IoT and IIoT technology deployment using edge sensors and devices succeeded in making Smart Farming possible. Techniques and knowledge are now available to those wishing to implement industrial automation that guarantees excellent results in the agriculture business, or in this case, indoor orchids cultivation.
Detecting flaws by employing machine vision systems is commonplace across a wide range of industries, including semiconductors, pharmaceuticals and automotive manufacturing, because machine vision systems not only lay bare all contamination, scratches, cracks, blemishes, discoloration, gaps and other imperfections undetectable by human vision, they also make available faster TTM and better resource optimization while at the same time lowering both the cost of ownership and the product fail rates.
This shift means that devices like IoT gateways and industrial PCs are being deployed en masse, in order to bring processing power closer to the data. And Gartner estimates that by 2020 at least 90% of all IoT projects will include gateway devices. Beyond the staggering scale of growth, managing these devices results in a myriad of challenges for organizations:
Nowadays the variety of beverage types is almost endless. They can roughly be categorized into sports drinks, energy drinks, bottled water, tea, coffee, carbonated beverages, wines/spirits and beers. Each category can be further sub-categorized based on flavors, sizes and where they are produced.
While most have yet to grasp the concept of Industry 4.0, Lanner has long completed its Industry 4.0 product roadmap and is now introducing its intelligent manufacturing solutions for MES, machine automation and vision inspection, enabling early adoption and system testing for Lanner’s strategic partners in preparation for developing smart manufacturing controllers and for realizing the implementation of smart factories.
While software-based thin client computing has now become ubiquitous in production automation, so too have the hardware appliances that can be customized and tailored for all industrial automation applications found at processing plants and manufacturing factories. Together with the availability of a variety of thin client management software, hardware appliances have evolved and changed in terms of their flexibility and capability.
Machine vision uses cameras, computers and software algorithms for carrying out inspection tasks that require precise and repetitive verification and testing in high speed. Accomplishing such tasks with human vision is extremely difficult, if not impossible, because while human eyes are capable of making precise measures in details, they aren’t equipped to do so in a rapid and repetitive manner; human vision, by comparison, is error-prone and could deteriorate irreversibly when made to perform such visually intensive tasks.