A computer-implemented method of detecting an event using different data sets, the method comprising: obtaining a first sample data set, wherein the first sample data set is representative of an acoustic signal across a frequency spectrum, and wherein the first sample data set is obtained using at least one sampling system having a first physical configuration, wherein the at least one sampling system comprises at least one acoustic sensor; determining at least one frequency domain feature of the first sample data set over a first time period; determining a first threshold for the at least one frequency domain feature using the first sample data set; determining that the at least one frequency domain feature matches the first threshold; determining the presence of an event during the first time period based on determining that the at least one frequency domain feature matches the first threshold; obtaining a second sample data set, wherein the second sample data set is representative of the acoustic signal across the frequency spectrum, and wherein the second sample data set is obtained using the at least one sampling system having a second physical configuration, wherein the first physical configuration is different than the second physical configuration; determining at least one frequency domain feature of the second sample data set over a second time period; characterized in that the method further comprises: determining a difference between the at least one frequency domain feature across the first sample data set and the at least one frequency domain feature across the second sample data set to obtain a difference data set; determining a variability in the difference data set; comparing the variability in the difference data set to a change threshold; determining a second threshold for the at least one frequency domain feature using the second sample data set, wherein determining the second threshold is based on the variability in the difference data set exceeding the change threshold; determining that the at least one frequency domain feature matches the second threshold; and determining the presence of the event during the second time period based on determining that the at least one frequency domain feature matches the second threshold. obtaining a first sample data set, wherein the first sample data set is representative of an acoustic signal across a frequency spectrum, and wherein the first sample data set is obtained using at least one sampling system having a first physical configuration, wherein the at least one sampling system comprises at least one acoustic sensor; determining at least one frequency domain feature of the first sample data set over a first time period; determining a first threshold for the at least one frequency domain feature using the first sample data set; determining that the at least one frequency domain feature matches the first threshold; determining the presence of an event during the first time period based on determining that the at least one frequency domain feature matches the first threshold; obtaining a second sample data set, wherein the second sample data set is representative of the acoustic signal across the frequency spectrum, and wherein the second sample data set is obtained using the at least one sampling system having a second physical configuration, wherein the first physical configuration is different than the second physical configuration; determining at least one frequency domain feature of the second sample data set over a second time period; determining a difference between the at least one frequency domain feature across the first sample data set and the at least one frequency domain feature across the second sample data set to obtain a difference data set; determining a variability in the difference data set; comparing the variability in the difference data set to a change threshold; determining a second threshold for the at least one frequency domain feature using the second sample data set, wherein determining the second threshold is based on the variability in the difference data set exceeding the change threshold; determining that the at least one frequency domain feature matches the second threshold; and determining the presence of the event during the second time period based on determining that the at least one frequency domain feature matches the second threshold.