Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  analyze the use of a WiFi network deployed in a large-scale technical university. To this extent,  leverage three eks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then,  search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely,  ansr the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results.
['Alessandro Redondi', 'Matteo Cesana', 'Daniel M. Weibel', 'Emma Fitzgerald']
I am writing a research paper on a idea Understanding the WiFi usage of university students
[{"from": "human", "value": "I am writing a research paper on a idea Understanding the WiFi usage of university students"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  analyze the use of a WiFi network deployed in a large-scale technical university. To this extent,  leverage three eks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then,  search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely,  ansr the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results."}]