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This research realizes the multi-agent community to handle the rinsing challenges in smart cities by the combined use of multi-fuzzy-agent systems for extracting relevant data from big noisy data, and the multi-agent systems-of-systems for adaptive big data processing. A multi-agent-based large wireless sensor network is used to show the approach used by the multi-fuzzy-agent systems, it exploits sensors as autonomous fuzzy agents that measure the relevance of the collected data and eliminate irrelevant ones. The aim of the multi-agent systems-of-systems is to handle the super velocity of big data flood in an adaptive way, which break down the rigidity of current big data systems that are forced to restart the data analysis process periodically to integrate the newly generated data into the analytical cycle.

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