Abstract
Participatory sensing networks rely on gathering personal data from mobile devices to infer global knowledge. Participatory sensing has been used for real-time traffic monitoring, where the global traffic conditions are based on information provided by individual devices. However, fewer initiatives address asphalt quality conditions, which is an essential aspect of the route decision process. This article proposes Streetcheck, a framework to classify road surface quality through participatory sensing. Streetcheck gathers mobile devices’ sensors such as Global Positioning System (GPS) and accelerometer, as well as users’ ratings on road surface quality. A classification system aggregates the data, filters them, and extracts a set of features as input for supervised learning algorithms. Twenty volunteers carried out tests using Streetcheck on 1,200 km of urban roads of Minas Gerais (Brazil). Streetcheck reached up to 90.64% of accuracy on classifying road surface quality.
Highlights
Streets and roads are worldwide daily popular routes for transportation, and yet, drivers face road surface conditions problems in several countries
3.1 General overview The Streetcheck framework is composed of two modules: 1 Data sourcing, an application that runs on mobile devices; and 2 A Classification system, implemented on the cloud, responsible for receiving and storing data, and subsequently, data filtering, features extraction, and classification of the data
The Softness fits the exponential model, Eq 4, with {a, b, c} = {0.812, 0.061, 0.101}. These results indicate that R-Mean Standard deviation (R-SD) and softness combined with the average speed represent good inputs for supervised learning algorithms
Summary
Streets and roads are worldwide daily popular routes for transportation, and yet, drivers face road surface conditions problems in several countries. Due to the popularity of smart devices, people are becoming "mobile sensors" capable of gathering valuable data about their environment [4] Services such as Waze and MapLink aggregate data from personal devices and provide real-time traffic information for all users. Drivers are just required to know the overall quality of the pavement instead of the IRI To fulfill this context, this article presents Streetcheck, a participatory sensing framework to classify urban road surface based on data gathered and shared by users through their devices. The mobile application forwards the information to the classification system, which aggregates, filters and classifies the raw data by using supervised learning algorithms. We considered the benefits of the aggregated information worth the collaboration, since route decisionmaking must consider road surface quality, in addition to the traffic condition.
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