A System-on-Chip Development of a Neuro-Fuzzy Embedded Agent for Ambient-Intelligence Environments

This paper presents the development of a neuro-fuzzy agent for ambient-intelligence environments. The agent has been implemented as a system-on-chip (SoC) on a reconfigurable device, i.e., a field-programmable gate array. It is a hardware/software (HW/SW) architecture developed around a MicroBlaze p...

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Bibliographic Details
Published in:IEEE transactions on cybernetics 2012-04, Vol.42 (2), p.501-512
Main Authors: del Campo, I., Basterretxea, K., Echanobe, J., Bosque, G., Doctor, F.
Format: Article
Language:English
Subjects:
Adaptation models
Ambient intelligence
Artificial neural networks
Complexity theory
Computation
Computational modeling
Cybernetics
Data models
embedded agent
field-programmable gate array (FPGA)
Fuzzy logic
Inference
Input variables
intelligent inhabited environments
Microorganisms
neuro-fuzzy systems
Partitions
smart environments
Studies
System on chip
System-on-a-chip
system-on-chip (SOC)
Temperature measurement
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Summary:This paper presents the development of a neuro-fuzzy agent for ambient-intelligence environments. The agent has been implemented as a system-on-chip (SoC) on a reconfigurable device, i.e., a field-programmable gate array. It is a hardware/software (HW/SW) architecture developed around a MicroBlaze processor (SW partition) and a set of parallel intellectual property cores for neuro-fuzzy modeling (HW partition). The SoC is an autonomous electronic device able to perform real-time control of the environment in a personalized and adaptive way, anticipating the desires and needs of its inhabitants. The scheme used to model the intelligent agent is a particular class of an adaptive neuro-fuzzy inference system with piecewise multilinear behavior. The main characteristics of our model are computational efficiency, scalability, and universal approximation capability. Several online experiments have been performed with data obtained in a real ubiquitous computing environment test bed. Results obtained show that the SoC is able to provide high-performance control and adaptation in a life-long mode while retaining the modeling capabilities of similar agent-based approaches implemented on larger computing machines.
ISSN:1083-4419
2168-2267
1941-0492
2168-2275
DOI:10.1109/TSMCB.2011.2168516