At Hammer-IMS, we specialize in advanced quality control solutions powered by neural networks and intelligent vision systems. To demonstrate our software’s versatility and AI-skills we set up a quick showcase with a simple IP-camera and a single board computer installed in the backyard of one our company’s founders. The result: a cool bird detector and classification application!
While our core technology is designed to detect material anomalies and quality deviations in industrial environments, the principles behind it are equally applicable in other contexts. In this case, we repurposed our detection and classification pipelines to identify and count bird species, offering a clear and intuitive demonstration of how our technology works. The system first uses a motion or anomaly detection algorithm to identify biological activity. When movement is detected, an image is captured and stored. In the initial phase of the project, these images were then annotated and used to train a neural network to recognize different bird species. Once trained, the system can classify every passing bird and log its occurrence—illustrating the same kind of detection, classification, and logging mechanisms used in industrial quality control.
This bird detection demo serves as a simplified analogy to our customer solutions: capturing anomalies, learning from them, and providing, real-time actionable insights. It's a user-friendly example of how Hammer-IMS leverages AI to boost up inline product quality straight from its Connectivity 3.0 software environment.
More information on our AI-enabled machine-vision solutions can be found on our technology page.
