The Intelligent System to Forecast and Manages Saltwater Intrusion and Flash Floods for Agriculture, Water Transportation and Community

The problem of saltwater and flash floods devastates the world’s food security. Statistics indicate that agricultural crop yields are affected by saltwater intrusion up to 20% of the land area, with projections reaching 50% by 2050. Flash flood problems have affected the settlement of people in agricultural and community areas. The Intelligent Systems to Forecast and Manage Saltwater Intrusion and Flash Floods for Agriculture, Water Transportation, and Community was developed to address these problems with adequate early warnings and water management. The accuracy of the innovation to forecast saltwater intrusion and flash floods one day and one week earlier, with 70% and 90%, respectively. A smart innovation guaranteeing sustainable agricultural production, global food security and sustainable cities and communities.

The idea came from knowledge and experience with how climate change has caused saltwater intrusion and flash floods that have affected Bangkok's agriculturalists, water communication, and communities. I have developed a satellite communication system and artificial intelligence to address this issue globally, including in remote areas and for general use.

The problem of saltwater and flash floods devastates the world's food security. Statistics indicate that agricultural crop yields are affected by saltwater intrusion up to 20% of the land area, with projections of reaching 50% by 2050. Researchers have developed a satellite communication system combined with artificial neural networks and satellite imagery to address these global environmental problems with adequate early warnings and water management. The study includes 1) developing a collecting data system with satellite communication technology. This involved the development of a Buoy, a Network System, and a Satellite Communication System for monitoring saltwater intrusion and flash floods. 2) Development of data analysis and forecast systems using artificial neural networks. 3) Development of early warning and water management systems for agriculture, transportation, and community. The system integrates water management with artificial neural networks. Developing a water region analysis system using satellite imagery further enhanced the ability to assess the damage to agricultural production and the economy. An early warning system for saltwater intrusion and flash floods was developed to help the general public effectively plan and prevent the problem of saltwater intrusion and flash floods. From the development of data analysis and forecast systems using artificial neural networks, researchers found that the LSTM (Long Short-Term Memory) neural network architecture can accurately forecast saltwater intrusion and flash floods one day and one week earlier, with an accuracy of 70% and 90%. The Mean Square Error was below 0.02 and 0.023 meters, indicating high accuracy and allowing the agriculturist to know the problem earlier and enable them to plan water management effectively, using agricultural and flash flooded area analysis systems. From the development of identifying agricultural areas and flooded area from satellite images system, researchers found that the Mask RCNN neural network architecture can accurately identify agricultural areas with an accuracy rate of 58.1%. This enables farmers, water commuters, and communities to address the issue of flash floods and plan efficient water management strategies. Regarding developing an early warning and water management system, the system was designed to be easily installed and connected to the neural network. In conclusion, the satellite communication system combined with artificial neural networks provides an intelligent and efficient worldwide early warning and water management system, guaranteeing sustainable agricultural production and global food security.