Publication
A Road Condition Service Based on a Collaborative Mobile Sensing Approach
| Summary: | Road pavement conditions influence the daily lives of both drivers and passengers. Anomalies in road pavement can cause discomfort, increase stress, cause mechanical failures in vehicles and compromise safety of road users. Detecting and surveying road condition/anomalies requires expensive and specially designed equipment and vehicles, that cost considerable amounts of money, and require specialized workers to operate them. As an alternative, an emergent sensing paradigm is being discussed as a promising mechanism for collecting large-scale real-world data. In this paper we describe our experience on the design, implementation and deployment of a cloud based road anomaly information management service, that combines Collaborative Mobile Sensing and data-mining approaches, to provide a practical solution for detecting, identifying and managing road anomaly information. Additionally, we identify technical challenges and propose guidelines that may help to improve this type of services and applications. |
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| Main Authors: | Soares, João |
| Other Authors: | Silva, Nuno Alberto Ribeiro; Shah, Vaibhav; Rodrigues, Helena |
| Subject: | Collaborative mobile sensing Data-mining Road anomaly detection Road condition monitoring Road condition service Road condition service architecture Engenharia e Tecnologia::Engenharia Civil |
| Year: | 2018 |
| Country: | Portugal |
| Document type: | conference paper |
| Access type: | restricted access |
| Associated institution: | Universidade do Minho |
| Language: | English |
| Origin: | RepositóriUM - Universidade do Minho |
| Summary: | Road pavement conditions influence the daily lives of both drivers and passengers. Anomalies in road pavement can cause discomfort, increase stress, cause mechanical failures in vehicles and compromise safety of road users. Detecting and surveying road condition/anomalies requires expensive and specially designed equipment and vehicles, that cost considerable amounts of money, and require specialized workers to operate them. As an alternative, an emergent sensing paradigm is being discussed as a promising mechanism for collecting large-scale real-world data. In this paper we describe our experience on the design, implementation and deployment of a cloud based road anomaly information management service, that combines Collaborative Mobile Sensing and data-mining approaches, to provide a practical solution for detecting, identifying and managing road anomaly information. Additionally, we identify technical challenges and propose guidelines that may help to improve this type of services and applications. |
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