Smart Microwave Sensor-Based Bottle Defect Detection, Filling, and Capping System

Bottle-packaging quality depends on several distinct operations, including container inspection, liquid filling, cap application, and verification of the finished package. This review examines selected publications from 2018 to 2026 on microwave non-destructive testing, microwave-based material characterization and level sensing, machine-vision inspection, deep-learning methods, and automated filling and capping. The literature is organized by the task addressed rather than by sensor name alone, because bottle-presence detection, structural-defect identification, material characterization, and liquid-level estimation are not interchangeable functions. The reviewed studies also differ in specimen materials, inspection regions, datasets, operating conditions, and reported metrics; therefore, their numerical results do not support a single cross-method ranking. The review compares these distinctions and identifies the evidence needed to validate microwave sensing on actual bottle materials and to integrate inspection decisions with packaging control. The accompanying project report documents a prototype that uses camera-based silhouette analysis with an ESP32-controlled handling, filling, and capping sequence. It does not establish microwave-based structural-defect detection in the prototype. Open research needs include bottle-specific microwave validation, detection of fine surface defects, feedback-based filling and cap tightening, fault-aware subsystem integration, and reproducible evaluation protocols.