COVIBOT: Robotic Strategies for Monitoring and Disinfection of COVID-19 environments
- Funded by Royal Academy of Engineering (RAENG)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$26,400Funder
Royal Academy of Engineering (RAENG)Principal Investigator
Cifuentes Garcia Carlos AndresResearch Location
ColombiaLead Research Institution
Escuela Colombiana de IngenieríaResearch Priority Alignment
N/A
Research Category
Infection prevention and control
Research Subcategory
Barriers, PPE, environmental, animal and vector control measures
Special Interest Tags
Innovation
Study Type
Unspecified
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Several countries are now resuming their activities after the quarantine period caused by the outbreak and rapid transmission of the COVID-19. However, several biosafety measurements, such as continuous monitoring of people, disinfection, and decontamination of environments are still required. All over the world, different robotic tools have been deployed to support these measurements, aiming to reduce the risk of infection in hazardous environments. However, these solutions are highly expensive in developing countries, and in some cases limited to local applications. Therefore, the aim of this project is to address this challenge and to control and reduce the COVID-19 transmission risk by means of developing robotic strategies for monitoring non-safety conditions related to human behaviours and, for planning processes of disinfection of outdoor and indoor environments. This project will configure an international cooperation network to generate a wider impact, which is led by the Colombian School of Engineering Julio Garavito, with leading Investigator Carlos A. Cifuentes and the University of Edinburgh support by Professor Subramanian Ramamoorthy along with researchers and clinicians from Latin America (Colombia, Brazil, Argentina and Chile). The outcomes will be validated under laboratory conditions and will be deployed as an open-source platform to ease external collaborations.