An open architecture framework for intelligent multisensor integration in an industrial environment is being developed. This framework allows for the computational evaluation and understanding of sensor uncertainty and data validity through the comparison of sensor data in a common format. A logical sensor model is used to represent both real and abstract sensors within the architecture. This allows for the unobtrusive addition or replacement of sensors. All logical sensor outputs are accompanied by a corresponding confidence level. These confidences are used to dynamically allocate valid sensor readings for use by higher-level sensors. Sensory information is passed to an inference engine which uses user- selectable and adjustable fuzzy logic and/or neural network modules to provide the required decision making intelligence. This architecture may be applied to a broad range of industrial applications, especially those involving non- uniform product grading.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.