| dc.description.abstract | The cargo transport represents the largest share of logistics costs in most companies. Thus, companies are investing in monitoring and tracking systems aiming at improving services, reducing costs and ensuring the safety in cargos transports. This dissertation presents the SafeTrack, a model for logistics tracking and monitoring focused on safety during the distribution of cargo. The proposed model identify in real time possible thefts of carrier vehicles and cargo carried. Furthermore, it allows transport companies to track and to get realtime information about carrier vehicles and cargo. The SafeTrack presents an automatic travel management to initialize and finalize travels without requiring user interaction. Furthermore, it provides a mechanism to monitor detours in planned routes and to send alarms notification through mobile devices. To build that mechanism were studied Geofence concept and existing techniques to prepare two solutions that enable discover continuously the occurrence of deviations of planned routes. Those solutions were compared and discussed. A component named SafeDuíno was developed to make the control of inputs and outputs of cargo on the vehicle. The decision on the occurrence of inconsistencies during the logistic flow is performed through the fusion of contexts information obtained from SafeDuíno and a mobile device. The information used are: event of input / output load, date and time of the occurrence, EPC code of load and GPS coordinates at the time of the event. A functional evaluation was also performed, in which a test scene was executed twenty times, showing that the proposed model has a good efficiency rate. In addition, we provide an impact analysis regarding GPS precision and battery power consumption. After the tests, we concluded that the proposed model generates a reliable system for tracking vehicles. | en |
