pi. Save it as tempLOG.py in your home directory.

import time
from piplates import ppDAQC
from ISStreamer.Streamer import Streamer

# Replace with your own Client Key
client_key = "YOUR_CLIENT_KEY_HERE"

# Create a stream to InitialState
stream = Streamer(client_key)

while True:
    # Read temperatures from DS18B20 sensors
    ambient = ppDAQC.getTEMP(1)  # Channel 1
    cooler = ppDAQC.getTEMP(2)   # Channel 2

    # Log the readings
    stream.pushData("Ambient", ambient)
    stream.pushData("Cooler", cooler)

    # Wait 5 minutes before next reading
    time.sleep(300)

Run the script with:
sudo python tempLOG.py – verify that it starts without errors.

Step 3: View Your Data in InitialState

After a few hours of logging, log in to your InitialState account. Navigate to your project’s page and open the log file titled “Lab Temperature Data.” Click the Source button to view raw entries, which will look similar to:

DateTime,SignalSource,OriginalPayload
2014-12-18T15:50:57.837852Z,"Lab Temperature Data","Stream Starting"
2014-12-18T15:50:58.841351Z,Cooler,37.6
2014-12-18T15:50:59.844371Z,Ambient,69.55
2014-12-18T15:56:00.947597Z,Cooler,36.5875
2014-12-18T15:56:01.950743Z,Ambient,68.7625

Use the built‑in graphing tools to create real‑time charts for the Ambient and Cooler readings, and set up alerts or export the data for further analysis.

By combining the ppDAQC Pi‑Plate, a headless Raspberry Pi, and InitialState, you achieve a lightweight, scalable, and secure sensor‑data pipeline that delivers actionable insights straight to your dashboard.