Data Collection Module
Protocols for HIS data acquisition, data synchronization and import mechanisms
Data collection may be the most critical step toward building an AI model. Multiple choices are made in advance and remain constant throughout the data collection process. The core choices to be made are:
Wavelength Range Choice
The first thing to choose is the wavelength range and Full width at half maximum (FWHM) that suits the specific use case needs. Literature can provide insights for both. This, in turn, will determine the sensor to be used.
Next, the distance between the sensor and the sample should be constant throughout the measurements.
Model Robustness and Accuracy
To strengthen the model’s robustness and accuracy, the samples used should have a reasonable variation in the characteristic under evaluation.
The sample number should be at least 200.
The next choice is the lighting system in case the measurements occur in a lab. Based on the wavelength of choice, lamp performance can vary. Once again, literature can provide insights, or pre-experiments can be conducted to determine the most suitable one. In outdoor measurements, sessions should be conducted, preferably when the sun is at its peak and when there are no clouds.