https://github.com/humairarizwan/iot-project-time-series

An IoT system that can indicate if the current heat index of an environment is healthy. Display a visualization of current relative humidity data and predicted relative humidity
https://github.com/humairarizwan/iot-project-time-series

machine-learning mqtt nodered nodered-dashboard python

Last synced: 4 days ago
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An IoT system that can indicate if the current heat index of an environment is healthy. Display a visualization of current relative humidity data and predicted relative humidity

• Host: GitHub
• URL: https://github.com/humairarizwan/iot-project-time-series
• Owner: HumairaRizwan
• Created: 2024-06-09T16:34:06.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-06-20T11:13:13.000Z (5 months ago)
• Last Synced: 2024-10-17T16:29:13.899Z (21 days ago)
• Topics: machine-learning, mqtt, nodered, nodered-dashboard, python
• Language: Python
• Homepage:
• Size: 38.1 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# IOT-Project

The system: 

- Tower Pro Servo connects with Raspberry Pi and is programmed with Python.

- DHTT22 Digital Temperature Sensor connects to Raspberry Pi with one wire to send temperature data to a terminal and display gauge.

- Red and green LED bulbs connect to Raspberry Pi to indicate high and low temperatures.

- Motor Driver IC connects between Pi and DC Motor for fan control.

- Fan speed automatically adjusts based on temperature changes.

- Fan turns off if temperature drops below 20 degrees Celsius.

- Display gauge shows three different temperature levels (High, Medium, Low).

- MQTT protocol used for message transport between Pi and dashboard.

- Node-Red dashboard displays latest temperature, past data visualization, and temperature prediction

According to the readings of temperature and  humidity sensor, the display gauge will  display the heat index level in four stages.

Implemented MQTT and node red dashboard  to detect current temperature and humidity  reading from sensor; published to MQTT  broker where that data is visualized in display  gauge and line chart.

Implement the Machine Learning model to  forecast the past and future temperature and  humidity and display in Node-RED dashboard.