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Autonomous indoor monitoring of elderly people using a mobile platform - Belgium  

Company managed [?] Still accepting applications

Posted on : 19 June 2017

Project Description

Project
  • Video surveillance is an omnipresent technology when it comes to enhancing security and safety in the public environments.
  •  In a healthcare environment  it is an attractive technology to collect relevant physiological parameters 24 hours a day. 
  •  A fixed video surveillance system however has several important disadvantages like camera occlusion and technical limitations, mainly in range and field of view. 
  • This project proposes a new approach to overcome these drawbacks by imposing an autonomous mobile surveillance platform that enables to monitor a person. 



Following technological challenges need to be tackled:
  • A low cost mobile platform needs to be designed that enables autonomous battery charging and provides extension sockets for various sensors. 
  • For this purpose an existing open robot base will be selected that allows custom made hardware and software extensions.
  •  Important features are the integration of active sensors (that are able to change orientation) and a flexible battery charging points.
  • Surveillance sensors (camera, temperature, sound, air quality,  ...) will be selected and integrated in the platform. 
  • Important features are:a reasonable cost, degrees of freedom and an open software interface. 
  • A new path planning and navigation algorithm will be developed to ensure that the sensors collect the necessary information while avoiding collisions. 
  • The collected data will be processed to monitor physiological parameters (movement,position, eating, sleeping, fall, …) of the person. 
  • The quality of the  processed information will be fed back to the navigation/path planning algorithm to improve the sensor perception.
  • The system is designed based on a participatory, user-centered design process.


Profile
  • Master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Industrial Engineering, or an equivalent university-level degree and relevant experience
  • Strong and demonstrated computer programming skills
  • Experience and/or keen interest in machine learning
  • A creative mind 
  • An interest to engage in a participatory, user-centered design process
  • Ability to work as an independent and flexible researcher in interdisciplinary teams
  • Strong English writing and speaking skills



Offer
A fully-funded PhD position