The main building blocks of our system are as follows:

• IoT data collection: This block includes IoT devices (such as drones, cameras, cameras, and water sensors) that will collect data (e.g., images of animals, plants, water level, turbidity, temperature, CO2, and other parameters) in all areas of the Tram Chim ecosystem. Data will be collected continuously, stored in the cloud, and processed in real time to provide updates on the state of the Park’s ecosystem.
• AI/ML data processing and classification: This block includes a series of image processing algorithms and models and AI/Machine Learning, which automatically process and analyze data to generate various insights, such as counting animals and species, classifying plants and identifying them in different states, and determining the water level in different areas of the Park.
• Digital AI-powered dashboard: This block can be easily accessed by various stakeholders of the Park (such as rangers, managers, and researchers) through common computing devices (such as personal computers, mobile phones, or tablets) to support decision making. The digital console will also provide a clear demonstration of how management interventions impact key indicators of the Park’s ecosystem health. In addition, the console will be able to issue warning messages to users/administrators in case of danger such as fire, low water level or high salinity.

This product represents a major digital transformation in the management of complex wetland ecosystems. This system will be the first of its kind in Vietnam. Specifically, it addresses the following:

• Leveraging hyper-connectivity through IoT infrastructure development, including drones, sensors, digital console, and cloud storage. This structure is powered by AI and Machine Learning, which analyzes Big Data collected by IoT devices. This infrastructure is innovative and does not exist in Tram Chim or any other National Park in Vietnam.
• Enhancing opportunities for “sharing” through the public provision of the system framework and environmental data collected from the system to the country and the international community for sustainable research and development, resulting in global impacts.
• Developing new and more effective business models for the environmental management of Tram Chim National Park and wetland landscapes through data-driven decision-making approaches.
• Improving productivity and efficiency by reducing the labor costs of manually collecting, processing, and classifying data to monitor the health of the Park’s ecosystem. These pieces of work are now automated by using reliable AI technologies. Promoting the more comprehensive, sustainable development of Tram Chim National Park and wetland ecosystems, thus improving the health of animals and people in the local area.

Currently, the project is implemented under the cooperation between University of Technology – VNUHCM, Tram Chim National Park and the University of Wollongong, Australia. The product is being deployed and operated onsite at Tram Chim National Park. The entire operation procedure of the product has been transferred to Tram Chim National Park to operate and manage the Park. The technology to build IoTs monitoring stations and AI camera stations is owned by University of Technology, VNUHCM and ready to be transferred to interested organizations and local agencies for implementation. Bird recognition and fire alarm technology based on machine learning developed by the University of Wollongong have also been completely transferred to the research team of University of Technology, VNUHCM and ready to be transferred to other interested agencies and National Parks.