| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
In this research and development, we developed a prediction method of wireless communication quality by using multi-dimensional time-series data and a high-speed and energy efficient content delivery method. The prediction method can achieve prediction of future communication quality by constructing a deep learning-based regression model from multi-dimensional time-series data such as mobile throughputs, RSSI, GPS, and other sensing information. The content delivery method can achieve providing high-speed and energy efficient content delivery by using communication quality map and moving route search method. We developed the protype application and evaluated the performance by carrying out a field experiment around Waseda University.
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