IoT-Based Flood Monitoring System

This project focuses on developing an IoT-based flood monitoring system designed to provide real-time information to communities near rivers. The system comprises key components, including a rainfall sensor to measure rainfall intensity, a flow meter to gauge water flow rate, and a NodeMCU that facilitates communication with an Arduino Uno for data processing.

Data collected from these sensors is transmitted via WiFi and stored in the cloud for easy access. The system features a web application that displays flood risk information, enabling residents to take necessary precautions. The benefits of this project include enhancing community awareness of flood risks, supporting disaster mitigation efforts, and aligning with Sustainable Development Goals (SDGs).

Overall, the IoT-based flood monitoring system is a vital tool for improving disaster preparedness and resilience in Indonesian communities, providing timely information to minimize flood-related losses and fostering collaboration among stakeholders for a safer environment.

This project aims to develop an IoT-based flood monitoring system that provides real-time information to communities living near rivers. By utilizing sensor technology, this system can detect rainfall and water flow, delivering crucial data to help anticipate flood risks.

Key Components

Rainfall Sensor
Measures rainfall intensity by counting the number of "tips" to determine the rainfall in millimeters.

Flow Meter
Measures water flow rate in liters per hour using a flow meter sensor that reads pulses from the water flow.

NodeMCU and Arduino Uno
NodeMCU communicates with Arduino Uno via serial communication using SoftwareSerial to process data from the sensors.

WiFi and HTTP Request
Sensor data is transmitted to the server via a WiFi connection using the HTTP protocol and stored in the cloud for easy access.

LCD Display
Displays water flow information on an I2C LCD screen to provide real-time data visualization.

Main Features

Rainfall Measurement:
The rainfall sensor detects "tips" that occur, and the data is converted to millimeters to calculate total rainfall.

Water Flow Measurement:
The flow meter sensor calculates the water flow rate based on the pulses detected and sends the results via serial communication to the NodeMCU.

WiFi Connection and Data Transmission:
NodeMCU connects to a configured WiFi network and sends rainfall and flow rate data to the server using HTTP GET requests.

Code Structure

Flow Meter

• Connected to pin 2 to detect pulses.
• Pulse data is accumulated every second, converted into a flow rate in liters per hour, displayed on the LCD, and sent to the server.

Rainfall Measurement

• Utilizes an interrupt on GPIO14 to detect "tips" from the rainfall sensor.
• The number of tips is multiplied by a constant (millimeters_per_tip) to measure rainfall in millimeters.

WiFi Connection

• NodeMCU connects to the WiFi network and sends data to the server using WiFiClient.

Serial Communication

• NodeMCU communicates with Arduino Uno through pins D1 and D2 (SoftwareSerial).

Benefits and Outcomes

Benefits

• Provides essential real-time information on rainfall and flood potential, allowing communities to prepare more effectively.
• Increases community awareness of flood risks and the importance of disaster mitigation.
• Supports government and organizational efforts to achieve Sustainable Development Goals (SDGs), particularly related to sustainability and disaster resilience.

Outcomes

The project is expected to produce:

• A system that operates effectively and reliably in delivering timely information.
• Historical data storage and provision for further analysis, which will be invaluable for planning and decision-making in disaster mitigation.
• Online accessibility that enhances community engagement in flood risk management.

Conclusion

The development of this IoT-based flood monitoring system is a crucial step in addressing the flood challenges in Indonesia. By providing fast and accurate information access, this project aims not only to minimize flood-related losses but also to raise community awareness of existing risks. The implementation of this technology is anticipated to serve as a model for other monitoring systems, fostering collaboration among students, communities, and stakeholders to create a safer and more sustainable environment. Through ongoing research and innovation, we can mitigate disaster impacts and enhance community resilience to climate change.