解决尼日利亚的房屋编号问题:物联网(IoT)作为一种新兴解决方案

T. M. Okediran, O. R. Vincent, A. O. Agbeyangi, A. Abayomi-Alli, O. Adeniran
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引用次数: 0

摘要

房屋编号是为街道或区域内的每个建筑物分配唯一编号的行为,以便更容易定位特定的建筑物。由于城镇和区域规划不佳,街道命名和房屋编号是尼日利亚面临的主要挑战。缺点是无法在一个地点确定一个特定的房子。本研究的目的是利用物联网(IoT)作为解决房屋编号问题的解决方案,特别是在拉各斯州的Ojo地方政府区,通过识别街道上的房屋,对其编号,对建筑物类型进行分类,并将数据存储在数据库中。该研究采用了一种机器学习技术,即k近邻分类器,来训练和编程物联网设备,并以50所房屋作为案例研究。这项工作是用50所房子来测试的,他们给街道命名,给房子编号,并把它们分为五大类。谷歌地图的使用有助于确定街道的名称和位置。训练和测试数据的成功率高达0.97,表明所使用的技术足以解决街道名称和门牌号问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving the House Numbering Problem in Nigeria: Internet of Things (IoT) As An Emerging Solution
House numbering is the act of assigning a unique number to each building in a street or area in order to make it easier to locate a specific building. Due to poor town and regional planning, street naming and house numbering are major challenges in Nigeria. The disadvantage is being unable to identify a specific house in a location. The purpose of this study is to use the Internet of Things (IoT) as a solution to address the issue of house numbering, specifically in the Ojo Local Government Area of Lagos State, by identifying houses on the street, numbering them, classifying the type of building, and storing the data in a database. The study employs a machine learning technique, the k-nearest neighbor classifier, to train and program the IoT device, with fifty houses serving as a case study. The work was tested using fifty houses to name the street, number the houses, and categorize them into five major groups. The use of Google Maps aided in determining the name and location of a street. The success rate was as high as 0.97 for training and testing data, indicating that the technique used is adequate to address street name and house numbering problems.
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