1.1 Severity and Social Impact of Ground Subsidence
Ground subsidence is becoming a serious problem worldwide due to rapid urbanization and industrialization. Ground subsidence causes building collapse, road damage, and damage to water supply and sewage facilities, resulting in not only casualties but also massive economic losses. In particular, urban areas are densely populated with various underground facilities such as subways and water supply and sewage systems, so ground subsidence is likely to paralyze social functions.

1.2 Limitations of Existing Ground Subsidence Detection Methods
Existing ground subsidence detection methods have mainly used regular ground measurement and leveling. However, these methods are time-consuming and costly, and have the disadvantage of being difficult to monitor in real time over a wide area. In addition, there are limitations in detecting subtle changes just before ground subsidence occurs.

1.3 Need for AI-based Ground Subsidence Detection Solutions
To solve these problems, ground subsidence detection solutions utilizing AI technology are attracting attention. The AI ​​solution analyzes various data to predict the possibility of ground subsidence and quickly detects early signs to support proactive response.

2. Overview of AI-based ground subsidence detection solution
2.1 Goal of the solution
This solution aims to accurately predict the possibility of ground subsidence and minimize damage by detecting early signs based on AI technology.

2.2 Key functions of the solution
Integrated analysis of various data: Integrates and analyzes various data related to ground subsidence (ground measurement data, weather data, satellite images, social network data, etc.).
Deep learning-based prediction model: Develops a high-performance model that predicts the possibility of ground subsidence using deep learning technology.
Real-time monitoring and alarm: Monitors ground conditions in real time and immediately sends an alarm to the relevant parties when the possibility of ground subsidence increases.
Generate risk area map: Creates a map of ground subsidence risk areas based on the results of the prediction model to provide visual information.
Continuous model learning and improvement: Continuously learns new data to improve the accuracy of the model.

2.3 Components of the Solution
Data collection system: Collects ground measurement data, weather data, social network data, etc. through various sensors, drones, satellites, etc.
Data processing and storage system: Preprocesses the collected data and stores it in a database.
Deep learning model: Learns ground subsidence prediction models and performs predictions in real time.
User interface: Provides a user-friendly interface so that users can easily use the system and check the results.

3. Expected effects of the solution
-Minimize ground subsidence damage: Predict the possibility of ground subsidence in advance and detect early signs to minimize damage.
-Promote social safety: Prevent paralysis of social functions due to ground subsidence and ensure the safety of citizens.
-Reduce maintenance costs: Reduce maintenance costs by performing preemptive maintenance before ground subsidence occurs.
-Increase urban development efficiency: Provides accurate information on ground stability to contribute to establishing urban development plans.

4. Conclusion
AI-based ground subsidence detection solution is an innovative technology for solving ground subsidence problems. This solution analyzes various data and uses deep learning technology to accurately predict the possibility of ground subsidence. This is expected to bring about various positive effects, such as improving social safety and reducing economic losses.