Case-Based Reasoning (CBR) In Public Health Delivery: Airborni Fungi Identification

Abstract

Human beings are exposed to aerial micro-organisms in the various fields of their personal and, or professional daily life. Some advanced communities have rules protecting employees in the workplace from biological hazards. Airborne fungi can be detected and identified by an image acquisition and interpretation system. In this paper we present a work on building an automatic cbr-bascd image interpretation system for the identification of different kinds of airborne fungi. We explain the application domain and describe the architecture of the cbr-based image interpretation system and conclude by explaining some of the advantages that a public health worker can derive from the proposed system in the cause of providing the masses with dependable health-care services.