About This System

Learn about the camera trap monitoring system, its components, and how it works to capture wildlife activity while maintaining autonomous operation.

System Overview

This camera trap monitoring system automatically captures wildlife images using an ESP32-based camera module. The system is designed for long-term outdoor deployment and provides comprehensive monitoring of both wildlife activity and device performance.

The system combines hardware sensing with web-based monitoring to create a complete solution for wildlife observation and research.

Key Features

Automated Image Capture

Photos are taken at regular intervals with precise timestamps. Each image is automatically named with the capture date and time for easy organization and analysis.

Battery Monitoring

Real-time tracking of power levels and system health ensures reliable operation. Battery data is logged continuously and visualized through interactive charts.

Data Logging

All measurements are stored in a local SQLite database for historical analysis. The system maintains detailed records of battery levels, timestamps, and system events.

Web Interface

Easy access to images and system status through this responsive website. View recent captures, browse historical data, and monitor system health remotely.

Date-Based Organization

Images are automatically organized by capture date, making it easy to browse through large volumes of wildlife photos and track activity patterns over time.

Performance Analytics

Daily and weekly battery trend visualizations help monitor device performance and plan maintenance activities to ensure continuous operation.

Technical Implementation

Hardware Components

Software Architecture

File Naming Convention

Images follow a standardized naming pattern: cam_01_image_YYYYMMDD_HHMMSS.jpg

This convention enables automatic sorting, easy identification, and efficient organization of captured images. The timestamp is embedded directly in the filename for reliable chronological ordering.

System Data Flow

  1. Image Capture: Camera trap device captures images at scheduled intervals
  2. Data Collection: Battery voltage and system metrics are recorded
  3. Storage: Images are saved to the file system with timestamped names
  4. Database Logging: Sensor data is stored in SQLite database with timestamps
  5. Visualization: Python scripts generate SVG charts from database data
  6. Web Serving: Caddy web server provides access to images and status data
  7. User Interface: Web interface displays latest images and system status

System Directory Structure

/home/kris/Project/www_camtrap/
├── index.html              # Main dashboard page
├── gallery.html            # Image browsing interface  
├── about.html              # System documentation
├── camtrap-style.css       # Website styling
├── plot_camtrap_data.py    # Data visualization script
├── battery_status.json     # Real-time battery data
├── camtrap_01_data.db      # SQLite measurement database
├── images/                 # Camera trap image storage
├── static/                 # Web assets (favicons, etc.)
├── last_24_hours.svg       # 24-hour battery chart
└── last_week.svg           # Weekly battery trend chart
            

System Maintenance

Regular maintenance ensures optimal system performance and continuous data collection:

System Information

Database Records

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Total Measurements

Image Collection

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Total Images Captured

System Uptime

Active
Operational Status