Phillips Hue Bridge and Redis Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
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.
See Ways to Get Started
Input and output integration overview
This plugin gathers status from Hue Bridge devices using the CLIP API interface.
The Redis plugin enables users to send metrics collected by Telegraf directly to Redis. This integration is ideal for applications that require robust time series data storage and 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.
Redis
The Redis Telegraf plugin is designed for writing metrics to RedisTimeSeries, a specialized Redis database module for time series data. This plugin facilitates the integration of Telegraf with RedisTimeSeries, allowing for the efficient storage and retrieval of timestamped data. With RedisTimeSeries, users can take advantage of enhanced capabilities for managing time series data, including aggregated views and range queries. The plugin offers various configuration options to enable the flexibility needed to connect securely to your Redis database, including support for Authentication, Timeouts, data type conversions, and TLS configurations. The underlying technology leverages Redis’ efficiency and scalability, making it an excellent choice for high-volume metric environments, where real-time processing is essential.
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>
Redis
[[outputs.redistimeseries]]
## The address of the RedisTimeSeries server.
address = "127.0.0.1:6379"
## Redis ACL credentials
# username = ""
# password = ""
# database = 0
## Timeout for operations such as ping or sending metrics
# timeout = "10s"
## Enable attempt to convert string fields to numeric values
## If "false" or in case the string value cannot be converted the string
## field will be dropped.
# convert_string_fields = true
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
# insecure_skip_verify = false
Input and output integration examples
Phillips Hue Bridge
-
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.
-
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.
-
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.
-
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.
Redis
-
Monitoring IoT Sensor Data: Utilize the Redis Telegraf plugin to collect and store data from IoT sensors in real-time. By connecting the plugin to a RedisTimeSeries database, users can analyze trends in temperature, humidity, or other environmental factors. The ability to query historical sensor data efficiently will aid in predictive maintenance and help in resource management.
-
Financial Market Data Aggregation: Employ this plugin to track and store time-sensitive financial data from various sources. By sending metrics to Redis, financial institutions can aggregate and analyze market trends or price changes over time, providing them with actionable insights derived from reliable time series analytics.
-
Application Performance Monitoring (APM): Implement the Redis plugin for gathering application performance metrics such as response times and CPU usage. Users can visualize their application’s performance over time with RedisTimeSeries, allowing them to identify bottlenecks and optimize resource allocation swiftly.
-
Energy Consumption Tracking: Leverage this plugin to monitor energy usage in buildings over time. By integrating with smart meters and sending data to RedisTimeSeries, municipalities or enterprises can analyze energy consumption patterns, helping to implement energy-saving measures and sustainability practices.
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
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration