Railway Condition Detection in Finnish Ports

We are collaborating with different Finnish ports to deploy drones for surveillance and monitoring of cargo railway conditions. These tasks are currently assigned to port employees that need to visit the installations on a daily basis. Taking into account the cold weather conditions in Finland during a significant part of the year, the work conditions are not favourable and drones can provide an important improvement in efficiency.

By deploying semi-autonomous drones to the harbour, the monitoring frequency of critical points can be increased enabling early warnings. Moreover, drone operations are monitored from a central control center can operate on cold days and their operation is not affected by the condition of the roads and paths within the harbour.


The drones will be equipped with a full suite of sensors including cameras, and deep learning models will be trained to detect a set of predefined common problems. Employees in the control center will overview the operation and have access in real-time to video feeds from the drones.

Publications

[1] Jorge Peña Queralta, Cassandra McCord, Tuan Nguyen Gia, Hannu Tenhunen and Tomi Westerlund, "Communication-free and Index-free Distributed Formation Control Algorithm for Multi-robot Systems", Procedia Computer Science , Elsevier (2019) . The 10th International Conference on Ambient Systems, Networks and Technologies (ANT). (View) (Download) (Researchgate)