Phillips Hue Bridge and DuckDB Integration
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Table of Contents
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
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Input and output integration overview
This plugin gathers status from Hue Bridge devices using the CLIP API interface.
This plugin enables Telegraf to write structured metrics into DuckDB using SQLite-compatible SQL connections, supporting lightweight local analytics and offline metric analysis.
Integration details
Phillips Hue Bridge
The Hue Bridge plugin allows users to gather real-time status from Philips Hue Bridge devices utilizing the CLIP API interface. By communicating with Hue Bridges, this plugin is capable of retrieving various metrics related to home lighting and environmental conditions. It offers multiple schemes for accessing the bridges, such as local LAN, cloud, and mDNS, ensuring flexibility in deployment scenarios. The plugin can handle diverse configurations such as room assignments for devices, which optimizes the evaluation of statuses, especially in environments with many devices. Furthermore, it provides various monitoring metrics applicable to lights, temperature sensors, motion sensors, and device power status, thereby enabling comprehensive insights into a smart home setup. The configuration options allow users to tailor their connections to optimize performance and security, including optional TLS configurations for secure communication.
DuckDB
Use the Telegraf SQL plugin to write metrics into a local DuckDB database. DuckDB is an in-process OLAP database designed for efficient analytical queries on columnar data. Although it does not provide a traditional client-server interface, DuckDB can be accessed via SQLite-compatible drivers in embedded mode. This allows Telegraf to store time series metrics in DuckDB using SQL, enabling powerful analytics workflows using familiar SQL syntax, Jupyter notebooks, or integration with data science tools like Python and R. DuckDB’s columnar storage and vectorized execution make it ideal for compact and high-performance metric archives.
Configuration
Phillips Hue Bridge
[[inputs.huebridge]]
## URL of bridges to query in the form ://:@/
## See documentation for available schemes.
bridges = [ "address://:@/" ]
## Manual device to room assignments to apply during status evaluation.
## E.g. for motion sensors which are reported without a room assignment.
# room_assignments = { "Motion sensor 1" = "Living room", "Motion sensor 2" = "Corridor" }
## Timeout for gathering information
# timeout = "10s"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
# tls_key_pwd = "secret"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
</code></pre>
DuckDB
[[outputs.sql]]
## Use the SQLite driver to connect to DuckDB via Go's database/sql
driver = "sqlite3"
## DSN should point to the DuckDB database file
dsn = "file:/var/lib/telegraf/metrics.duckdb"
## SQL INSERT statement with placeholders for metrics
table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"
## Optional: manage connection pooling
# max_open_connections = 1
# max_idle_connections = 1
# conn_max_lifetime = "0s"
## DuckDB does not require TLS or authentication by default
Input and output integration examples
Phillips Hue Bridge
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Automated Lighting Control Based on Room Occupancy: Utilize the Hue Bridge plugin to monitor motion sensors within various rooms of a home. When motion is detected, the system can automatically trigger the lights to turn on, providing convenience and energy efficiency. This integration could significantly enhance user experience and preferences, adapting the lighting to occupancy levels without manual intervention.
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Environmental Monitoring in Smart Homes: Implement the Hue Bridge plugin to track temperature and light levels within the house. By continuously monitoring these metrics, users can create a comfortable indoor climate, adjusting heating and cooling systems based on temperature trends or activating lights based on light levels detected. This data-driven approach leads to smart home automation that responds to actual environmental conditions.
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Integration with Home Automation Systems: Leverage this plugin to integrate Philips Hue Bridge statistics into broader home automation frameworks. For example, collecting light and temperature data can feed into a centralized dashboard that provides homeowners with insights about their energy usage patterns. Environments can be programmed to respond proactively to user habits, promoting efficiency and energy conservation.
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Battery Monitoring for Smart Devices: Use the Hue Bridge plugin to monitor battery levels across various connected smart devices. By being alerted about low battery states, homeowners can take timely actions to replace or recharge devices, preventing outages and ensuring smooth operation of their smart home systems.
DuckDB
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Embedded Metric Warehousing for Notebooks: Write metrics to a local DuckDB file from Telegraf and analyze them in Jupyter notebooks using Python or R. This workflow supports reproducible analytics, ideal for data science experiments or offline troubleshooting.
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Batch Time-Series Processing on the Edge: Use Telegraf with DuckDB on edge devices to log metrics locally in SQL format. The compact storage and fast analytical capabilities of DuckDB make it ideal for batch processing and low-bandwidth environments.
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Exploratory Querying of Historical Metrics: Accumulate system metrics over time in DuckDB and perform exploratory data analysis (EDA) using SQL joins, window functions, and aggregates. This enables insights that go beyond what typical time-series dashboards provide.
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Self-Contained Metric Snapshots: Use DuckDB as a portable metrics archive by shipping
.duckdb
files between systems. Telegraf can collect and store data in this format, and analysts can later load and query it using the DuckDB CLI or integrations with tools like Tableau and Apache Arrow.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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