1. Automated Quality Inspection in Food & Beverage Washdown Zones
Utilizing the IDS NXT oslo camera to perform on-edge AI vision inspection for packaging defects and contamination in food processing plants, where equipment is subjected to intensive daily cleaning.
Problem SolvedStandard vision systems degrade or short-circuit during mandatory high-temperature, high-pressure sanitation washdowns in food processing. This camera solves the environmental limitation while eliminating the latency of centralized AI processing by running neural networks directly on the edge.
IP69 / IPx9K ratingNeural Processing Unit (NPU)Ambarella SoC8.29 MP Resolution
2. Intelligent Traffic Monitoring and Low-Light ANPR
Deploying the camera for Automatic Number Plate Recognition (ANPR) and traffic anomaly detection in smart city infrastructures, requiring reliable 24/7 operation under challenging ambient lighting and weather conditions.
Problem SolvedCapturing clear images of moving vehicles at night or during heavy rain typically requires expensive external lighting or results in blurry footage. The highly sensitive sensor resolves this issue natively, while efficient compression saves limited remote network bandwidth.
Sony Starvis 2 IMX678IP66 / IP67 ratingRTSP / H.264 CompressionPower-Over-Ethernet
3. AI-Driven Robotic Bin Picking for Micro-Component Assembly
Integrating the camera into robotic work cells to identify and localize randomly oriented micro-components within bulk bins, enabling autonomous robotic arms to pick and place parts for assembly.
Problem SolvedRobotic sorting of tiny, overlapping parts requires extremely high visual precision and fast inference. Traditional PC-based vision setups introduce latency and require complex cabling. This camera processes object detection locally while capturing ultra-fine details.
3840 x 2160 Resolution2.00 µm Pixel SizeCMOS Rolling Shutter1.00 Gbps Ethernet Interface
