The Smart Refrigerator is designed to enhance a traditional refrigerator using sensors, actuators, and AI technology. Most importantly, it prevents you from completely running out of stock of food by recognizing items that are close to finishing and alerting you in advance. It also provides automatic chilled water refilling, food recognition, and a door monitoring system to ensure optimal performance and user convenience.
- Recognizes foods that are close to finishing using weight measurements.
- Automatic chilled water refilling system.
- Door monitoring system to ensure the door is properly closed.
- Uses an AI model to recognize foods inside the fridge.
- User Friendly dashboard
- NI DAQ mx
- Rasberry Pi 4
- Rigol DP900 Variable DC Power Supply
- Thin Film Pressure Sensor 2Kg
- Magnetic Door Sensor Proximity NO
- Water level Sensor Float switch Small PP
- Ultra-quiet Brushless Motor Submersible Water Pump
- Web Camera
- LabVIEW
- Python
- TensorFlow
The user interface displays the weight of the goods, helping to identify food that is close to finishing. It also notifies the user if the door is not properly closed and allow the user to connect or disconnect the automatic chilled water system.
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The core of the system was developed using LabVIEW to control and monitor the sensors and actuators. The program interfaces with the hardware, ensuring efficient communication and response to real-time data.
- LabVIEW Programming: Developed control systems for the DAQ card, sensors, and automation.
- Machine Learning Model Training: Trained and implemented a model for fruit and vegetable recognition.
- Raspberry Pi Programming: Integrated the image recognition model with Raspberry Pi for real-time use.
- Circuit Design and Sensor Calibration: Assembled circuits and calibrated sensors for data collection and system accuracy.
- Add a mobile app interface to provide real-time updates on fridge contents.
- Integrate a more advanced food spoilage detection system.
- Enhance the weight monitoring system to categorize and track specific food items.
This project is licensed under the MIT License - see the LICENSE file for details.