Artificial Intelligence (AI) and the Internet of Things (IoT) are two of today’s most impactful technology developments. Inevitably, an increasing range of both enterprise and consumer applications and solutions leverage both technologies, so that they are enabled by both AI and IoT. A growing subset of these applications and solutions incorporate AI capabilities directly onboard an IoT device, as AIoT, unlocking benefits ranging from faster response times to more efficient use of connectivity bandwidth.
This report focusses on the implications that the growth of AIoT might have on software platforms designed to support AIoT applications. Supporting software platforms for IoT are relatively well-developed, including Connectivity Management Platforms, Device Management Platforms, Application Enablement Platforms, and more. Meanwhile, supporting software platforms for AI are developing fast, and include concepts such as Application Performance Management, Software Management (often referred to as MLOps), Workload Management, and more.
Since AIoT is defined as occurring when AI and IoT converge onboard devices, it is natural that platforms that are designed to support AIoT devices should include a set of capabilities that are drawn from both AI and IoT domains, alongside new AIoT-specific capabilities.
This report discusses some of the key capabilities that a software platform specified to support AIoT devices should have. It focusses on the specific requirements for supporting AIoT devices, rather than more generic requirements that are well-known in either IoT or AI contexts.
