This project is based on the real life implications of the Internet of Things (IoT). Here we have built a temperature monitoring system using the Bolt Wifi Module. The temperature is monitored using a LM35 sensor, which is connected to the module and the setup is such that it detects the temperature, looks for anomalies and predicts data using machine learning and sends alerts using the Mailgun API whenever an anomaly is detected. This helps the user to monitor any temperature based machine continuously and detect and predict any anomaly.
HARDWARE REQUIRED:- The Bolt WiFi module
- 3 female to male wires
- Temperature Sensor: LM35 sensor
- 5V Cable of DC adapter
Hold the sensor in a manner such that you can read LM35 written on it.
1. Set up the connections as required using the Bolt WiFi module, a temperature sensor and a set of male to female connecting wires as shown below.
2. Connect this module to the system and set it up in the Bolt website.
3. Configure the device and set up hardware settings.
4. Type the program required to run the polynomial regression algorithm on the data sent by the Bolt
5. Save the code and ensure that the connected device is online.
6. Place the system inside the fridge and close the door but ensure the connection continues.
7. Open PuTTy and type the code for the credentials for email details, API key device ID etc.
8. Type the code for the program as follows.
9. Implement the code to obtain output.
10. Check the obtained graph in the Bolt website.
11. It was coded in the program to send alert (email) when an anomaly is detected. Below is the screenshot of the alert received in the mail inbox.
Thank you.







Comments