Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots

Area of Science:

• Occupational Safety
• Laboratory Automation
• Environmental Monitoring

Background:

• Increased automation in life science labs with robots necessitates enhanced safety measures.
• Robots may emit hazardous vapors from low volatile compounds, especially during leaks or accidents.
• Fast detection systems are crucial for human-robot collaboration safety.

Purpose of the Study:

• To develop and evaluate a modular IoT-sensor node for detecting hazardous vapors in automated life science laboratories.
• To assess the suitability of specific gas sensors (BME688, SGP30) for continuous total volatile organic compound (TVOC) measurement.
• To investigate the sensor node's integration and performance within practical laboratory automation scenarios.

Main Methods:

• Development of a modular IoT-sensor node with configurable hardware layers.
• Integration of BME688 and SGP30 gas sensors for TVOC monitoring.
• Controlled laboratory experiments to evaluate sensor response to various VOCs and installation conditions.
• Practical implementation and examination of the sensor node with stationary and mobile laboratory robots.

Main Results:

• The developed IoT-sensor node with BME688 and SGP30 sensors demonstrated suitability for early detection of solvent vapors.
• Sensor performance is influenced by the specific volatile organic compounds, distance from the source, and automation system speed.
• Controlled tests confirmed the general sensor behavior under different conditions.

Conclusions:

• The modular IoT-sensor node is effective for early detection of solvent vapors in life science laboratories.
• The system contributes to improved occupational safety in human-robot collaborative environments.
• System applicability is dependent on specific experimental parameters, highlighting the need for tailored configurations.