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Turn Data Into Insights With Medium One

Medium One combines real-time stream processing, built-in analytics and machine learning for enterprises to enable rapid prototyping and deployment of Internet of Things (IoT) solutions. Our simple-to-use tools offer users fast time-to-market, even for complex, real-time applications.

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We have integrated our data intelligence cloud platform with SAMI data exchange, thus enabling SAMI developers to augment their data with real-time stream processing capabilities and simple-to-build workflows. The below video gives a sense of the possibilities:

Our platform ingests data through REST/JSON Web APIs, as well as MQTT protocol. Our customers use Python to create custom workflow processing modules, and Python also enables interoperation with SAMI. We have extended our WebSockets to interface with SAMI by using a Python library, websocket-client, to connect to SAMI’s WebSockets.

In addition, we made the SAMI application integration seamless through simple account registration links. SAMI’s Users and Messages APIs allow us to register users and push/pull the data for the devices that we have created using the Developer Portal. We then take the message data and process it further with our custom workflows.

With the User and Developer Portals, we created demo applications, users and device Manifests for the retail store demo seen above. In our demo, a sensor Manifest is used to handle retail facility monitoring. It includes temperature, sound, light, presence, staff, and other data fields.

Medium One Sensor Manifest in SAMI

Now that we have implemented a seamless integration with SAMI, we are exploring ways to make the data intelligence workflows even easier to use. Stay tuned for more updates on Medium One and SAMI, as well as new developments with Samsung ARTIK!

This is a guest post from Medium One.

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