A Semantic-Associative Computing System with Multi-Dimensional World Map for Ocean-Environment Analysis

摘要

Semantic computing integration with deep-learning realizes a new artificial brain-memory system. We have presented a concept of "MMM: Semantic Computing System" for analyzing and interpreting environmental phenomena and changes occurring in the oceans and rivers in the world. We also introduce the concept of "SPA (Sensing, Processing and Analytical Actuation Functions)" for realizing a global environmental system, to apply it to Multi-dimensional World Map (5-Dimensional World Map) System. This concept is effective and advantageous to design environmental systems with Physical-Cyber integration to detect environmental phenomena as real data resources in a physical-space (real space), map them to cyber-space to make analytical and semantic computing, and actuate the analytically computed results to the real space with visualization for expressing environmental phenomena, causalities and influences. This paper presents integration and semantic-analysis methods for KEIO-MDBL-UN-ESCAP Joint system for global ocean-water analysis with Coral-Image Analysis in two environmental-semantic spaces with water-quality and image databases. We have implemented an actual space integration system for accessing environmental information resources with water-quality and image analysis. We clarify the feasibility and effectiveness of our method and system by showing several experimental results for environmental medical document databases. Environmental-semantic space integration realizes deep analysis environmental phenomena and situations. The essential computation in environmental study is context-dependent-differential computation to analyze the changes of various situations (air, water, C02, places of livings, sea level, coral area, etc.). It is important to realize global environmental computing methodology for analyzing difference and diversity of nature and livings in a context dependent way with a large amount of information resources in terms of global environments. In the design of environment-analysis systems, one of the most important issues is how to integrate several environmental aspects and analyze environmental data resources with semantic interpretations. In this paper, we present an environmental-semantic computing system. Our environmental-semantic computing system realizes integration and semantic-search among environmental-semantic spaces with water-quality and image databases.