In Aug. 2019, we visited some prone places to natural disasters in Quang Nam province to check our current environment monitoring system for further upgrade and deployment plan. During this visit, we had met many local governments to discuss our plan as well as invite them to support and join the project for maximizing the achievements of the project. These activities are given in the Fig. 1 and Fig. 2 below. After this visit, we will plan to deploy the UAV network that is based on fog computing, real-time embedded optimisation, and machine learning, which can compensate for poor infrastructure in Vietnam and thus provide further improvement in system performance.
Fig. 1: Dr. Duong and Dr. Nguyen checked the current environment monitoring system
Fig. 2: Meeting with local governments in Dien Ban, Que Son, Dai Loc, and Hiep Duc Districts, Quang Nam province, for further supports
The meeting was centered on the flooding problems in the VuGia-ThuBon river basin, Quang Nam, where flash flood usually occurs, seriously affecting the life of 3 million people. Floods impact on both individuals and communities, and have social, economic, and environmental consequences. This proposed real-time flood monitoring system will enable flood forecasts with greater accuracy and longer lead times than today, thus significantly reduce immediate impacts associated with flooding such as loss of human life, damages to property/infrastructure, deterioration of health conditions owing to waterborne diseases, and long-lasting psychological impacts.
In the meeting, we demonstrated the outcomes of this project that will be sent to Quang Nam province via the partnership with DTU for further assessment and utilisation in disaster preparedness. In short term, the proposed real-time flood monitoring system will increasingly be linked to flood warning systems. Real-time flood models will be linked to interactive (internet based) maps that provide residents with detailed information on key issues such as: predicted peak flood levels, rates of rise for their location, and escape routes together with predictions of evacuation time and the provision of staggered ‘get out’ warnings to isolated residents. These systems may have a simulation capability to allow disaster training and practices.
The project team will act in transferring and UAV-based artificial intelligent (AI) to environment monitoring, disaster management in wider scope. In medium run (5-10 years), the stakeholders and related industries will unlock the huge market of UAV-based AI products and services. The project therefore rapidly will lay the initial foundation for long-term economic development in Vietnam.
Last but not least, we expect that by promoting the use of ICT (wireless communications, machine learning, IoT) in the long run (10-15 years), we will contribute to the development in Vietnam in the following ways: sustainable economic development through adopting ICT in disaster management and smart cities, increased living quality, and public health.