Docs

Platforms

Suggest Edits

Examples of IoT Platforms

There are several cloud IoT platforms in which you can fairly easy process your data and show dashboards for your sensor data and/or trigger events. These platforms are especially good to start with if you are just starting to build an IoT solution. Some examples are:

If the above platforms would not be sufficient and you will need more flexibility, data storage and stronger data processing tools, there are several options you can choose from that are far more powerful, but also more complex. Some examples are:

These IoT cloud platforms are more complex due to the tons of possibilities they provide. To choose the right platform that suits your use case best, we have added some info to compare them. This info comes from the following article:
https://www.computerworlduk.com/galleries/data/best-internet-of-things-platforms-3635185/

A deeper look into platforms

BEST CLOUD IOT PLATFORMS
As businesses look to adopt the Internet of Things (IoT) by connecting internet-enabled devices to assets and relay that information back to key decision makers, the need for a platform to store, manage and analyse all this data is increasingly important.

The good news is there are lots of options on the market. All of the big players in public cloud (AWS, Azure, Google and IBM) have developed IoT platforms on top of their infrastructure, and there are also smaller pure-play options for more industrial IoT (IIoT) uses.

The bad news is this means the IoT platform market can be a bit of a jungle, with all of the big players promising the easiest, smartest platform available.

We run through the best IoT platforms for your business that can help you get the most out of connected assets and the data they collect to create operating efficiencies and even new business models.

GOOGLE

Google made its fully managed IoT platform generally available in February 2018.

Cloud IoT Core sits on top of the Google Cloud Platform and is marketed as having an edge on its rivals through its focus on 'intelligence'. This means you can connect, manage and ingest IoT device data to the Google platform before running an array of advanced analytics.

These include ad-hoc queries using Google BigQuery, machine learning with Cloud Machine Learning Engine, data visualisations in Google Data Studio and automating changes to devices based on real-time events with Cloud Functions workflows.

Google has also acquired IoT platform Xively from LogMeIn for $50 million and will integrate its tools into Cloud IoT Core.

The Google stack currently works roughly like this: device data is captured by the Cloud IoT Core and published to Cloud Pub/Sub, ready for downstream analytics. Google also supports out-of-the-box integration with IoT hardware makers such as Intel and Microchip.

AWS

AWS IoT Core is a managed cloud platform that provides a place to connect and manage sensors on cars, turbines, sensor grids and elsewhere by using AWS' public cloud to store, process and analyse the data transmitted by these devices.

The platform provides a device SDK, secure device gateway, message broker, registry for recognising devices, device shadows and a rules engine to evaluate inbound messages.

AWS has also struck partnerships with the likes of Broadcom, Intel and Qualcomm to create hardware component "IoT Starter Kits" that are compatible with its services.

The vendor also produces software called AWS Greengrass that allows customers to run local compute, messaging and data caching at the edge, so on the connected devices themselves. Greengrass uses AWS Lambda functions to keep device data in sync, and lets them communicate with other devices securely, even when they're not connected to the internet.

MICROSOFT

Running alongside Microsoft Azure cloud services, the Azure IoT Hub offers a rules engine, identity registry, information monitoring and device shadowing.

The IoT platform incorporates existing products such as IoT Hub, Stream Analytics, notifications hubs, Power BI and some pre-packed machine learning to process and analyse large quantities of device data in near real-time.

For example, Rolls Royce is using Azure Stream Analytics and Power BI to link up sensor data from its airline engines with more contextual information like air traffic control, route data, weather and fuel usage to get a fuller picture of the health of its aircraft engines.

Using Microsoft's Azure IoT Suite to collect data and Cortana Intelligence Suite to derive insights, Rolls-Royce can go beyond predictive maintenance and into metrics that it can pass onto operations teams at airlines as a value-added service.

IBM

IBM Watson IoT is a platform for customers to connect all of their devices and IoT device data into a repository, where the cognitive capabilities of Watson can be leveraged to gain insight into an IoT network to improve operations and even launch new business models.

IBM Watson users receive device management, real-time data exchange, secure communications and data storage as part of the IoT platform.

For example, Finnish escalator and elevator manufacturer KONE has been using IBM Watson IoT alongside Salesforce software to manage its connected assets, which carry as many as 1 billion people every day.

By combining intelligent analysis from IBM Watson IoT with Salesforce's Service Cloud Lightning and Field Service Lightning tools, the company will be able to respond to emergencies as they happen.

DIY - Learn how to do it!

If you want to know more about the integration of specific modules/devkits, plattforms, applications and/or off-the-shelf sensors and IoT solutions and actually start doing it yourself, please check out our "Integrations" chapter.

To get a good overview of all the things you would need to consider when choosing a cloud IoT platform, we recommend to read the following article:
https://medium.com/iotforall/how-to-choose-your-iot-platform-should-you-go-open-source-23148a0809f3

Updated over 3 years ago