A recent software publication from the Department of Software Engineering, members of MYDASS Research Group and the OnTheEdge R&D Project, at the University of Granada, titled RouteRecoverer, presents an advanced tool designed to address a common issue in License Plate Recognition (LPR) systems—missing or incorrect data due to errors in detection. The authors, Alberto Durán-López, Daniel Bolaños-Martínez, Luisa Delgado-Márquez, and María Bermúdez-Edo, developed this tool to help recover noisy or incomplete LPR data and reconstruct vehicle routes accurately.
Key Features of RouteRecoverer
The software offers the ability to recreate routes of vehicles by filling gaps in LPR data, especially when sensors fail to capture a complete journey. For example, if a vehicle is detected by LPR cameras A and C, but not by B, the tool can infer the missing segment and recreate the full route. RouteRecoverer uses distance algorithms like Levenshtein and Damerau-Levenshtein to correct errors in license plate numbers and improve the accuracy of vehicle tracking. This makes it a valuable asset for studies in traffic management, tourism, and urban planning.
Impact on Smart Villages
The software was tested in rural areas, particularly in the Alpujarra region, where LPR data often encounter connectivity issues. RouteRecoverer not only recovered around 88% of erroneous plates but also helped classify vehicles into different visit types, such as day visits, short stays (1-5 nights), and extended visits (more than 5 nights). This classification is crucial for local authorities, as it enables better decision-making for managing tourism and adjusting resources based on visitor behavior. Longer stays, for example, tend to have a higher economic and resource impact, so distinguishing between visit types is essential for sustainable management.
Collaborative Research and Future Directions
The tool is part of a broader interdisciplinary project involving the MYDASS Research Group at the University of Granada, funded by various European initiatives. The project reflects the growing importance of integrating technology into rural and touristic areas for smarter infrastructure. The authors acknowledge that further scalability tests are required to adapt RouteRecoverer to more complex environments like urban areas with a larger number of LPR cameras and potential routes.
Reference
Durán-López, A., Bolaños-Martinez, D., Delgado-Márquez, L., & Bermudez-Edo, M. (2024). RouteRecoverer: A tool to create routes and recover noisy license plate number data. Software Impacts, 20, 100636. https://doi.org/10.1016/j.simpa.2024.100636
