Research Article
A Smartphone Application Designed to Detect Obstacles for Pedestrians’ Safety
@INPROCEEDINGS{10.1007/978-3-030-76063-2_25, author={Marios Thoma and Zenonas Theodosiou and Harris Partaourides and Charalambos Tylliros and Demetris Antoniades and Andreas Lanitis}, title={A Smartphone Application Designed to Detect Obstacles for Pedestrians’ Safety}, proceedings={Science and Technologies for Smart Cities. 6th EAI International Conference, SmartCity360°, Virtual Event, December 2-4, 2020, Proceedings}, proceedings_a={SMARTCITY}, year={2021}, month={5}, keywords={Pedestrian safety Citizen-science Crowdsourced data collection Smart city Obstacle recognition Deep learning}, doi={10.1007/978-3-030-76063-2_25} }- Marios Thoma
Zenonas Theodosiou
Harris Partaourides
Charalambos Tylliros
Demetris Antoniades
Andreas Lanitis
Year: 2021
A Smartphone Application Designed to Detect Obstacles for Pedestrians’ Safety
SMARTCITY
Springer
DOI: 10.1007/978-3-030-76063-2_25
Abstract
Encouraging people to walk rather than using other means of transportation is an important factor towards personal health and environmental sustainability. However, given the large number of pedestrian accidents recorded every year, the need for safe urban environments is increasing. Taking advantage of the potential of citizen-science for crowdsourcing data and creating awareness, we developed a smartphone application for enhancing the safety of pedestrians while walking in cities. Using the application, citizens will monitor the urban sidewalks and update a crowdsourcing platform with the detected barriers and damages that hinder safe walking, along with their location on a city map. To help users assign the correct type of obstacle, and authorities to assess the urgency, a Convolutional Neural Network (CNN) model for barrier and damage recognition is embedded in the application. The results of a user evaluation, based on a group of volunteers who used the application in real conditions, demonstrate the potential of using the application in conjunction with a smart city framework.
