| 基于层次分析法的屋顶绿化智慧管理系统 |
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| 引用本文： | 罗恒,邹优敏,陈扬,陆家欣,郭爱煌,李慧.基于层次分析法的屋顶绿化智慧管理系统[J].应用声学,2017,25(11). |
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| 作者姓名： | 罗恒 邹优敏 陈扬 陆家欣 郭爱煌 李慧 |
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| 作者单位： | 苏州科技大学江苏省建筑智慧节能重点实验室,苏州科技大学江苏省建筑智慧节能重点实验室,苏州科技大学江苏省建筑智慧节能重点实验室,苏州科技大学江苏省建筑智慧节能重点实验室,同济大学电子与信息工程学院 上海,中国科学院上海微系统与信息技术研究所 上海;中国科学院上海微系统与信息技术研究所 上海 |
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| 基金项目： | 国家自然科学(61602334,61502329,61401297)；住房与城乡建设部科学技术项目(2015-K1-047)；江苏省自然科学(BK20140283)； |
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| 摘 要： | 快速的城市化进程使得当前城市普遍面临绿地面积减少、抗自然灾害能力下降等问题。针对城市资源与需求的矛盾,对现有屋顶绿化自动管理系统进行了研究,设计了一种基于无线传感器网络的屋顶绿化智慧管理系统。通过实时获取光照强度等植物生长环境参数；使用层次分析法对植物生长环境进行评估与分析,提出了量化环境适宜度指标,通过反馈控制系统,实现屋顶绿化植物的智慧管理。实验结果表明,与传统屋顶绿化方法相比较,系统可以提高24%的植物存活率,同时可实现屋顶降温20%的目标。系统具有成本低、自适应管理等优点,可以广泛应用于当前我国的城市屋顶绿化中,也可以为学界和业界的相关研究提供参考。
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| 关 键 词： | 屋顶绿化 层次分析法 智能系统 无线传感器网络 |
| 收稿时间： | 2017/8/16 0:00:00 |
| 修稿时间： | 2017/8/31 0:00:00 |
A Smart Green Roof System based on Analytic Hierarchical Process (AHP) |
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| Zou Youmin,Chen Yang,Lu Jiaxin,Guo Aihuang and Li Hui.A Smart Green Roof System based on Analytic Hierarchical Process (AHP)[J].Applied Acoustics,2017,25(11). |
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| Authors: | Zou Youmin Chen Yang Lu Jiaxin Guo Aihuang and Li Hui |
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| Institution: | JiangSu Province Key Lab of Intelligent Building Energy Efficiency,Suzhou University of Science and Technology,Suzhou,Jiangsu,China,JiangSu Province Key Lab of Intelligent Building Energy Efficiency,Suzhou University of Science and Technology,Suzhou,Jiangsu,China,JiangSu Province Key Lab of Intelligent Building Energy Efficiency,Suzhou University of Science and Technology,Suzhou,Jiangsu,China,JiangSu Province Key Lab of Intelligent Building Energy Efficiency,Suzhou University of Science and Technology,Suzhou,Jiangsu,China,College of Electronics and Information Engineering,TongjiSUniversity,Shanghai,Shanghai Institute of Microsystem and Information Technology Chinese Academy of Science,Shanghai |
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| Abstract: | With the rapid development of urbanization, problems such as reduction of green land and decrease of ability to deal with natural disaster occur. A smart green roof management system is proposed in this paper, targeting at improve the efficiency of the current management systems. Humidity, temperature as well as light intensity are measured and transmitted for further analysis with AHP, aiming at ranking the sampling environment to offer benchmark for feedback control. Experiment results show that the proposed smart system is able to improve the survival rate as high as 24% and reduce as much as 20% temperature in summer with low cost and without the involvement of people. The proposed system can be widely applied in our cities and it can also provide experience for related research home and abroad. |
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| Keywords: | Green Roof AHP Smart System Wireless sensor networks |
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