KNX and IoTDB 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.

This plugin saves Telegraf metrics to an Apache IoTDB backend, supporting session connection and data insertion.

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.

IoTDB

Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Its light-weight architecture, high performance, and rich feature set create a perfect fit for massive data storage, high-speed data ingestion, and complex analytics in the IoT industrial fields. IoTDB deeply integrates with Apache Hadoop, Spark, and Flink, which further enhances its capabilities in handling large scale data and sophisticated processing tasks.

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"]

IoTDB

[[outputs.iotdb]]
  ## Configuration of IoTDB server connection
  host = "127.0.0.1"
  # port = "6667"

  ## Configuration of authentication
  # user = "root"
  # password = "root"

  ## Timeout to open a new session.
  ## A value of zero means no timeout.
  # timeout = "5s"

  ## Configuration of type conversion for 64-bit unsigned int
  ## IoTDB currently DOES NOT support unsigned integers (version 13.x).
  ## 32-bit unsigned integers are safely converted into 64-bit signed integers by the plugin,
  ## however, this is not true for 64-bit values in general as overflows may occur.
  ## The following setting allows to specify the handling of 64-bit unsigned integers.
  ## Available values are:
  ##   - "int64"       --  convert to 64-bit signed integers and accept overflows
  ##   - "int64_clip"  --  convert to 64-bit signed integers and clip the values on overflow to 9,223,372,036,854,775,807
  ##   - "text"        --  convert to the string representation of the value
  # uint64_conversion = "int64_clip"

  ## Configuration of TimeStamp
  ## TimeStamp is always saved in 64bits int. timestamp_precision specifies the unit of timestamp.
  ## Available value:
  ## "second", "millisecond", "microsecond", "nanosecond"(default)
  # timestamp_precision = "nanosecond"

  ## Handling of tags
  ## Tags are not fully supported by IoTDB.
  ## A guide with suggestions on how to handle tags can be found here:
  ##     https://iotdb.apache.org/UserGuide/Master/API/InfluxDB-Protocol.html
  ##
  ## Available values are:
  ##   - "fields"     --  convert tags to fields in the measurement
  ##   - "device_id"  --  attach tags to the device ID
  ##
  ## For Example, a metric named "root.sg.device" with the tags `tag1: "private"`  and  `tag2: "working"` and
  ##  fields `s1: 100`  and `s2: "hello"` will result in the following representations in IoTDB
  ##   - "fields"     --  root.sg.device, s1=100, s2="hello", tag1="private", tag2="working"
  ##   - "device_id"  --  root.sg.device.private.working, s1=100, s2="hello"
  # convert_tags_to = "device_id"

  ## Handling of unsupported characters
  ## Some characters in different versions of IoTDB are not supported in path name
  ## A guide with suggetions on valid paths can be found here:
  ## for iotdb 0.13.x           -> https://iotdb.apache.org/UserGuide/V0.13.x/Reference/Syntax-Conventions.html#identifiers
  ## for iotdb 1.x.x and above  -> https://iotdb.apache.org/UserGuide/V1.3.x/User-Manual/Syntax-Rule.html#identifier
  ##
  ## Available values are:
  ##   - "1.0", "1.1", "1.2", "1.3"  -- enclose in `` the world having forbidden character 
  ##                                    such as @ $ # : [ ] { } ( ) space
  ##   - "0.13"                      -- enclose in `` the world having forbidden character 
  ##                                    such as space
  ##
  ## Keep this section commented if you don't want to sanitize the path
  # sanitize_tag = "1.3"

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.

IoTDB

1. Real-Time IoT Monitoring: Utilize the IoTDB plugin to gather sensor data from various IoT devices and save it in an Apache IoTDB backend, facilitating real-time monitoring of environmental conditions such as temperature and humidity. This use case enables organizations to analyze trends over time and make informed decisions based on historical data, while also utilizing IoTDB’s efficient storage and querying capabilities.

2. Smart Agriculture Data Collection: Use the IoTDB plugin to collect metrics from smart agriculture sensors deployed in fields. By transmitting moisture levels, nutrient content, and atmospheric conditions to IoTDB, farmers can access detailed insights into optimal planting and watering schedules, thus improving crop yields and resource management.

3. Energy Consumption Analytics: Leverage the IoTDB plugin to track energy consumption metrics from smart meters across a utility network. This integration enables analytics to identify peaks in usage and predict future consumption patterns, ultimately supporting energy conservation initiatives and improved utility management.

4. Automated Industrial Equipment Monitoring: Use this plugin to gather operational metrics from machinery in a manufacturing plant and store them in IoTDB for analysis. This setup can help identify inefficiencies, predictive maintenance needs, and operational anomalies, ensuring optimal performance and minimizing unexpected downtimes.

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