We are building an IoT platform to enable intelligence. This means adding digital inputs and outputs to objects in the physical world. Current IoT technology makes it possible to deploy a sensor, connect it to the cloud, and send data. This is immensely powerful, but it is only the first step. The next step is to make these physical objects more intelligent. We aim to achieve this by pushing the compute capability as close as possible to the source of data. This is known as edge computing.

Arm recently invested in SWIM.AI’s Series B to accelerate developers in creating the apps that will define the edge computing era. SWIM.AI does this through EDX, their world-leading distributed computing platform. EDX makes it simple, cheap, and efficient to build and deploy apps that run simultaneously on edge devices, the cloud and in between. Their solution complements the Arm Mbed IoT Device Management Platform and our mission of enabling organizations to seamlessly obtain and derive meaning from their IoT data.

The potential for edge computing is huge: Business Insider estimates that 5.6 IoT devices owned by enterprises and governments will utilize edge computing for data collection and processing by 2020. Edge devices have access to a wealth of information from many kinds of sensors. Processing this information at the edge has the potential to deliver new applications and user experiences that are faster, more efficient, cheaper, and more personalized while improving privacy and security.

However, making this a reality requires developers to do a lot of “plumbing” (operating systems, networks, databases ad systems programming, etc.). SWIM EDX removes these barriers by providing an integrated platform that handles all of this plumbing. This enables developers to focus on building the apps that unlock the value for them and their users.

For example, SWIM.AI is used to enable cars to choose the least congested routes using real-time traffic predictions for the intersections ahead. SWIM.AI is also used in manufacturing facilities to track components, detect faulty items, and remove them from the assembly line before they cause further issues.

In addition to the benefits of distributed compute, SWIM EDX brings data analysis and machine learning as close as possible to the device that generated it, with analysis workloads optimized for Arm devices. This means data that was previously too expensive or difficult to analyze in the cloud becomes usable and valuable. EDX currently runs in Java, with an SDK for other languages.

We look forward to seeing SWIM.AI continue to enable new applications and user experiences, taking us a step closer to a world of connected intelligence.  

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