认知智能环境:一种基于概念层次和传感器数据融合的方法

F. Cicirelli, A. Guerrieri, Alessandro Mercuri, G. Spezzano, Andrea Vinci
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引用次数: 2

摘要

传感器数据融合收集了在智能环境中收集、分类和组合来自多个传感器的数据的技术解决方案,以增强对系统的了解并实现认知行为。目标是有效地管理所获得的数据,并促进认知系统的实现,这些系统可以感知环境,推理,并为达到某些目的而正确(重新)行动。无论如何,这种系统的开发需要合适的方法来处理诸如异构性、传感器/执行器管理、系统反应性、行为建模和上下文感知等问题。本文提出了一种基于概念层次和传感器数据融合的多层方法来处理上述问题。这种方法有利于分离关注点和抽象。它依赖于代理隐喻和状态图的使用。iSapiens平台被建议用于实现目的。作为一个重要的案例研究,提出了位于意大利科森扎的智能博物馆的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive smart environment: an approach based on concept hierarchies and sensor data fusion
Sensor data fusion gathers technological solutions for collecting, classifying and combining data from multiple sensors in a smart environment for augmenting knowledge about the system and realising cognitive behaviours. The goal is to make effective the management of acquired data and to promote the realisation of cognitive systems which can sense the environment, reason, and properly (re)act for reaching some purposes. Anyway, the development of such systems asks for suitable approaches able to deal with issues like heterogeneity, sensor/actuator management, system reactivity, behavioural modelling, and context awareness. This paper proposes a multi-tier approach, based on concept hierarchies and sensor data fusion, dealing with the above aspects. The approach favours separation of concerns and abstractions. It relies on the use of the agent metaphor and statecharts. The iSapiens platform is suggested for implementation purposes. As a significant case study, the development of a smart museum located in Cosenza (Italy) is proposed.
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