Implementing Embedded Expert Systems via Programmable Hardware

The work deals with intelligent embedded systems, particularly with the problem of application of expert systems in embedded architectures. It summarizes the state of art and challenges in areas of embedded systems and rule-based expert systems, and gives motivations for implementing expert systems in embedded architectures. We design architecture of expert system and hardware architecture of embedded system suitable for implementation of embedded expert systems. We also devise a universal representation for knowledge bases of embedded expert systems. We propose two methods of hardware acceleration of inference in embedded expert systems. One of the devised methods we experimentally evaluate and claim its remarkable contribution to inference process of expert systems and its suitability for utilization in embedded expert systems. Based on the performed experiments and acquired experience we synthesize a set of rules for implementation of expert systems in embedded architectures which contribute to the problem area of intelligent embedded systems development. The devised method for hardware accelerated inference enables implementation of expert systems even in embedded architectures where it has not been possible with the current state of art, thus facilitating further adoption of intelligent embedded systems.

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