Using Incremental Direction Searches to Stay Away from COVID-19

This research is related to the author’s actual experience about the COVID-19 pandemic. The author had to drive from Grand Forks, North Dakota to Columbus, Ohio to visit his family. Traveling via airplanes or buses was not considered because the coronavirus may prevail in small, crowded space. However, driving is not without risk since they had to stop from time to time to do the tasks like filling up the gas tank, using restrooms, or buying food. There are numerous routes from Grand Forks to Washington D.C. To reduce the risk, they tried to take a “safe” route and avoid the “hotspots” like Chicago or Minneapolis as much as possible. This research uses the technique of incremental direction searches to find the “best” routes between two locations. There are numerous routes between two distant locations. Finding the “best” route most likely is an NP-complete problem, so exhaustive methods should not be considered. This research uses the incremental direction searches to find the route. Instead of finding the route at once, the proposed method finds the next direction whenever a major intersection is encountered based on the number of COVID-19 cases on each direction. Many accomplishments will be achieved by this research. Three of them are listed as follows:
  • Finding a safe route: Numerous routes are available between two distant locations. This research finds a safe route based on the numbers of COVID-19 cases. Though it is not a proactive method, it is considered much safer than risking the possibility of getting infected by entering the high infected areas.
  • Incremental direction searches: Searching for the “best” route may not be feasible because of numerous cases. This research tries to find the best route by using incremental direction searches. Though the result may not be the global optimum, local optimum could be achieved for each intersection.
  • User privacy preservation: Another issue of location-based services is user privacy preservation, so it would not be possible to associate the users to the locations, paths, or queries. Users of this research do not need to share their information other than their current locations and destinations to the system.
Other than the above three achievements, various subjects and methods such as human travel behavior recognition and prediction, and mobile computing are studied in this research too.

COVID-19, Location-based Services, Smartphones, Mobile Computing, and Incremental Searches

WMSCI-2020-Hu.pdf and WMSCI-2020-Hu.pptx