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The study presents a cost-effective and scalable method to determine the Window to Wall Ratio (WWR) and Air conditioning status of existing buildings from ground-view façade imagery. Object Detection Classifier deploying Faster Region-based Convolutional Neural Network (Faster R-CNN) is used to detect windows and buildings in visible images. The detected elements are used by the second algorithm to calculate the Window to Wall Area Ratio (WWR) with a 40% variation from actual values. By superimposing the detected elements on corresponding thermal images of the building, a third algorithm is used to obtain the outside surface temperatures of windows and walls. Based on simulation study, a difference greater than 7 °C between these values translates into air-conditioned zone.