Objective
IWARD targets mainly hospitals and healthcare centres to overcome the shortages of healthcare staff - a major issue in European healthcare. Our aging society and economic pressure increase the patients-to-medics' ratio, having an adverse effect on healthcare quality and performance. Not being able to attend all patients at the right time and not keeping the hospitals clean enough (e.g. MRSA Transmission) also increases recovery time and cost.
To improve the quality of healthcare, these focal issues emerge: fast identification and location of patients needing immediate attention; reduction of human errors; effective cleaning in hospitals; wider reach of specialist medics, possibly attending patients remotely. To achieve this, IWARD presents a robot swarm delivering support to oversee activities in healthcare environments, providing a multipurpose, cost-effective and scalable solution to enhance quality of healthcare.
Four major tasks are: attendance, recognition, communication and support (assisting/cleaning). Attendance means to monitor hospital wards by robots acting as a dynamic swarm. Recognition points out, that the swarm is able to recognize patients or objects needing attention, providing immediate information about the location and needs of the concerned patients. The robots can be equipped with different adaptable hardware components for floor cleaning and delivery of food, linen, medicine etc. All mobile robots are capable of providing patients and visitors with guidance and information. It provides easy to use but high tech interaction interfaces like voice control through mobile and fix-mounted robots.
The swarm based approach unburdens the nursing staff from the details of robot control and central coordination - reducing the complexity of robot control to that of a chat, having the swarm negotiating which robot to use for each job, shortening the reaction time, reducing human error and increasing efficiency to deliver better patient care.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health scienceshealth sciencesnursing
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsswarm robotics
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Topic(s)
Call for proposal
Data not availableFunding Scheme
STREP - Specific Targeted Research ProjectCoordinator
79108 MÜNCHEN
Germany