Contact person: Business Client

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Location: Chicago, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I am developing a self-contained toilet module for mobile homes that automatically collects urine and fecal matter, isolates the sample, and runs on-board AI to detect infectious agents in real time. The sole focus is medical-grade identification of bacterial, viral, or parasitic markers—no nutrient or hormone analysis is required. Once the test cycle completes, results must appear on an integrated, wall-mounted home display with clear color coding, confidence scores, and a short explanation of any abnormal findings.

To make this work end-to-end I need:

• A detailed hardware schematic and bill of materials for the sensor array, microfluidic handling, and self-cleaning mechanism.
• Embedded firmware that automates sample capture, prepares it for analysis, and triggers the cleanup cycle.
• A lightweight inference model (Python / TensorFlow Lite or comparable) trained specifically for infectious-agent detection, delivered with documented data sources and achieved accuracy metrics.
• A touchscreen interface packaged for a Raspberry Pi (or similar SBC) that renders live results, daily history, and threshold-based alerts.
• Assembly instructions that let a technician reproduce the prototype without guesswork.

Acceptance criteria:
– Correctly flags provided positive/negative control solutions with at least 90 % accuracy.
– Updates the home display within 60 seconds of sample collection.
– Performs an automated rinse that prevents cross-contamination for the next user.

Experience with biosensors, microfluidics, and edge AI will be essential to meet these targets and keep the unit compact enough for a mobile-home bathroom footprint." (client-provided description)