Behind the Scenes: How Antenna-I’s AI Learns to Detect Antenna Defects

Have you ever wondered how an AI system can detect something as subtle as a misaligned antenna? In this post, we take a closer look at the technology behind Antenna-I and how it is transforming quality control in IoT sensor manufacturing.

The Two AI Models

Antenna-I relies on two specialized AI models to ensure accurate and efficient quality control. The first, the Antenna Recognition AI, operates at the edge and is trained to identify the specific type of antenna being tested. Using RSSI data collected by ESP32 receivers, this model can distinguish between different antenna patterns with minimal training time—just 30 minutes per antenna type.

The second model, the Assembly Quality AI, works in tandem with the first to evaluate the correctness of the antenna assembly. By comparing live antenna patterns to predefined reference standards, this model can quickly flag discrepancies. For more complex cases, the system seamlessly transitions to cloud-based analysis, ensuring comprehensive quality assurance without compromising speed or accuracy.

Why It’s a Game-Changer

Antenna-I represents a significant leap forward in quality control technology. Unlike traditional methods that rely on visual inspection, our system uses RF signals to detect issues, eliminating challenges related to lighting or surface conditions. Its scalability and adaptability make it easy to integrate into diverse manufacturing environments, while its low-cost hardware and open-source framework ensure accessibility for small and medium-sized enterprises.