Kanki WATANABE

Research Topic
Development of a predictive model for the deterioration of sewage pipelines based on the quantification of specific genetic markers
Research Abstract
Based on the SDG6, water infrastructure is being implemented around the world. It is essential that the introduction of sustainable water supply and sewage systems be accompanied by appropriate asset management. Currently, however, the main means of inspecting water/sewer ducts are visual inspection using small cameras, which has problems in terms of efficiency and economy, and there is a need to develop better inspection methods. This study aims to develop an inspection method using microbial source tracking markers for sewage ducts and to construct a deterioration prediction model using a statistical method.
Members
Professor
Associate Professor
Assistant Professor
Post-Doc
Special Research Student
Ph.D.Students
- Luhur Akbar DEVIANTO
- Sewwandi BANDARA
- Aken Puti WANGUYUN
- Katayoun AMIRFARD
- Mohammadreza VESALINASEH
- Yohei MIURA
- Luyao Wang
Master Students
- Takehito IIZUKA
- Hiroki KOYAMA
- Yu-bing LI
- Shun TAKAYAMA
- Marcus SANCHEZ
- Jarin TASNIM
- Lucas MARIJANOVIC
- Anju SAWADA
- Ren SUZUKI
- YiLei WANG
- Kanki WATANABE
- Putri Shafa Kamila