https://github.com/legitcoconut/teed-ts
The Touchless Entry-Exit Data Tracking System (TEED-TS) is a hygienic, non-contact solution designed to monitor entry and exit movements.
https://github.com/legitcoconut/teed-ts
arduino data-tracking datamonitor esp32 esp8266 python sensor statistics
Last synced: about 1 year ago
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The Touchless Entry-Exit Data Tracking System (TEED-TS) is a hygienic, non-contact solution designed to monitor entry and exit movements.
- Host: GitHub
- URL: https://github.com/legitcoconut/teed-ts
- Owner: LegitCoconut
- Created: 2024-12-16T19:27:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-26T10:53:52.000Z (over 1 year ago)
- Last Synced: 2025-04-14T02:56:49.727Z (about 1 year ago)
- Topics: arduino, data-tracking, datamonitor, esp32, esp8266, python, sensor, statistics
- Language: Python
- Homepage:
- Size: 446 KB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🚪 Touchless Entry-Exit Data Tracking System (TEED-TS)
## 📖 Overview
The **Touchless Entry-Exit Data Tracking System (TEED-TS)** is a hygienic, non-contact solution designed to monitor entry and exit movements. It uses **Infrared (IR) sensors**, the **ESP8266 microcontroller**, and **IoT technologies** to provide real-time data tracking while reducing physical contact.
Collected data is visualized through dynamic graphs and stored in CSV format, making it suitable for environments requiring reliable monitoring, such as:
- 🏥 Hospitals
- 🏢 Offices
- 🛒 Retail Spaces
- 🛡️ Security Zones
---
## ✨ Features
- **Touchless Monitoring**: Tracks entry/exit movements using IR sensors.
- **Real-Time Visualization**: Displays real-time entry/exit counts via animated bar graphs.
- **Data Logging**: Saves timestamped data in CSV format for analysis.
- **Hygienic and Efficient**: Reduces human contact and contamination risk.
- **Scalable**: Can integrate with larger networks or more complex setups.
---
## 🛠️ Components
### 🔩 Hardware
| Component | Quantity | Description |
|----------------|----------|------------------------------------------|
| **IR Sensors** | 4 | Detect interruptions in infrared beams. |
| **ESP8266** | 1 | Microcontroller for data processing. |
| **Breadboard** | 1 | For prototyping the circuit. |
| **Jumper Wires** | Set | Connect components to the circuit. |
### 💻 Software
1. **Arduino IDE**: For programming the ESP8266 microcontroller.
2. **Python**: For data processing and visualization.
- Libraries used:
- `csv`: Handles data logging.
- `time` & `datetime`: For timestamps.
- `matplotlib`: For creating animated bar graphs.
- `serial`: For serial communication with the ESP8266.
---
## 🚀 How It Works
1. **Initialization**:
- The ESP8266 connects to Wi-Fi to sync the current time from an NTP server.
2. **Detection**:
- IR sensors monitor movements by detecting interruptions in their beams.
3. **Data Processing**:
- The ESP8266 categorizes events as **entry** or **exit** and sends the data to a laptop.
- Timestamped data is logged in a CSV file.
4. **Visualization**:
- Real-time bar graphs show ongoing entry/exit counts.
- Interval-based graphs provide insights every 5 minutes.
---
## 📊 Results
| **Metric** | **Performance** |
|---------------------------|-----------------------------------|
| **Accuracy** | ~95% in controlled environments. |
| **Sensor Response Time** | 0.5 seconds (average). |
| **Uptime** | 100% (during testing). |
| **Test Period Data** | 98 entries, 96 exits (24 hours). |
---
## 🔧 Setup Instructions
### Hardware
1. Connect IR sensors to the ESP8266 microcontroller.
2. Use jumper wires and a breadboard for prototyping.
3. Power the ESP8266 and ensure proper wiring.
### Software
1. Install **Arduino IDE** and upload the provided client-side code to the ESP8266.
2. Install Python (3.x) and required libraries using:
```bash
pip install matplotlib pyserial
```
A practical, precise, and scalable solution for monitoring movements in real-time. This system prioritizes hygiene, efficiency, and data visualization, making it suitable for a variety of environments, including healthcare, retail, and public spaces.
## 🛠️ Future Improvements
- **Replace wired communication with Wi-Fi-based communication**: Enhance connectivity and reduce dependency on physical wiring.
- **Integrate AI analytics**: Analyze movement trends and predict patterns for smarter decision-making.
- **Improve sensor calibration**: Mitigate interference caused by environmental factors to enhance accuracy.
## 🏆 Key Benefits
- **Hygienic**: Reduces contact in sensitive environments.
- **Real-Time Insights**: Provides live tracking for better monitoring.
- **Scalable**: Adaptable to various use cases, including large-scale deployments.
## 🖼️ Visualization Example
*Include your data visualization example here (e.g., graphs, charts, or images demonstrating real-time tracking).*
## 📚 References
- [Arduino People Counter](#)
- [Assessing the ESP8266 Wi-Fi Module](#)
- [A Smart Bidirectional Visitor Counter](#)
## 💡 Conclusion
The **Touchless Entry-Exit Data Tracking System (TEED-TS)** is designed for environments where hygiene, precision, and efficiency are paramount. Its features and future enhancements ensure adaptability for applications in various sectors, including:
- Healthcare
- Retail
- Public spaces
---
### 🚀 How to Run the Python Script
1. Clone this repository:
```bash
git clone https://github.com/your-repo-name.git
cd your-repo-name
```
2. Install required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Python script to process and visualize data:
```bash
python script_name.py
```
---
### 🔧 System Requirements
- Python 3.7+
- Arduino IDE (for microcontroller programming)
- ESP8266 Wi-Fi Module or equivalent
- Sensor hardware
---
Feel free to contribute by submitting pull requests or issues!
## Screenshots
.
## Support
For support, email labzmad44@gmail.com .