Abstract: A method to continuously identify and recognize microbiota in water comprises random sampling of a water source, directing the sample to an optical plane where microscopic CCD/video images are obtained and stored in analogue and digitized form. Statistical data on organism type and number will be simultaneously collected. Using novel software the digitized images are filtered and segmented. Segmented images will activate software to extract morphological and motion-related features. The extracted features are used to search a database for matching, specific microbiota profiles in a recognition and classification step. Software will enable classification, together with the statistical data will ascertain the biological status of the water. A flizzy-logic decision tree will trigger actuator/annunciator relays that manipulate water intake valves and send signals through modems for telephone warning messages.