Abstract
Many highly contagious infectious diseases, such as COVID-19, monkeypox, chickenpox, influenza, etc., have seriously affected or currently are seriously affecting human health, economic activities, education, sports, and leisure. Many people will be infected or quarantined when an epidemic spreads in specific areas. These people whose activities must be restricted due to the epidemic are represented by targets in the article. Managing targets by using targeted areas is an effective option for slowing the spread. The Centers for Disease Control (CDC) usually determine management strategies by tracking targets in specific areas. A global navigation satellite system (GNSS) that can provide autonomous geospatial positioning of targets by using tiny electronic receivers can assist in recognition. The recognition of targets within a targeted area is a point-in-polygon (PtInPy) problem in computational geometry. Most previous methods used the method of identifying one target at a time, which made them unable to effectively deal with many targets. An earlier method was able to simultaneously recognize several targets but had the problem of the repeated recognition of the same targets. Therefore, we propose a GNSS coordinate recognition algorithm. This algorithm can efficiently recognize a large number of targets within a targeted area, which can provide assistance in epidemic management.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.