Analysing the Needs of Homeless People Using Feature Selection and Mining Association Rules
- Resource Type
- Conference
- Authors
- Alcalde-Llergo, Jose M.; Garcia-Martinez, Carlos; Vaquero-Abellan, Manuel; Aparicio-Martinez, Pilar; Yeguas-Bolivar, Enrique
- Source
- 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), 2022 IEEE International Conference on. :568-573 Oct, 2022
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Extended reality
Neural engineering
Europe
Metrology
Feature extraction
Software
Mobile applications
AI for inclusivity
Feature selection
Association rules
Homelessness
Data collection
- Language
Homelessness is a social and health problem with great repercussions in Europe. Many non-governmental organisations help homeless people by collecting and analysing large amounts of information about them. However, these tasks are not always easy to perform, and hinder other of the organisations duties. The SINTECH project was created to tackle this issue proposing two different tools: a mobile application to quickly and easily collect data; and a software based on artificial intelligence which obtains interesting information from the collected data. The first one has been distributed to some Spanish organisations which are using it to conduct surveys of homeless people. The second tool implements different feature selection and association rules mining methods. These artificial intelligence techniques have allowed us to identify the most relevant features and some interesting association rules from previously collected homeless data.