An apparatus for monitoring a switchgear, the apparatus comprising: - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with a monitor infra-red image of a switchgear; wherein, the processing unit is configured to implement a machine learning classifier algorithm to analyse the monitor infrared image and determine if there is one or more anomalous hot spots in the switchgear; wherein the monitor infra-red image comprises image data of one of a plurality of circuit breakers; wherein, the machine learning classifier algorithm has been trained on the basis of a plurality of training images, wherein the plurality of training images comprises at least one synthetic infra-red image of a switchgear generated by an image processing algorithm, wherein the at least one synthetic infra-red image was generated by a Generative Adversarial Network on the basis of at least one real infra-red image of a switchgear, wherein the at least one real infra-red image comprises a plurality of different real infra-red images, wherein the different real infra-red image comprises image data of a plurality of circuit breakers, wherein the at least one synthetic infrared image comprises a plurality of different synthetic infra-red images, wherein the plurality of synthetic infra-red images comprises a plurality of synthetic infrared images of each of the circuit breakers, and wherein the number of the plurality of different real infra-red images is less than the number of the plurality of synthetic infra-red images; and wherein, the output unit is configured to output information relating to the one or more anomalous hot spots. - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with a monitor infra-red image of a switchgear; wherein, the processing unit is configured to implement a machine learning classifier algorithm to analyse the monitor infrared image and determine if there is one or more anomalous hot spots in the switchgear; wherein the monitor infra-red image comprises image data of one of a plurality of circuit breakers; wherein, the machine learning classifier algorithm has been trained on the basis of a plurality of training images, wherein the plurality of training images comprises at least one synthetic infra-red image of a switchgear generated by an image processing algorithm, wherein the at least one synthetic infra-red image was generated by a Generative Adversarial Network on the basis of at least one real infra-red image of a switchgear, wherein the at least one real infra-red image comprises a plurality of different real infra-red images, wherein the different real infra-red image comprises image data of a plurality of circuit breakers, wherein the at least one synthetic infrared image comprises a plurality of different synthetic infra-red images, wherein the plurality of synthetic infra-red images comprises a plurality of synthetic infrared images of each of the circuit breakers, and wherein the number of the plurality of different real infra-red images is less than the number of the plurality of synthetic infra-red images; and wherein, the output unit is configured to output information relating to the one or more anomalous hot spots. <EOS>