Xian-Hao Zhang
Research Subjects
Research Interests
Xian-Hao Zhang has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Chen-Yu Wang
Department of Civil Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
1 shared publication - Kai-Yang Zhu
Chung Yuan Christian University, Taoyuan, Taiwan
1 shared publication - Shiu-Shin Lin
Department of Civil Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
1 shared publication - Yi-Chuan Liu
Department of Civil Engineering, Chung Yuan Christian University, Taoyuan 320314, Taiwan
1 shared publication
Latest Publications
- Open Access
- 5 December 2023
- Published by MDPI AG in Smart Cities
- Vol. 6 (6) , 3411-3426
Development of a Microservice-Based Storm Sewer Simulation System with IoT Devices for Early Warning in Urban Areas
This study proposes an integrated approach to developing a Microservice, Cloud Computing, and Software as a Service (SaaS)-based Real-Time Storm Sewer Simulation System (MBSS). The MBSS combined the Storm Water Management Model (SWMM) microservice running on the EC2 Amazon Web Services (AWS) cloud platform and an Internet of Things (IoT) monitoring device to prevent disasters in smart cities. The Python language and Docker container were used to develop the MBSS and Web API of the SWMM microservice. The IoT comprised a pressure water level meter, an Arduino, and a Raspberry Pi. After laboratory channel testing, the simulated and IoT-monitored water levels under different flow rates indicate that the simulated water level in MBSS was such as that monitored by the IoT. These findings suggest that MBSS is feasible and can be further used as a reference for smart urban early warning systems. The MBSS can be applied in on-site stormwater sewers during heavy rain, with the goal of issuing early warnings and reducing disaster damage. The use case can be the process by which the SWMM model parameters will be optimized based on the water level data from IoT monitoring devices in stormwater sewer systems. The predicted rainfall will then be used by the SWMM microservices of MBSS to simulate the water levels at all manholes. The status of the water levels will finally be applied to early warning.
- 5 December 2023
- Published by MDPI AG in Smart Cities
- Vol. 6 (6) , 3411-3426
Open AccessDevelopment of a Microservice-Based Storm Sewer Simulation System with IoT Devices for Early Warning in Urban Areas
This study proposes an integrated approach to developing a Microservice, Cloud Computing, and Software as a Service (SaaS)-based Real-Time Storm Sewer Simulation System (MBSS). The MBSS combined the Storm Water Management Model (SWMM) microservice running on the EC2 Amazon Web Services (AWS) cloud platform and an Internet of Things (IoT) monitoring device to prevent disasters in smart cities. The Python language and Docker container were used to develop the MBSS and Web API of the SWMM microservice. The IoT comprised a pressure water level meter, an Arduino, and a Raspberry Pi. After laboratory channel testing, the simulated and IoT-monitored water levels under different flow rates indicate that the simulated water level in MBSS was such as that monitored by the IoT. These findings suggest that MBSS is feasible and can be further used as a reference for smart urban early warning systems. The MBSS can be applied in on-site stormwater sewers during heavy rain, with the goal of issuing early warnings and reducing disaster damage. The use case can be the process by which the SWMM model parameters will be optimized based on the water level data from IoT monitoring devices in stormwater sewer systems. The predicted rainfall will then be used by the SWMM microservices of MBSS to simulate the water levels at all manholes. The status of the water levels will finally be applied to early warning.