MaLeStV

Project Details

Funding

FFG

Grant Number

873495

Duration

2019/09/01 - 2021/08/31

Contact

Martin Kampel

Persons

Martin Kampel
Jennifer Lumetzberger

Machine Learning of motion patterns in the penal system

The everyday life of a prison is characterised by aspects of security. A number of structural and organisational measures (prison cell design, video surveillance, …) are designed to reduce the risk of safety-related incidents in prisons and to support the personnel of the correctional system in their work. However, a permanent observation of potential endangering and endangered persons is not feasible due to limited personnel resources.

Violence in prison is no exception: suicides, for example, can be prepared and carried out in unobserved moments. Suicides in prisons often cause collateral damage beyond the tragedy of the event, ranging from increased media coverage to irritation among employees and inmates.

The project will provide important insights for the digitization of the prison regime system and offers the chance to develop highly innovative solutions from Austria for prisons worldwide.

The goals of this project are:

  1. define behavioural patterns and scenarios in prison to be detected by a 3D sensor
  2. using 3D image analysis to register behavioural patterns of people in real-time to identify critical movement patterns
  3. analyse the possibilities to support security personnel in prison by the detection of motion patterns
  4. development of a prototype

Project Partners