Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A key part of achieving a reasonable Quality of Experience (QoE) for the mobile user is the ability to properly assess the quality of the available network capacity. Unfortunately, most existing techniques are ill-suited to wireless characterization, either providing fast but grossly inaccurate results or providing accurate results at the cost of time and bandwidth. To meet this need,  developed Fast Mobile Network Characterization (FMNC). FMNC operates within a b fetch and provides an accurate available bandwidth assessment within 250  ms  while consuming less than 100 KB of data. In our demo,  will show the mobile clients for FMNC including apps for Android / iOS, the server back end, and a REST API.  will also show visualization of our ongoing longitudinal dataset of nearly one hundred users.
['Lixing Song', 'Aaron Striegel']
I am writing a research paper on a idea FMNC - rapid and accurate wifi characterization: demo
[{"from": "human", "value": "I am writing a research paper on a idea FMNC - rapid and accurate wifi characterization: demo"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A key part of achieving a reasonable Quality of Experience (QoE) for the mobile user is the ability to properly assess the quality of the available network capacity. Unfortunately, most existing techniques are ill-suited to wireless characterization, either providing fast but grossly inaccurate results or providing accurate results at the cost of time and bandwidth. To meet this need,  developed Fast Mobile Network Characterization (FMNC). FMNC operates within a b fetch and provides an accurate available bandwidth assessment within 250  ms  while consuming less than 100 KB of data. In our demo,  will show the mobile clients for FMNC including apps for Android / iOS, the server back end, and a REST API.  will also show visualization of our ongoing longitudinal dataset of nearly one hundred users."}]