Railroad Artificial Intelligence Intruder Learning System (RAIILS) - Phase I

Concept of RAIILS project
 Concept of RAIILS project shown above


The goal of RAIILS is to evaluate the effectiveness of AI-based tools for reducing trespass events on rail properties.

AI Detection of railroad intruders
 AI detection of trespassers


  • Michigan Tech is using AI and edge-computing framework to improve response times and reduce bandwidth requirements.
  • The prototype system will consist of an integrated camera/CPU module capable of being either pole or drone mounted.
  • Michigan Tech is also conducting interviews with government and industry stakeholders to understand the needs and challenges posed by trespassing on rail properties.
Raspberry Pi and camera module
Raspberry Pi and 5MP camera module used for initial prototype.

Preliminary Results

The project team’s efforts so far have resulted in being able to demonstrate real-time person detection at ~1Hz using a Raspberry Pi + 5MP camera module.
The total cost of this package was less than $100, making it a cost-efficient solution for widespread deployment.

The team is currently working on real-time (i.e, 15Hz) person detection using joint thermal + optical data and an NVIDIA development board.
Because data is only transmitted when a detection is made,
this is system amenable to deployment in conjunction with ubiquitous
(albeit low bandwidth) cell networks.

Xavier developer board and FLIR Duo Pro camera being used for current experiments.
 Xavier developer board and FLIR Duo Pro camera being used for current experiments.