The Implementation of an IoT-Based Flood Alert System

Shah, Wahidah Md; Arif, Fahim; Shahrin, A.A.; Hassan, Aslinda

doi:10.14569/ijacsa.2018.091187

Cited by 26 publications

(7 citation statements)

References 2 publications

(3 reference statements)

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“…Along these ideas, Shah et al [26] proposed a flood warning system built using Raspberry Pi. The Raspberry Pi is connected with several sensors such as an ultrasonic sensor, camera and rain gauge to determine the water level of the station every 10 microseconds and capture the condition of the station every 5 minutes.…”

Section: Long Range Communication (Lora)mentioning

confidence: 99%

Conceptualising flood warning system for connected vehicles

Sung,

Razak,

Yogarayan

et al. 2023

IJEECS

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Floods are a common natural hazard in Malaysia during the monsoon season. It affects millions of people each year that leads to severe deaths and infrastructure destruction. In recent time, flood warning system (FWS) has been a notable topic but it has not been extensively implemented in Malaysia. In this study, we developed a FWS that can interface with connected vehicles in order to provide alerts to drivers while also sending warnings to end users. This type of FWS enables vehicles to connect with one another within a particular radius to broadcast flood information via long range (LoRa) communication technology. When the water level rises over a certain point, the system sends a warning to drivers indicated through a mobile application. Drivers have the option to take alternative route, reducing the likelihood of damage when driving into or near a flooded area. The developed application demonstrates that the warning was able to be instantly displayed to the driver if there is a significant increase in water level. Experimental evidence shows that the driver was able to receive the water level alert and a visual interpretation of the immediate area affected by flood through the application.

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Section: Long Range Communication (Lora)mentioning

confidence: 99%

Conceptualising flood warning system for connected vehicles

Sung,

Razak,

Yogarayan

et al. 2023

IJEECS

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“…A system to detect inundation stages by measuring the upsurge in water levels and alerting local residents was proposed by Shah et al [20]. The waterfall model as a methodology with Raspberry Pi was used to gather information from deployed sensors which transmitted it to the Global System for Mobile communication (GSM) module.…”

Section: The Implementation Of An Iot-based Flood Alert Systemmentioning

confidence: 99%

Flood Monitoring and Early Warning Systems – An IoT Based Perspective

Ahmed,

Mohammed Siddique,

Mohammad Shahid Husain

2023

EAI Endorsed Trans IoT

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One of the most frequently occurring calamities around the world is the flood. For flood prone areas or countries, an essential part of their governance is flood management. The necessity to continuously review and analyse the adverse or ambient environmental conditions in real-time demands developing a monitoring system so that floods could be detected beforehand. This paper discusses different Internet of Things (IoT) based techniques and applications implemented for efficient flood monitoring and an early warning system and it is observed that in future, the combination of IoT and Synthetic Aperture Radar (SAR) data may be helpful to develop robust and secure flood monitoring and early warning system that provides effective and efficient mapping during natural disasters. The emerging technology in the discipline of computing is IoT, an embedded system that enables devices to gather real-time data to further store it in the computational devices using Wireless Sensor Networks (WSN) for further processing. The IoT based projects that can help collect data from sensors are an added advantage for researchers to explore in providing better services to people. These systems can be integrated with cloud computing and analyzing platforms. Researchers recently have focussed on mathematical modeling based flood prediction schemes rather than physical parametric based flood prediction. The new methodologies explore the algorithmic approaches. There have been many systems proposed based on analog technology to web-based and now using mobile applications. Further, alert systems have been designed using web-based applications that gather processed data by Arduino Uno Microcontroller which is received from ultrasonic and rain sensors. Additionally, the machine learning based embedded systems can measure different atmospheric conditions such as temperature, moisture, and rains to forecast floods by analyzing varying trends in climatic changes.

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“…It is observed that EWIN might offer a superior approach, since it uses faster communication protocols and a centralized information system. In another similar work, “The Implementation of an IoT-Based Flood Alert System” [ 14 ], the alert processing is made at each node. The node processing power can be a handicap in comparison with the proposed system that uses a dedicated server for such task.…”

Section: Introductionmentioning

confidence: 99%

Flash Flood Early Warning System in Colima, Mexico

Ibarreche

Aquino

Edwards

et al. 2020

Sensors

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This paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.

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The Implementation of an IoT-Based Flood Alert System

Cited by 26 publications

References 2 publications

Conceptualising flood warning system for connected vehicles

Conceptualising flood warning system for connected vehicles

Flood Monitoring and Early Warning Systems – An IoT Based Perspective

Flash Flood Early Warning System in Colima, Mexico

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