基于物联网和ISM的草原生态环境监测与智能决策关键技术研究

In recent years, due to the dry climate, extensive management, overloading and overgrazing, the grassland ecological environment in the mid-western regions of Inner Mongolia Province has deteriorated increasingly, which has been seriously restricting the sustainable development of the economy and society. Accordingly, drawing lessons from the relatively matured technologies in the Internet of Things (IoT), this research will construct the architecture of monitoring and intelligent decision based on IoT and "Immune-Softman" (ISM) for the grassland ecological environment, by using the ISM as the organizational unit. Besides, the distributed Fog Computing model and algorithm base on the Multi-ISM alliance will be designed, which will combine the paradigm of the Fog Computing with the network migration and negotiation control mechanism of the ISM. Meanwhile, aiming at data sources of different levels, it will optimize the radial basis function neural network and the naive Bayesian algorithm so as to design the model and algorithm of the multi-source data fusion and mining based on the ISM. Furthermore, it will build the big data service platform of the IoT for the grassland monitoring. Selecting the "Saihan Tara" ecological Park as a research case, it will develop typical applications and try to achieve all-round monitoring, intelligent decision and risk warning in order to provide scientific basis and decision support for the high quality, high efficiency and low consumption of grassland ecological environment. The purpose of the research is to obtain advanced theory and practical technology so that they can effectively promote the healthy and rapid development of the grassland ecological environment. The achievement is of both higher practical value and better application value for promotion.

近年来，内蒙古中西部地区因气候干旱、粗放经营、超载过牧等因素，导致草原生态环境日益恶化，已严重制约了经济社会可持续发展。为此，本项目借鉴物联网中较成熟的技术，以“免疫软件人”（ISM）智能体为组织单元，构建基于物联网和ISM的草原生态环境监测与智能决策体系结构；采用雾计算范式，融合ISM的网络迁移和协商控制机制，设计基于Multi-ISM联盟的分布式雾计算模型及算法；针对不同层次的数据来源，优化径向基神经网络和朴素贝叶斯算法，设计基于ISM的多源数据融合与挖掘模型及算法；搭建草原物联网大数据服务平台，以包头市“赛汗塔拉”生态园为研究对象，研发典型应用程序，对其实现全方位监测、智能决策和风险预警等，从而为草原生态环境的优质、高效、低耗发展提供科学依据和决策支持。本研究旨在获取理论上先进、技术上实用，能有效地推动草原物联网健康、快速发展的研究成果，其具有较强的实用价值和较好的应用推广价值。

近年来，内蒙古中西部地区因气候干旱、粗放经营、超载过牧等因素，导致草原生态环境日益恶化，已严重制约了经济社会可持续发展。为此，本项目借鉴物联网中较成熟的技术，以“免疫软件人”（ISM）智能体为组织单元，构建基于物联网和ISM的草原生态环境监测与智能决策体系结构；采用雾计算范式，融合ISM的网络迁移和协商控制机制，设计基于Multi-ISM联盟的分布式雾计算模型及算法；针对不同层次的数据来源，优化径向基神经网络和朴素贝叶斯算法，设计基于ISM的多源数据融合与挖掘模型及算法；搭建草原物联网大数据服务平台，以包头市“赛汗塔拉”生态园为研究对象，研发典型应用程序，对其实现全方位监测、智能决策和风险预警等，从而为草原生态环境的优质、高效、低耗发展提供科学依据和决策支持。本研究旨在获取理论上先进、技术上实用，能有效地推动草原物联网健康、快速发展的研究成果，其具有较强的实用价值和较好的应用推广价值。