The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

中文翻译：

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基于人群轨迹数据分析的森林路径状况监测

近年来，基于移动人群感知（MCS）范式的道路信息采集系统（RIAS）的开发已得到广泛研究。从这个意义上讲，大多数现有的基于MCS的RIAS都集中在城市道路网络上，并采用了基于汽车的方案。但是，缺乏关注乡村和乡村道路网络的方法。从这个意义上说，森林小径被许多不同的人用于广泛的娱乐和体育活动，它们也可能受到各种问题或阻碍它们的障碍的影响。因此，这项工作引入了SAMARITAN，这是一个基于MCS的农村公路网络监控框架。SAMARITAN分析了从健身应用程序Strava中提取的骑自行车者的时空轨迹，以发现目标道路网中的潜在障碍。