| Project/Area Number |
18K13838
|
|---|
| Research Category |
Grant-in-Aid for Early-Career Scientists
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
Basic Section 22040:Hydroengineering-related
|
|---|
| Research Institution | Osaka University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2018-04-01 – 2020-03-31
|
| Project Status |
Completed (Fiscal Year 2019)
|
| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
|
|---|
| Keywords | 河面観測システム / AIを利用したカメラ画像解析 / スカム動態予測モデル / 感潮河川 / 浮遊汚泥スカム / 現地調査 / 画像解析 / 数値シミュレーション |
|---|
| Outline of Final Research Achievements |
In urban rivers where sewer sewage overflows, a large amount of suspended sludge (scum) floats on the river surface after rainfall. Since scum adversely affects the aquatic ecosystem and living environment, an urgent solution is strongly desired. The purpose of this study was to clarify the dynamics of scum in urban tidal river networks and to propose concrete solutions.
By constructing a river surface observation network using multiple fixed-point cameras and performing analysis using AI that can continuously and quantitatively identify scum from camera images, the behavior characteristics of scum and the location of floating / occurrence were clarified. In addition, a prediction model of scum dynamics based on a particle tracking model was developed, and it was possible to estimate the points at which scum easily occurs and accumulates.
|
| Academic Significance and Societal Importance of the Research Achievements |
本研究は実態が不明なスカムの動態を明らかにし，解決策を提案することを目標としており，現地調査やAI，数値流動モデルなどを駆使して取り組んだ．得られた知見は，実際の行政施策にも活用されるよう，河川管理者（大阪府）に積極的に情報提供を行った．実際に，府のスカム対策部会が新たに立ち上げられるなど，スカム問題の解決に向けた取り組みが活発化しており，本研究の成果も活用して具体的な対策が講じられている．
|
