The University Libraries at UNCG currently track the state of a computer, determining whether or not a particular computer is in use. This data is compiled into a database, and a web app pulls from this database to show a map and number of available computers. As of Fall 2017, the data had not been used to determine which computers are used more frequently, aside from counting the number of times a computer transitions into/away from the 'in-use' state. This project attempts to correlate the usage of these computers with various factors, including: campus scheduling, equipment configuration, placement, population in the library, and area weather. Using this data, this project also uses machine learning to determine the best placement of computers for future allocation, and possible reconfiguration of equipment and space.
1
stars
1
forks
source link
Introduced an issue with Hourly Columns in GSOWeather #8
PatriciaTanzer
commented
7 years ago
Believe it to be a character I forgot to copy, should have it fixed in a few minutes