Our Project focuses on Object detection using Computer Vision and Load cells. The Fridge will detect the Human coming and will activate the process of detection. It will recognize the Item in the Human?s hand using computer vision and will add it to the inventory list. Currently we are working on tw
Implementation of innovative item management process and recognition of edible food in a fridge using computer vision and iot.
Our Project focuses on Object detection using Computer Vision and Load cells. The Fridge will detect the Human coming and will activate the process of detection. It will recognize the Item in the Human’s hand using computer vision and will add it to the inventory list. Currently we are working on two items from each food category, we will train our model to detect those two items and add them to the inventory list. In order to remove something, load cells will be used to detect the change in weight. The weight will be checked with the previous weight. Whichever item will be equals to the weight reduced will be notified to the User as the item removed.
User will be notified in either cases via Voice and Android Application
1) To research and study about Object recognition using Computer vision and Artificial Intelligence.
2) To study different Algorithms used for computer vision, in order to find the most optimized one for object recognition.
3) To develop such a System which can automate the process of Inventory management and recipe management.
4) To research and find best platform for Native Mobile App development for IoT Applications
We propose a Smart Fridge that will work on the principle of Computer Vision. The detailed Methodology of this project will be:
1) Object Detection Using Computer Vision: We will be using Computer Vision to detect the item added to the fridge. The camera will first detect if the user is coming toward the fridge or not. If the user is coming towards the fridge, it will activate the process. The camera will take the image of the Item and send it to the web server. The image will be resized and sent to cloud for object detection. The Algorithm will return the labels like Category and Sub-Category. For example, if the added item was Apple, the label will return Fruit, Apple. In this way we can the user will be aware of what is added to what section of the fridge.
2) User Notification through Internet of Things: User will be notified through Voice, whenever something is added or removed. For example, if the Apple is added, the User will be notified through Voice like that, “Apple is added to the Fruits Section.” Furthermore, the User will be notified through Android Application. The app will contain the list of Inventory, which will be uploaded on the Google Firebase, the app will contain some options to personalize the fridge as well as Nutritional Information and Shopping lists.
The scope of this project is to develop a smart fridge which will be able to detect inventory using Computer Vision Algorithms. A smart fridge can be used in various applications in Household management such as keeping track of inventory, getting health information, finding recipes, finding food expiry in order to reduce food wastage. The increasing demand in Smart Home appliances has opened the doors of more capable Smart fridges without much of the manual training.
The final delivery will be a Frdige capable of detection of different kind of fruits and vegetables, using Computer Vision and IoT. The user will be able to add an item to smart fridge, the smart fridge will detect the item and send the details to the user via Android Application. So, our Final delivery will also contain an Android Application.
The fridge will contain camera, Arduino (for processing) and load cells for weight and other features. All these are final deliverables.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Camera | Equipment | 2 | 2000 | 4000 |
| Raspberry Pi | Equipment | 1 | 10000 | 10000 |
| Load Cells | Equipment | 1 | 1000 | 1000 |
| Fridge | Equipment | 1 | 7000 | 7000 |
| Miscellaneous | Miscellaneous | 1 | 5000 | 5000 |
| Total in (Rs) | 27000 |
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