Solving the House Numbering Problem in Nigeria: Internet of Things (IoT) As An Emerging Solution

Abstract

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.