Forest path condition monitoring based on crowd-based trajectory data analysis

Abstract

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.

RECITE: A framework for user trajectory analysis in cultural sites

“…The advent of the Internet of Things (IoT) has come with the development of several indoor location solutions based on different wireless technologies like WiFi [37], RFID [3,18] or Bluetooth Low Energy (BLE) [17]. One of the most prominent applications of these location technologies has been the development of location-based services (LBSs) able to adapt to users' locations inside buildings [6], provide users with ambient intelligence [19] or detect incidents in road infrastructures [4]. In this context, several proposals have recently arisen in the cultural environment in order to profit from such IoT advances.…”