KNX and SQLite Integration

Input and output integration overview

The KNX plugin listens for messages from the KNX home-automation bus via a KNX-IP interface, allowing for real-time data integration from KNX-enabled devices.

Telegraf’s SQL output plugin stores metrics in an SQL database by creating tables dynamically for each metric type. When configured for SQLite, it utilizes a file-based DSN and a minimal SQL schema tailored for lightweight, embedded database usage.

Integration details

KNX

The KNX plugin allows for the listening to messages transmitted over the KNX home-automation bus. It establishes a connection with the KNX bus through a KNX-IP interface, making it compatible with various message datapoint types that KNX employs. The plugin supports service input configuration, wherein it remains active to listen for relevant metrics or events rather than relying solely on scheduled intervals. This inherent characteristic enables real-time data capture from the KNX systems, enhancing automation and integration possibilities for building management and smart home applications. Additionally, this plugin is designed to handle multiple measurements from the KNX data, allowing for a flexible categorization of metrics based on the derived datapoint types, thus broadening the scope of data integration in smart environments.

SQLite

The SQL output plugin writes Telegraf metrics to an SQL database using a dynamic schema where each metric type corresponds to a table. For SQLite, the plugin uses the modernc.org/sqlite driver and requires a DSN in the format of a file URI (e.g., ‘file:/path/to/telegraf.db?cache=shared’). This configuration leverages standard ANSI SQL for table creation and data insertion, ensuring compatibility with SQLite’s capabilities.

Configuration

KNX

[[inputs.knx_listener]]
  ## Type of KNX-IP interface.
  ## Can be either "tunnel_udp", "tunnel_tcp", "tunnel" (alias for tunnel_udp) or "router".
  # service_type = "tunnel"

  ## Address of the KNX-IP interface.
  service_address = "localhost:3671"

  ## Measurement definition(s)
  # [[inputs.knx_listener.measurement]]
  #   ## Name of the measurement
  #   name = "temperature"
  #   ## Datapoint-Type (DPT) of the KNX messages
  #   dpt = "9.001"
  #   ## Use the string representation instead of the numerical value for the
  #   ## datapoint-type and the addresses below
  #   # as_string = false
  #   ## List of Group-Addresses (GAs) assigned to the measurement
  #   addresses = ["5/5/1"]

  # [[inputs.knx_listener.measurement]]
  #   name = "illumination"
  #   dpt = "9.004"
  #   addresses = ["5/5/3"]

SQLite

[[outputs.sql]]
  ## Database driver
  ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
  ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
  driver = "sqlite"

  ## Data source name
  ## For SQLite, the DSN is a filename or URL with the scheme "file:".
  ## Example: "file:/path/to/telegraf.db?cache=shared"
  data_source_name = "file:/path/to/telegraf.db?cache=shared"

  ## Timestamp column name
  timestamp_column = "timestamp"

  ## Table creation template
  ## Available template variables:
  ##  {TABLE}        - table name as a quoted identifier
  ##  {TABLELITERAL} - table name as a quoted string literal
  ##  {COLUMNS}      - column definitions (list of quoted identifiers and types)
  table_template = "CREATE TABLE {TABLE} ({COLUMNS})"

  ## Table existence check template
  ## Available template variables:
  ##  {TABLE} - table name as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL (optional)
  init_sql = ""

  ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
  connection_max_idle_time = "0s"

  ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
  connection_max_lifetime = "0s"

  ## Maximum number of connections in the idle connection pool. 0 means unlimited.
  connection_max_idle = 2

  ## Maximum number of open connections to the database. 0 means unlimited.
  connection_max_open = 0

  ## Metric type to SQL type conversion
  ## The values on the left are the data types Telegraf has and the values on the right are the SQL types used when writing to SQLite.
  #[outputs.sql.convert]
  #  integer       = "INT"
  #  real          = "DOUBLE"
  #  text          = "TEXT"
  #  timestamp     = "TIMESTAMP"
  #  defaultvalue  = "TEXT"
  #  unsigned      = "UNSIGNED"
  #  bool          = "BOOL"

Input and output integration examples

KNX

1. Smart Home Energy Monitoring: Utilize the KNX plugin to monitor energy consumption across various devices in a smart home setup. By configuring measurements for different appliances, users can gather real-time data on power usage, enabling them to optimize energy consumption and reduce costs. This setup can also integrate with visualization tools to provide insights into energy trends and usage patterns.

2. Automated Lighting Control System: Leverage this plugin to listen for lighting status updates from KNX sensors in a building. By capturing measurements related to illumination, users can develop an automated lighting control system that adjusts the brightness based on the time of day or occupancy, enhancing comfort and energy efficiency.

3. HVAC Performance Tracking: Implement the KNX plugin to track temperature and ventilation data across different zones in a building. By monitoring these metrics, facilities managers can identify trends in HVAC performance, optimize climate control strategies, and proactively address maintenance needs to ensure consistent environmental quality.

4. Integrated Security Solutions: Use the plugin to capture data from KNX security sensors, such as door/window open/close statuses. This information can be routed into a central monitoring system, providing real-time alerts and enabling automated responses, such as locking doors or activating alarms, thus enhancing the building’s security posture.

SQLite

1. Local Monitoring Storage: Configure the plugin to write metrics to a local SQLite database file. This is ideal for lightweight deployments where setting up a full-scale database server is not required.
2. Embedded Applications: Use SQLite as the backend for applications embedded in edge devices, benefiting from its file-based architecture and minimal resource requirements.
3. Quick Setup for Testing: Leverage SQLite’s ease of use to quickly set up a testing environment for Telegraf metrics collection without the need for external database services.
4. Custom Schema Management: Adjust the table creation templates to predefine your schema if you require specific column types or indexes, ensuring compatibility with your application’s needs.

Feedback

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