Hailo
Hailo, Q-technology, and Newtec's video was engineered to prove the enhanced throughput and reduced downtime achieved by their industrial tech. In the high-stakes food processing industry, relying on legacy sorting hardware often leads to costly crop misclassifications, lower yields, and severe operational bottlenecks. Failing to integrate edge AI hardware acceleration into sorting pipelines prevents facilities from processing high-resolution visual data in real time, leading to massive financial waste and compromised quality control.
Our design team mapped a structural visual blueprint that clarifies the hardware-to-software synergy. This computer vision demonstration spotlights the compact M2 AI module mating with the PCIe slot inside the camera casing, followed by side-by-side segmentation comparative views showcasing potato sorting with and without the active neural network. These technical CAD-style layouts and clear object-tracking boundaries demystify the high-speed data flow, so that food processing plant managers immediately grasp how edge-computed neural networks prevent product waste.
We executed a clean, precise mechanical animation style, utilizing smooth linear camera movements to track the flow of produce along the sorting belts. Framing this industrial solution overview within a clean, high-contrast industrial lab aesthetic minimizes visual clutter and prevents cognitive fatigue for technical viewers. The structural spatial layout routes the viewer's attention directly from raw hardware integration to real-time classification metrics. This authoritative visual execution builds absolute confidence in the system's operational viability, positioning Advids as a premier partner in technical video communication.