随着探测技术的发展和大型室内场景的增多,室内定位技术已经在人们的生产生活中占据着不可替代的地位。大到军事、电力生产、医疗卫生、化工制造、交通物流和餐饮服务等领域,小到地下室、矿井和停车场等场所,各种室内定位技术展现着不同的优势。本文选取定位精度较高、安全度高、功耗及成本较低且组网方便的ZigBee定位技术。目前基于RSSI(Received Signal Strength Indication)接收信号强度指示的室内定位方法有邻近探测法、质心定位法、多边定位法、三角定位法、极点法和位置指纹定位法等。本文选取的基于位置指纹的定位算法,因其定位精度最高深受科研团队的喜爱,目前已经形成了NN、KNN和WKNN等多种公共认可的相似度匹配算法。本文主要研究和创新内容如下:(1)构建RSSI概率分布模型,对RSSI概率特征进行了系统的分析,并且在指纹库的优化处理时,使用了马氏距离与卡尔曼滤波对指纹库进行多次过滤。(2)提出了改进EMD距离的G-EMD、SG-EMD和DSG-EMD算法,对EMD距离进行了贪心、排序和动态排序的处理,有效的提升了定位的精度。(3)提出了基于RSSI特征值融合匹配的CPA-WKNN算法,其核心思想是利用不同RSSI特征值的优势,根据实时采集到的数据波动情况动态选取RSSI概率特征和RSSI平均数特征进行融合匹配。(4)实现了基于javaweb的位置指纹在线定位系统,对比WKNN算法和CPA-WKNN算法的真实定位效果,并可以实时监测RSSI波动和绘制行走轨迹。在仿真环境下,对比了预处理阈值、噪声强度和K值选取对定位效果的影响。当K值选取为8时,DSG-EMD算法得到了最高的平均定位精度,达到了0.62m,较WKNN算法精度提升了0.3m。然后在理想和复杂环境下,对比了WKNN、DSG-EMD和CAP-WKNN算法的定位效果,证明DSG-EMD算法更适用于理想环境,而CPA-WKNN算法更适用于复杂环境。在真实环境下,对比了KNN、WKNN、SG-EMD、DSG-EMD以及CPA-WKNN算法的定位精度,本文提出的DSG-EMD算法和CPA-WKNN算法较WKNN算法的平均定位精度分别提升了0.04m和0.07m,2m以内的累计误差概率分别达到了92%和96%。
To achieve the intelligent, scientific management of the family pot, we design a remote intelligent watering system based on Internet of things. Firstly, the collection system of potted environment information is cons...
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ISBN:
(纸本)9781450376228
To achieve the intelligent, scientific management of the family pot, we design a remote intelligent watering system based on Internet of things. Firstly, the collection system of potted environment information is constructed by using soil moisture sensor and air temperature and humidity sensor. Secondly, based on STM32 microcontroller, ESP8266WIFI module and Internet of things technology, the potted information and watering command transmission system is realized. Finally, the web page of the system is developed by using javaweb technology and Mina communication framework to achieve the fundamental purpose of real-time display of potted environment information and remote intelligent watering. Tests show that the remote intelligent watering system works stably and has strong practicability, which ensures the healthy growth of family green plants.
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