Environment controller and method for predicting co2 level variations based on sound level measurements

A method for predicting carbon dioxide (CO2) level variations based on sound level measurements, the method comprising:

• storing a predictive model in a memory of a computing device;
• determining by a processing unit of the computing device N consecutive sets of frequency domain sound level measurements, each set of frequency domain sound level measurements comprising a given number M of sound level amplitudes at the corresponding given number M of frequencies, N and M being integers;
• and
• executing by the processing unit of the computing device a neural network inference engine using the predictive model for inferring one or more output based on inputs, the inputs comprising the N consecutive sets of frequency domain sound level measurements, the one or more output comprising a predicted variation of a CO2 level.

A non-transitory computer program product comprising instructions executable by a processing unit of a computing device, the execution of the instructions by the processing unit of the computing device providing for predicting carbon dioxide (CO2) level variations based on sound level measurements by:

• storing by the processing unit a predictive model in a memory of a computing device;
• determining by the processing unit N consecutive sets of frequency domain sound level measurements, each set of frequency domain sound level measurements comprising a given number M of sound level amplitudes at the corresponding given number M of frequencies, N and M being integers;
• and
• executing by the processing unit a neural network inference engine using the predictive model for inferring one or more output based on inputs, the inputs comprising the N consecutive sets of frequency domain sound level measurements, the one or more output comprising a predicted variation of a CO2 level.