The application discloses an
ammonia quantitative monitoring method facing anisotropic response of an olfactory sensor and edge calculation, belongs to the technical field of
gas monitoring, and specifically comprises the following steps: constructing an anisotropic response double-
sensor array; collecting
voltage signals and
environmental temperature and
humidity data in real time; performing anisotropic response
logic gate determination on two
voltage signals; storing
voltage values and temperature and
humidity data corresponding to effective signals into a sliding window buffer, extracting
time domain statistical features and dynamic trend features, combining temperature and
humidity to construct voltage-temperature ratio and voltage-
humidity ratio as physical cross features, and obtaining feature vectors after
standardization; inputting the feature vectors into a lightweight neural
network model deployed at the
microcontroller end, and outputting
ammonia concentration values after
nonlinear calibration and temperature and humidity compensation. The application realizes high-reliability real-time quantitative monitoring of
ammonia by inhibiting environmental common-mode interference through anisotropic response logic gating, and realizing temperature and humidity adaptive compensation through physical cross features and an edge neural network.