MicroAI™ is a self-correcting, semi-supervised learning engine that aggregates data from internal device sensors, to tune itself to create a behavioral profile of the asset, which then detects and acts upon abnormal behavior - delivering performance improvements and security enhancements to any device. MicroAI™ Atom brings big infrastructure intelligence into a single piece of equipment or device. Unlike traditional AI-driven asset management solutions that rely on edge based microcontrollers, MicroAI™ Atom is deployed directly to smart devices and sensors. MicroAI™ Atom operates within the small environment of the device itself, providing a more efficient method for asset analytics and generating real-time alerts. Atom generates real-time insights optimize asset performance while simultaneously enhancing security oversight. MicroAI™ Atom brings an intimate, local approach to asset management for producing a host of operational efficiencies.
MicroAI™ Atom is uniquely designed to train at the edge. Most vendors within the space deploy AI models that are trained in a cloud environment and pushed down to the edge locations. This means that each asset out in the field utilizes the same model. However, no two assets will always be operating under identical conditions. Those assets may be the same make and model but they may be performing completely different tasks while operating in different geographic locations within completely different environmental conditions. This is why MicroAI™ Atom is built and designed to train and process this individual data at the edge.
Training at the edge allows for massive amounts of data to be captured and analyzed without shipping across network communication protocols, or storing in cloud infrastructure. This greatly reduces the cost associated with data transmission, along with reducing, if not eliminating the cost of storing and processing the raw data - only the actionable insights need to be sent out. For example, if an asset has 10 unique sensor values being generated every second, over the course of a single hour, 360,000 data points are being generated. If this solution were to scale to hundreds and data is pulled at a faster rate than once per second, millions of data points are generated daily. With MicroAI™ Atom, only processed data created via the MicroAI™ behavioral analysis algorithm, are output.