Assignment
Capstone Final Project
This is the capstone project to summarize all the learnings in the 3 modules of the course and to give you practical hands-on experience by working on a major project using Bolt IOT module.
Problem Statement: In the capstone project for the IoT training, we require you to build a proof of concept of the lighting system of a refrigerator which uses data from the Light Dependent Resistor (LDR) and a push button as well as features of the Bolt IoT cloud. You need to use the light intensity and button state to collect light intensity and button data to decide the state of the fridge: a) Door open: Bright and button released b) Door closed: Dark and button pressed c) Door half open: Dim and button released In your code, send an e-mail with the current state of the door when the state changes. Additionally, irritate the user once every 10 seconds if the door is open (state a and c). Additionally, you should set the intensity of a single indicator LED which clearly indicates the above three states.
Components:
- IoT module
- LDR
- Push Button
- Resistors(10k,10k)
- Breadboard
API's used: MailGun Email API, Bolt Cloud API, Pyhon Library
Anomaly Detection: Using Machine Learning
For the Anomaly detection, I prepared a dataset sensorvalues.csv where I saved LDR sensor readings and door states according to problem description. I used Decision trees algorithm for prediction of door state depends on real-time LDR values. I've been using Scikit Learn library for couple of years for most Machine Learning algorithms and it was doing great. So I decided to use sklearn in this project. Here is the code for machine learning prediction of refrigerator door state using Decision trees.
Here is the shematics
It sends Emails when the state of the Door changes
Visit below link for detail story on HacksterIO https://www.hackster.io/harsha-manoj/intelligent-refrigerator-736b24
ThankYou!