ADLINK helps enterprises unlock IoT value with time and cost efficiencies
Right now sorting boxes onto the appropriate pallet as these goods move through a supply chain is a time-consuming, error-prone manual process. But it doesn’t have to be. During the recent PACK Expo in Las Vegas, ADLINK demonstrated how a combination of readily-available technologies can streamline the palletization process.
Broadly speaking, using sensing technology to derive new value from physical assets is the entire premise of the internet of things. But beyond sensors, achieving this new level of value from a digitized world requires localized data analysis on top of edge computing infrastructure. While the term sensor might conjure images of a thermometer, motion sensor or more traditional form factor, in this particular scenario, and many other impactful IoT use cases, consider a camera as just another sensor–capturing and transmitting visual data.
For ADLINK’s demonstration, a worker would receive a box and hold it in view of a camera. The camera would “read” the metadata on the box and provide a visual cue–a red or green light, indicating whether the box was placed on the correct pallet. Imbuing the camera with machine vision is a combination of the visual input then localized computing that turns the imagery into actionable instruction.
According to ADLINK IoT Director for North America Daniel Collins, “One of our customers decreased the time it takes to build a pallet by 41%, increasing daily throughput by 200% without disrupting the way employees are used to working.”
And that combo of technologies is applicable beyond just palletization, Collins said. “Our edge IoT solutions can help make conveyors smart, find missing inventory, automate bin picking, determine fill levels, connect robots and more–all in real-time.”
ADLINK is all about making the analog world digital and machine vision is a key piece of that. In fact, the market for machine vision components grew 9.2% year-over-year in 2018 and is projected to be worth some $14 billion.
In terms of the business value derived from an edge IoT system applied to a manufacturing and/or logistics environment, consider these benefits:
● Measuring the correct fill levels on a manufacturing line;
● Detecting anomalies and other quality issues early in the production process;
● Enhancing existing robotics with software-based intelligence;
● Directing automated guided vehicles;
● And bringing digitization down to the boxes themselves.
“The reason we do as much computing at the edge as possible…is to really cut down on costs and increase speed,” Collins explained. “If we can do the computing at the edge first, then we can have an instant result. Vision is a great use case that requires edge computing–if you want to use real-time video streams to create inferences…you have to do that compute at the edge.”
For more information on getting started with Edge IoT for machine vision with ADLINK Smart Pallet, click here.
