https://github.com/attmhd/ecosense
https://github.com/attmhd/ecosense
arduino-ide dht11 dnn fastapi streamlit
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/attmhd/ecosense
- Owner: attmhd
- Created: 2025-01-14T02:54:24.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-26T01:32:54.000Z (over 1 year ago)
- Last Synced: 2025-08-03T19:35:58.873Z (11 months ago)
- Topics: arduino-ide, dht11, dnn, fastapi, streamlit
- Language: Python
- Homepage:
- Size: 2.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Ecosense
This project is final project for Embedded System Course called Ecosense for monitoring temperature and humidity and some prediction.
## Tech Stack
[](https://skillicons.dev)
## Authors
- [@attmhd](https://github.com/attnmhd/)
## Prerequisites
Before you begin, make sure you have Python 3.12 > on your local machine.
## Installation
Follow these steps to get the project running on your local machine.
### Step 1: Clone the Repository
Clone the project repository to your local machine:
```bash
git clone https://github.com/attmhd/ecosense.git
cd ecosense
```
### Step 2: Setup Environment Variables
Create a **.env** file in the root of your project directory and add the following database configuration:
```env
DB_HOST=your_host
DB_USER=your_database_user
DB_PASSWORD=your_database_password
DB_NAME=your_database_name
```
### Step 3: Create Virtual Environment
```bash
python3 -m venv venv
source venv/bin/activate
```
### Step 4: Install Dependencies
```bash
go pip install -r requirements.txt
```
### Step 5: Training Model
```bash
./training.sh
```
### Step 6: Running the Application
Run Server
```bash
uvicorn server:app --host {your_host} --port {your_port}
```
Run Streamlit
```bash
streamlit run dashboard/main.py
```