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Overview

This project builds a complete indoor climate monitoring pipeline for the TP-Link Tapo T315 sensor. Sensor readings are written in real time to a CrateDB time-series database, then visualized through a configurable Apache Superset dashboard. The entire stack is packaged as Docker Compose and optimized for one-command deployment to a Synology NAS, making it suitable for long-term home or lab monitoring.

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Tech Stack

  • Language: Python
  • Sensor: TP-Link Tapo T315 (temperature and humidity)
  • Database: CrateDB (time-series optimized)
  • Visualization: Apache Superset
  • Deployment: Docker Compose, Synology NAS

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Key Features

  • Automatic polling of Tapo T315 sensors with direct write to CrateDB
  • Configurable data retention policy to manage storage growth
  • Superset dashboard for temperature and humidity trend analysis
  • Docker Compose packaging with an .env.example template
  • Deployment flow optimized for Synology NAS (DSM Docker)
  • Automatic service restart on failure (restart: unless-stopped)

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Deployment Architecture

climate-monitor/
├── docker-compose.yml    # Main orchestration file
├── .env.example          # Environment variable template
├── collector/            # Python data collection service
│   └── main.py
└── superset/             # Superset configuration
    └── superset_config.py

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GitHub

Source code: github.com/felimet/climate-monitor