Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

A Geographic Information System Mobile Application for Road Traffic Crash Data Collection, Management and Analysis

Domain:

mobilitygeospatial

Record type:

software
Creator:
JudManAdeMos
Publisher:
Uni
Host:
The study addressed the issue of road traffic crashes in developing countries like Nigeria by developing a mobile app called Geographic Information System-Road Traffic Crash Data (GIS-RTCD). The app developed and tested in Southwest Nigeria is designed to transform the collection and management of real-time road traffic crash data by replacing the traditional paper-based method known for its imprecise, missing, contradictory, and disparate data. The app, accessible on Android and iPhone platforms, uses an Epicollect5-implemented mobile user interface, web server, PostgreSQL-based database, Apache Tomcat/Geoserver application/GIS server, and OpenLayers-implemented web service for map data visualization. The app provides precise crash location determination through GPS/geospatial mapping, digitally structures data collection, prevents data duplication, and eliminates labour-intensive tasks associated with manual data processing. The study recommends replacing manual crash data recording systems in Nigeria with the GIS-RTCD app to standardize crash data records and enhance comprehensive data collection for national analysis and research.

Visit

doi.org

Similar

Self-design mobile agent based approach for road traffic data collectionNigerian Multi-modal Road Traffic Crash DataDesign and implementation of an offline-first road crash data collection systemApplication of Linear Probability Model to Road Traffic Crashgbenaedem-cell/Road-Traffic-Crash-Analysis-in-Nigeria-Case-2021---2023A Georeferenced Incident-Level Road Traffic Crash Dataset for Nigeria (2015–2024)

Self-design mobile agent based approach for road traffic data collection

Today, the collection of high-quality

Nigerian Multi-modal Road Traffic Crash Data

This is a Nigerian multi-modal road traffic crash (RTC) dataset curated from the Nigerian RTC corpus

Design and implementation of an offline-first road crash data collection system

Road traffic accidents (RTAs) are a global burden that particularly affects people in developing cou

Application of Linear Probability Model to Road Traffic Crash

Road traffic crashes remain a critical public health and safety concern, particularly in developing

gbenaedem-cell/Road-Traffic-Crash-Analysis-in-Nigeria-Case-2021---2023

This project analyzes road traffic crash occurrences in Nigeria from 2021 to 2023 using quarterly ro

A Georeferenced Incident-Level Road Traffic Crash Dataset for Nigeria (2015–2024)

This is an artificial intelligence (AI)-ready dataset of road traffic crash (RTC) incidents in Niger