A meteorological station is set up in a field of green crops, likely corn, under a partly cloudy sky. The station has several sensors and instruments mounted on a tall pole, secured with metal wires. Grassy vegetation surrounds the station, and a wire fence is visible in the background.

Research

Exploring innovative methods for environmental data collection and analysis.

A person wearing a mask and an apron is closely observing a coffee roasting machine. The machine's display shows various numbers related to temperature and time, and coffee beans are visible inside. The environment suggests an industrial or professional setting with dim lighting.

A robotic outdoor sweeper is positioned on a wooden deck surrounded by lush green trees. The machine is labeled with #ROBOCLEANING and appears to be designed for outdoor maintenance.

A smartphone displaying an air quality monitoring app interface in Indonesian, featuring an AQI reading of 159, which is labeled as unhealthy. The screen is divided into sections with different readings and options, and the phone is placed on a light grey surface.

A monitor displaying a digital interface with technical data and graphics, mounted on a piece of equipment. The screen shows various colors and lines, indicating some form of technical or industrial application.

A close-up view of a digital medical monitor displaying vital signs including a green electrocardiogram (ECG) line, a yellow respiratory rate line, and numerical values with a red background indicating a concerning level.

Expected outcomes include:

1) Proposing a GPT-4-based intelligent analysis framework for environmental monitoring, significantly improving the accuracy and real-time performance of environmental data processing. 2) Developing environmental riskearly warning algorithms to enhance the proactiveness and effectiveness of environmental protection. 3) Establishing interpretable AI models to increase environmental monitoring personnel’s trust in AI technologies. 4) Achieving efficient integration and sharing of cross-regional environmental data to provide scientific evidence for the formulation of environmental protection policies. These outcomes will advance the application of AI in environmental monitoring, providing technical support for building a green and sustainable ecological environment, while offering scientific evidence for policymakers to promote the intelligence and efficiency of environmental protection efforts.