https://github.com/somdipdey/smartnoshwaste
Supplementary data/documents of SmartNoshWaste: Using Blockchain, Machine Learning, Cloud Computing and QR Code to Reduce Food Waste in Decentralized Web 3.0 Enabled Smart Cities
https://github.com/somdipdey/smartnoshwaste
Last synced: 8 months ago
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Supplementary data/documents of SmartNoshWaste: Using Blockchain, Machine Learning, Cloud Computing and QR Code to Reduce Food Waste in Decentralized Web 3.0 Enabled Smart Cities
- Host: GitHub
- URL: https://github.com/somdipdey/smartnoshwaste
- Owner: somdipdey
- License: mit
- Created: 2022-02-13T17:38:52.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-02-14T15:18:18.000Z (almost 4 years ago)
- Last Synced: 2025-02-15T10:31:24.423Z (9 months ago)
- Language: Python
- Size: 61.5 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://github.com/somdipdey/SmartNoshWaste/blob/main/LICENSE)
# SmartNoshWaste: Using Blockchain, Machine Learning, Cloud Computing and QR Code to Reduce Food Waste in Decentralized Web 3.0 Enabled Smart Cities
Blockchain and QR code generation program for the paper, "SmartNoshWaste: Using Blockchain, Machine Learning, Cloud Computing and QR Code to Reduce Food Waste in Decentralized Web 3.0 Enabled Smart Cities"
## Paper citation
*Dey, Somdip, Suman Saha, Amit K. Singh, and Klaus McDonald-Maier. 2022. "SmartNoshWaste: Using Blockchain, Machine Learning, Cloud Computing and QR Code to Reduce Food Waste in Decentralized Web 3.0 Enabled Smart Cities" Smart Cities 5, no. 1: 162-176. https://doi.org/10.3390/smartcities5010011*
## Installation
```
pip install -r requirements.txt
```
## Running the program
Execute blockchain.py file to generate blockchain and QR code embedded data. Run the following command for this.
```
python blockchain.py
```
To decode the QR code execute the decode.py file. Run the following command for this.
```
python decode.py
```
## Data for the paper
Data/results from the nosh app, which is used in the experimental section, is provided in data.xlsx file.