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broker = "localhost" # MQTT broker address @@ -290,27 +288,51 @@ def on_connect(client, userdata, flags, rc): else: print(f"Connection failed with code {rc}") -# Data generators +client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2) +client.on_connect = on_connect +client.username_pw_set(username, password) +client.connect(broker, port, 60) + +# Data generator def generate_wheel_data(): velocity = random.uniform(0, 100) # Generate random velocity (between 0 and 100 km/h) direction = random.uniform(-45, 45) # Generate random direction (between -45 and 45 degrees) - return [velocity, direction] + return velocity, direction def generate_gps_data(): latitude = random.uniform(-90.0, 90.0) longitude = random.uniform(-180.0, 180.0) return latitude, longitude -# Parse data to Ditto Protocol -def get_ditto_protocol_msg(name, time, fields, values): - value = {} - for idx, field in enumerate(fields): - value[field] = { +# Ditto Protocol +def get_ditto_protocol_value_car(time, latitude, longitude): + return { + "gps" : { "properties": { - "value": values[idx], + "latitude": latitude, + "longitude": longitude, "time": time } } + } + +def get_ditto_protocol_value_wheel(time, velocity, direction): + return { + "velocity" : { + "properties": { + "value": velocity, + "time": time + } + }, + "direction": { + "properties" : { + "value": direction, + "time" : time + } + } + } + +def get_ditto_protocol_msg(name, value): return { "topic": "{}/{}/things/twin/commands/merge".format(namespace, name), "headers": { @@ -320,25 +342,22 @@ def get_ditto_protocol_msg(name, time, fields, values): "value": value } -# MQTT connection -client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2) -client.on_connect = on_connect -client.connect(broker, port, 60) - # Send data try: while True: t = round(time.time() * 1000) # Unix ms # Car twin - msg = get_ditto_protocol_msg(car_name, t, car_features, generate_gps_data()) + latitude, longitude = generate_gps_data() + msg = get_ditto_protocol_msg(car_name, get_ditto_protocol_value_car(t, latitude, longitude)) client.publish(topic + namespace + "/" + car_name, json.dumps(msg)) print(car_name + " data published") # Wheels twins for i in range(1, 5): name = wheels_name+str(i) - msg = get_ditto_protocol_msg(name, t, wheel_features, generate_wheel_data()) + velocity, direction = generate_wheel_data() + msg = get_ditto_protocol_msg(name, get_ditto_protocol_value_wheel(t, velocity, direction)) client.publish(topic + namespace + "/" + name, json.dumps(msg)) print(name + " data published") @@ -404,5 +423,94 @@ The Eclipse Ditto ip and port are obtained the same as mosquitto's, but since Di ``` +### Visualization + +Finally, we need to present the data in a user-friendly and meaningful way for the users of the digital twin. +To achieve this, we will create a new [dashboard](https://grafana.com/docs/grafana/latest/dashboards/) in Grafana and add [panels](https://grafana.com/docs/grafana/latest/panels-visualizations/) to display the relevant digital twin information. + +The digital twin data is stored in an [InfluxDB2](https://docs.influxdata.com/influxdb/v2/) database, so we will have to query the information using [Flux](https://docs.influxdata.com/flux/v0/) language. +If OpenTwins has been installed via Helm with default values, the [connection](https://grafana.com/docs/grafana/latest/datasources/) between InfluxDB and Grafana should already be established, so it will only be necessary to select it as data source when creating a panel. + +

+Children of car type +
+ +In this example, we will demonstrate a basic visualization. However, **you can use any of Grafana's functionalities and plugins to customize it according to your specific objectives**. +We will create four panels: one displaying the most recent GPS data of the car, another showing the evolution of the GPS data, a third panel indicating the current direction of all the wheels, and a fourth comparing the velocity of each wheel. +The result would look something like this: + +
+Grafana dashboard +
+ +For each of the four panels, we have selected the most convenient chart type, kept the default settings and added the related query in the Query section. + +The panel displaying the **current GPS** data extracts the longitude and latitude information from the digital twin *example:mycar*. +It renames the fields for proper display, retains the relevant fields, sorts the results by time, and keeps only the most recent entry. + +``` +import "strings" +from(bucket: "opentwins") + |> range(start: v.timeRangeStart, stop: v.timeRangeStop) + |> filter(fn: (r) => r["_measurement"] == "mqtt_consumer") + |> filter(fn: (r) => r["thingId"] == "example:mycar") + |> filter(fn: (r) => r["_field"] == "value_gps_properties_latitude" or r["_field"] == "value_gps_properties_longitude") + |> map(fn: (r) => ({ r with _field: strings.replace(v: r["_field"], t: "value_gps_properties_", u: "", i: 2) })) + |> keep (columns: ["_value", "_field", "_time"]) + |> sort(columns: ["_time"], desc: false) + |> last() +``` + +The panel for show the **GPS evolution** also extracts the latitude and longitude data from the digital twin *example:mycar*, but keeps all the entries instead of just the last one. + +``` +import "strings" +from(bucket: "opentwins") + |> range(start: v.timeRangeStart, stop: v.timeRangeStop) + |> filter(fn: (r) => r["_measurement"] == "mqtt_consumer") + |> filter(fn: (r) => r["thingId"] == "example:mycar") + |> filter(fn: (r) => r["_field"] == "value_gps_properties_latitude" or r["_field"] == "value_gps_properties_longitude") + |> map(fn: (r) => ({ r with _field: strings.replace(v: r["_field"], t: "value_gps_properties_", u: "", i: 2) })) + |> keep (columns: ["_value", "_field", "_time"]) +``` + +The panel displaying the **current direction of wheels** extracts the direction data of the four twins corresponding to the wheels, identified by starting with *example:mycar:wheel_*. +It modifies the identifiers of the twins for a more readable display and retains the most recent value based on time. + +``` +import "strings" +from(bucket: "opentwins") + |> range(start: v.timeRangeStart, stop: v.timeRangeStop) + |> filter(fn: (r) => r["_measurement"] == "mqtt_consumer") + |> filter(fn: (r) => strings.hasPrefix(v: r["thingId"], prefix: "example:mycar:wheel_")) + |> filter(fn: (r) => r["_field"] == "value_direction_properties_value") + |> map(fn: (r) => ({ r with thingId: strings.replace(v: r["thingId"], t: "example:mycar:", u: "", i: 2) })) + |> keep (columns: ["thingId", "_value", "_time"]) + |> sort(columns: ["_time"], desc: false) + |> last() +``` + +Finally, the panel that makes a **wheels velocity comparison** is similar to the previous one, although extracting the velocity data from the 4 twins instead of the direction and keeping all the entries. + +``` +import "strings" +from(bucket: "opentwins") + |> range(start: v.timeRangeStart, stop: v.timeRangeStop) + |> filter(fn: (r) => r["_measurement"] == "mqtt_consumer") + |> filter(fn: (r) => strings.hasPrefix(v: r["thingId"], prefix: "example:mycar:wheel_")) + |> filter(fn: (r) => r["_field"] == "value_velocity_properties_value") + |> map(fn: (r) => ({ r with thingId: strings.replace(v: r["thingId"], t: "example:mycar:", u: "", i: 2) })) + |> keep (columns: ["thingId", "_value", "_time"]) +``` -### Visualization \ No newline at end of file +This satisfies the basic requirements to consider a system as a digital twin. +However, to take full advantage of its capabilities, we recommend including other functionalities or additional data sources. +This will allow you to obtain a more complete and accurate view of the real system. +You can check our [guides](./category/guides) for more information \ No newline at end of file