Laser-induced thermal emissions detection with sensor fusion and AI for greenhouse gas monitoring

Overview

This solution offers a low-cost, field-deployable sensor prototype for detecting and quantifying greenhouse gases, including nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4), as well as their degradation products. The technology leverages Laser-Induced Thermal Emission (LITE) spectroscopy, which enhances the natural infrared and visible emission of gases to enable trace-level detection. By fusing data from infrared, thermal, and electrical sensors and applying artificial intelligence models, the system delivers improved specificity and quantification sensitivity compared to conventional spectroscopic approaches. The prototype is designed for water-resistant, durable operation in agricultural field conditions, with real-time data reporting capabilities that support environmental monitoring and emissions management.

Technical specifications

Core methodology:

• Laser-Induced Thermal Emission (LITE) spectroscopy increases natural gas emissions in the visible and infrared regions, enabling detection at trace levels
• Sensor fusion integrates mid-infrared (MIR) absorption, thermocouple, and electrical sensor data for enhanced quantification sensitivity
• Artificial intelligence models process spectral and sensor data to detect and quantify analytes with appropriate accuracy levels

Prototype components:

• Miniature spectrometer coupled to a sample compartment with laser induction
• Thermocouple for thermal measurement
• Electrical sensor for complementary signal capture
• Gas-capturing system for analyte collection
• Software for data capture, calibration, and AI-driven analysis

Performance benchmarks:

• Demonstrated gas trace detection at 21 pg/mL using MIR absorption spectroscopy supported by AI models and validated against GC-MS methodology
• Successful standoff detection of analytes and degradation products with increased IR emission sensitivity via LITE

Design features:

• Water-resistant construction for agricultural field durability
• Real-time data reporting capability
• Cost-effective architecture enabled by decreasing pulsed laser prices and integration of AI and sensor fusion

Technology readiness level

The technology is currently at the prototype development stage. Prior validation has demonstrated trace-level gas detection through MIR absorption spectroscopy with AI support, achieving a detection level of 21 pg/mL and confirmed against GC-MS methodology. Additionally, standoff detection of analytes and degradation products using the LITE methodology has been validated with demonstrated IR emission sensitivity improvements. The next development phase involves building an automated prototype integrating a miniature spectrometer, thermocouple, electrical sensor, and gas-capturing system for detecting N2O, CO2, and CH4 in real time. This will be followed by calibration and AI software programming. The final validation step requires partnership with standing row crop operations to test the prototype against a validated reference technique under real agricultural conditions.