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docs/accessing-context.md

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# Accessing the Context Data
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> "Ask and it shall be given you; seek, and ye shall find."
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>
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> — Matthew 7:7
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For a typical smart solution you will be retrieving context data from diverse sources (such as a CRM system, social
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networks, mobile apps or IoT sensors for example) and then analyzing the context programmatically to make appropriate
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business logic decisions. For example in the stock management demo, the application will need to ensure that the prices

docs/big-data-flink.md

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# Real-time Processing and Big Data Analysis using Apache Flink
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> "Who controls the past controls the future: who controls the present controls the past."
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> "You are what you eat."
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>
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> George Orwell. "1984"
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> Proverb
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Smart solutions based on FIWARE are architecturally designed around microservices. They are therefore are designed to
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scale-up from simple applications (such as the Supermarket tutorial) through to city-wide installations base on a large

docs/big-data-spark.md

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# Real-time Processing and Big Data Analysis using Apache Spark
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> "You have to find what sparks a light in you so that you in your own way can illuminate the world."
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> "Cooking is like love. It should be entered into with abandonment or not at all."
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>
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> Oprah Winfrey
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> Harriet van Horne
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Smart solutions based on FIWARE are architecturally designed around microservices. They are therefore are designed to
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scale-up from simple applications (such as the Supermarket tutorial) through to city-wide installations base on a large

docs/custom-iot-agent.md

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@@ -38,10 +38,10 @@ The process for creating your own IoT Agent is relatively simple. It is best ach
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which uses the required data transport and rewriting/amending the payload processing code to handle the payloads in
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question.
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For the purpose of this tutorial we will amend code from the existing JSON IoT Agent to process a similar custom
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XML format. A direct comparison of the two IoT Agents can be seen below:
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For the purpose of this tutorial we will amend code from the existing JSON IoT Agent to process a similar custom XML
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format. A direct comparison of the two IoT Agents can be seen below:
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| IoT Agent for JSON | IoT Agent for XML | Protocol's Area of Concern |
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| IoT Agent for JSON | IoT Agent for XML | Protocol's Area of Concern |
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| ------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------- |
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| Sample Measure `c\1` | Sample Measure <br/>`<measure device="lamp002" key="xxx">`<br/>&nbsp;&nbsp;`<c value="1"/>`<br/>`</measure>` | Message Payload |
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| Sample Command `Robot1@turn\left=30` | Sample Command <br/>`<turn device="Robot1">`<br/>&nbsp;&nbsp;`<left>30</left>`<br/>`</turn>` | Message Payload |
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## The teaching goal of this tutorial
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The aim of this tutorial is to improve developer understanding of how to create their own custom IoT Agents, a series of
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simple modifications has been made to the code of the JSON IoT Agent demonstrating how to make changes. The
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tutorial consists of a walkthrough of the relevant code and a series of HTTP requests to connect the new IoT Agent. The
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code can be found within the current
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simple modifications has been made to the code of the JSON IoT Agent demonstrating how to make changes. The tutorial
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consists of a walkthrough of the relevant code and a series of HTTP requests to connect the new IoT Agent. The code can
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be found within the current
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[GitHub Repository](https://github.com/FIWARE/tutorials.Custom-IoT-Agent/tree/master/iot-agent)
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## Reusing Common Functionality
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```
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As expected the HTTP command to **provision a device** does not change based on the underlying payload or transport
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protocol since we are using the same HTTP transport as the original JSON IoT Agent. `internal_atttributes` can be
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used to supply additional information for the custom IoT Agent if necessary. In the request we are associating the
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device `motion001` with the URN `urn:ngsi-ld:Motion:001` and mapping the device reading `c` with the context attribute
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`count` (which is defined as an `Integer`) A `refStore` is defined as a `static_attribute`, placing the device within
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**Store** `urn:ngsi-ld:Store:001`
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protocol since we are using the same HTTP transport as the original JSON IoT Agent. `internal_atttributes` can be used
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to supply additional information for the custom IoT Agent if necessary. In the request we are associating the device
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`motion001` with the URN `urn:ngsi-ld:Motion:001` and mapping the device reading `c` with the context attribute `count`
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(which is defined as an `Integer`) A `refStore` is defined as a `static_attribute`, placing the device within **Store**
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`urn:ngsi-ld:Store:001`
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You can simulate a dummy IoT device measurement coming from the **Motion Sensor** device `motion001`, by making the
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following XML request
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<h3>Reading Measures - Analysing the Code</h3>
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Both the payload and the `Content-Type` have been updated. The dummy devices made a similar JSON request in the
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previous tutorials when the door was unlocked, you will have seen the state of each motion sensor changing and a
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Northbound request will be logged in the device monitor.
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Both the payload and the `Content-Type` have been updated. The dummy devices made a similar JSON request in the previous
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tutorials when the door was unlocked, you will have seen the state of each motion sensor changing and a Northbound
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request will be logged in the device monitor.
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Now the IoT Agent is connected, the service group has defined the resource upon which the IoT Agent is listening
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(`iot/xml`) and the API key used to authenticate the request (`4jggokgpepnvsb2uv4s40d59ov`) is found in the body. Since
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1. The custom IoT Agent is making a registration for an attribute
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2. The custom IoT Agent each request for updating context (on the `/v2/op/update` endpoint)
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3. A decision is made how to handle the request - for both the Custom IoT Agent and the JSON Agent this follows
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the paradigm of setting a `<command>State` attribute, amending and forwarding the request on a `/cmd` endpoint to
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the device (or alternatively to a middleware responsible for the device).
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3. A decision is made how to handle the request - for both the Custom IoT Agent and the JSON Agent this follows the
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paradigm of setting a `<command>State` attribute, amending and forwarding the request on a `/cmd` endpoint to the
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device (or alternatively to a middleware responsible for the device).
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The first two items - listening to context changes from the context broker follow the well-defined NGSI syntax and
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therefore are common to all IoT Agents. However, the third item - what to do to prepare the message for ongoing

docs/historic-context-flume.md

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For the purpose of this tutorial, a series of dummy IoT devices have been created, which will be attached to the context
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broker. Details of the architecture and protocol used can be found in the [IoT Sensors tutorial](iot-sensors.md). The
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state of each device can be seen on the JSON device monitor web page found at:
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`http://localhost:3000/device/monitor`
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state of each device can be seen on the JSON device monitor web page found at: `http://localhost:3000/device/monitor`
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![FIWARE Monitor](https://fiware.github.io/tutorials.Historic-Context-Flume/img/device-monitor.png)
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docs/historic-context-nifi.md

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For the purpose of this tutorial, a series of dummy IoT devices have been created, which will be attached to the context
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broker. Details of the architecture and protocol used can be found in the [IoT Sensors tutorial](iot-sensors.md). The
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state of each device can be seen on the JSON device monitor web page found at
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`http://localhost:3000/device/monitor`.
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state of each device can be seen on the JSON device monitor web page found at `http://localhost:3000/device/monitor`.
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![FIWARE Monitor](https://fiware.github.io/tutorials.Historic-Context-NIFI/img/device-monitor.png)
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