Indian Journal of Science and Technology

Abstract

Objectives: (1) To solve the problem of inefficiency and inaccuracy of vehicle monitoring; (2) To propose and develop a software that will serve as the initial replacement to a man-to-man motorbike monitoring; (3) Evaluate the components of the system in terms of functionality, efficiency, and accuracy. Methods: Waterfall model was used in the system development model. The proposal is a system development and evaluation. Python 3.6 was used in program coding, the Graphical User Interface (GUI) used was Tkinter, the database was SQLite, and the image processing OpenCV was utilized. KNN algorithm was used as the machine learning technique. Using Slovin’s formula in finding the sample of respondents with 95% of confidence level and 5 % margin error, resulted 33 respondents. The survey questionnaire is ISO 9126 Quality Software as the bases for software evaluation. Frequency distribution, percentage, and weighted mean were used to interpret the data gathered from the software evaluation metrics. Findings: Using the Likert Scale System, the weighted mean of efficiency is 4.25 described as Highly Acceptable, and the weighted mean of accuracy is 4.73 interpreted as Highly Acceptable. The overall mean is 4.49 interpreted as Highly acceptable. The functionality of the software using the percentage and frequency distribution is 100% functional. The proposal is a solution for inefficient and inaccurate of motorbike monitoring. The overall interpretation can be considered as recommendation for further study and additional features for advance version of vehicle license plate recognition. Limitations or non-recognizable pieces found in the license plate can be bearable for future studies recommended. Novelty: Initial Step in replacing the man-to-man motorbike License Plate Monitoring. The Author ‘s version in developing a software that will solve the inefficient and inaccurately monitoring of the status of the congested number of vehicles passing in and out in a certain vicinity, specifically motorbikes.

Keywords: e-recognition; Motorbike; Man-To-Man Monitoring; Replacement; License Plate