Artificial Intelligence of Things (AIoT) combines AI and IoT to create smart, connected systems that can analyze and respond intelligently to data collected from IoT devices. IoT systems facilitate the collection and exchange of data among various devices and AI analyzes the data to drive smart decision-making ― without the need for human intervention.

Today’s industrial solutions are continuously evolving. Industrial automation and IoT industries demand rugged and compact solutions that excel in edge computing tasks, such as real-time decision-making, without compromising energy efficiency and customizability for the wide range of Industry 4.0 devices.

Today’s industrial environments are pressured by the need for real-time data analysis and decision-making at the edge, especially for applications like machine vision, automated guided vehicles (AGV), autonomous mobile robots (AMR), and intelligent video-analytics applications that assist with sorting machinery, performing automated optical inspection (AOI) and defect inspection, and object recognition tasks.

It’s almost hard to imagine a conversation these days that doesn’t involve AI. The topic du jour is how we can enhance Edge AI performance using MXM (mobile PCI Express module) GPU modules. First, let’s briefly explain what an MXM GPU module is and what functions it performs.

With the influx of industrial applications being deployed in a variety of today’s challenging environments, the need for reliable, flexible, and high-performance computing solutions is dire. Edge computing solutions like smart factories, intelligent transportation and video analytics, and machine vision need rugged devices capable of operating in environments with extreme temperatures, dust, and vibration, without sacrificing performance.

Edge AI is being increasingly deployed across various sectors, including healthcare, manufacturing, retail, and smart cities. This trend is driven by the need for real-time data processing and decision-making at the source of data generation, facilitated by deep learning at the Edge.

Industrial environments are often faced with harsh conditions that are demanding, and sometimes, unpredictable. Extreme temperatures, moisture, dust, and vibration are all factors that influence the reliability, performance, and overall lifetime of traditional systems. With the added demands of remote monitoring and industrial automation functions, it’s important that these mission- and safety-critical applications consistently withstand these challenges.