Riverbank Monitoring using Image Processing for Early Flood Warning System via IoT

Abstract

This paper is presented a system that monitor the river water level by using computer vision with image processing and IoT. This system is developed to detect riverbank level and river water level by applying image processing where edge detection technique is applied on both images captured by video camera. The flood severity level is determined by comparing the river water level and the riverbank level. Then, the determined flood severity is upload to IoT platform. A notification is sent the people when the flood severity level reached certain critical level via Telegram app which one of the social media applications. The available Raspberry Pi 3 Model B is usedas a controller in this system hardware device with the Raspberry Pi 5MP camera module.The IoT platform used is Ubidots where the user can be notified through it. The main contribution of this work is on the integration of computer vision with IoT Cloud as an early flood monitoring system in responding to climate change by determining the flood severity level and alert the community on the flood severity condition. Experimental results shown that it is viable approach to combine computer vision with an artificial intelligent image processing and the IoT Cloud platform. The work makes a comparison of the Canny Edge Detection technique and the threshold technique for determining the water level and the river bank level. This system also had been tested in lab (indoor) environment and outdoor environment to check the suitability of this system to operate at the real environment.

A Systematic Review of Existing Early Warning Systems’ Challenges and Opportunities in Cloud Computing Early Warning Systems

“…In terms of tsunamis, an EWS named INSPIRE leverages cloud computing capability for the simulation of tsunamis [91]. With respect to flood, computer vision with image processing functionality was embedded in an IoT cloud platform for flood prediction [92]. It can be identified from the reviewed literature that few EWSs deployed on the cloud computing environment could not specifically indicate the service infrastructure, either IaaS, PaaS, or software as a service (SaaS).…”

IoT Based Greenhouse Condition Monitoring System for Chili Plant Growth

“…The Ubidots IoT Cloud platform is already used in various IoT application such as in alert on LPG gas leakage [16,17]. It provides internet of things (IoT) platform that can link the hardware and software for monitoring, controlling and automatic process for riverbank monitoring [18]. The IoT based greenhouse [19][20][21] with adoption of machine learning also had been presented in previous studies.…”

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

“…As of 2020, the number of interconnected IoT devices is estimated to be 10 billion, and it is expected to grow to 22 billion by 2025. Soh et al [ 17 ] presented an architecture where camera-equipped IoT devices capture river water levels and compare them to the riverbank level. When the flood severity reaches a critical level, an alert is sent to the threatened community via social media (Telegram App).…”