The RT-CDRSS employs advanced sensors integrated into the processing lines to continuously monitor for contaminants at microscopic levels.

These sensors use technologies like spectroscopy and biosensors to detect any anomaly or hazardous particles, instantly analyzing air quality and surface contaminants.

Once detected, the system automatically triggers responsive sanitation mechanisms using targeted UV-C light and electrostatic fogging to deactivate or remove contaminants.

The system is connected to a central AI-driven software that collects data, learns patterns, and optimizes the sanitation processes, ensuring minimal disruption to operations.

This approach allows for swift isolation and cleaning of the affected areas without halting the overall production line.

The system significantly reduces contamination risks with real-time, precise detection, and automatic sanitation responses that prevent costly recalls and enhance food safety without causing downtime.

It leverages AI to continually improve efficiency and response times, maintaining high production throughput.

Sensor technology for real-time detection exists in laboratory environments and could be adapted for industrial use; however, ensuring scalability and consistency across various facilities presents an engineering challenge.

Technologies such as UV-C light and electrostatic sanitation are proven but require substantial integration into existing production lines.

Market adoption will likely be driven by regulatory changes emphasizing food safety compliance.