Name: Shiva Sharma A/L Sobana Rao
Student Id: 1102181002
Topic: Early Flood Warning and Monitoring System
Course: Bachelor of Civil Engineering

 

Floods occur in our surroundings on a regular basic. The goal of this writing is to use Wireless Sensor Networks (WSN) to provide early warnings to areas that are likely to be flooded. Early Flood Warning System is an artificial intelligent system that monitors variety of natural factors in order to predict a flood. With this, we can take early precautions and reduce the damage caused by the flood. System design is the process of establishing the system's architecture, components, modules, interfaces, and data in order to meet the system's optimal requirements (Chen hang, Yen 2014). The prototype is tweaked multiple times to create a system that meets the user's needs (Barbara Haley et al 2012).

The system entails the installation of sensor nodes in flood-prone areas for real time flood monitoring and detections (D.Kumari, 2020). Microcontrollers, sensors and power supply components were among the hardware used in this process. The hardware collects the water level, pressure of water, storm water measurement to detect the levels of the flood. Furthermore, hardware includes a Wi-Fi enabled controller that connects to the server and allows data to be shared over the internet. As we know, Internet of Things (IOT) is already widely utilized around the world, and the system will display data from a web server that measures the water levels (C.K. Gomathy, 2021). If it continues to rain heavily, users may simply check the water level on their electronic gadgets from anywhere as long as they have internet connection. This approach could be improved in future by sending SMS as a warning signal to those who have not subscribed to mobile data or do not have access to internet. Finally, flood events such as flash flooding and run-off water or overflow will be successfully monitored in real-time by using this method. Besides, this will save people plenty of time to prepare against predicted flood tragedy. This technology should be tested via stimulation of several flood scenarios to really observe the results where to show it is actually efficient and accurate.