Graph Database-modelled Public Transportation Data for Geographic Insight Web Application

Guillermo, Marielet; Rivera, Maverick; Concepcion, Ronnie; Billones, Robert Kerwin C.; Sybingco, Edwin; Fillone, Alexis M.; Dadios, Elmer P.

doi:10.1109/snpd54884.2022.10051802

Cited by 4 publications

(1 citation statement)

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“…Big data analytics methodologies may be utilized to provide information for practical decision-making and policy development to address the issues posed by the problems of increasing traffic congestion on the roadways. Guillermo et al (2022) examined a structure for modelling information gathered from PT was developed. To connect data and enable the gathering of geographical information while traveling, the Tiger Graph system was employed, and Django Python was used as the web framework for the (geographic insight website 2020).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of public transportation system from the perspective of passengers

Krishna,

Sharma,

Jain

2023

Multidiscip. Sci. J.

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In this research, Nigeria's Akure-Owo Axis public transportation system (PTS) passenger satisfaction is evaluated. It was required because certain Nigerian urban centres’ weak transportation infrastructure made it difficult for people, products, and services to move freely. Meanwhile, the significance of public transportation resides in the basic truth that accessibility and mobility are necessary for both economic development and the effective and efficient flow of products and services in cities of many developing nations. There was discovered to be twelve bus services. To gather the necessary data at the terminals (Akure and Owo Park), the research used questionnaires and field observation. Passengers at the two terminals were given one hundred and twelve (112) questionnaires. Standard deviation and weighted mean were used as descriptive tools. Also utilized to provide descriptive statistics was gap analysis. The results showed that passengers were dissatisfied with the drivers' skills, the vehicle's condition, overloading and over speeding, the drivers' attitudes, the drivers' adherence to traffic laws and orders, and the cost of the trip.

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Section: Introductionmentioning

confidence: 99%