I need a Python-driven solution that can reliably spot both ferrous and non-ferrous metals during industrial inspections. The detector will be deployed in mixed environments—sometimes on the factory floor, other times out in the yard—so the software must remain accurate despite changes in temperature, humidity, and electromagnetic noise. I already have the basic concept in mind but I’m looking for an experienced developer who can: • Select or interface with suitable sensor hardware (commonly used coils, Hall-effect, or EMI probes—happy to discuss alternatives). • Write clean, well-documented Python code that reads the sensor data in real time, filters out environmental noise, and flags detections with minimal latency. • Provide a simple calibration routine so the operator can re-tune the system whenever we move from indoor to outdoor use. • Output clear visual and/or audible alerts; a basic Tkinter or PyQt interface is sufficient for now. • Supply a short README explaining setup, dependencies, and how to extend the detection thresholds if required. Acceptance criteria 1. Detects both ferrous and non-ferrous test pieces (5 mm diameter) at ≥80 % success rate within a 10 cm range during lab trials. 2. Runs on a standard Raspberry Pi 4 under Python 3.9 without external internet access. 3. Full source code and wiring diagram delivered via Git repository or zip archive. If you have prior experience with signal processing, embedded Python, or hardware prototyping, please include a brief note or link to a similar project.