Wireless sensor network based flood/drought forecasting system

Khan, Feeza; Memon, Saira; Jokhio, Imran Ali; Jokhio, Sana Hoor

doi:10.1109/icsens.2015.7370354

Cited by 14 publications

(4 citation statements)

References 7 publications

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“…Flood/Drought Forecasting System (FDFS) [12] is developed to help the authorities in generating early warnings for flood or drought. WSN is used in collecting data as input for the system.…”

Section: Flood Simulation Methodologiesmentioning

confidence: 99%

“…These data become an input to various flood application systems [2]- [9]. Flood prediction is one of the most critical application that can help to predict flood occurrences and once a flood is predicted to occur, an alert can be sent to the people living in the respective area [12]. An accurate and early flood detection is crucial and has the potential to save lives.…”

Section: Iot-based Wsn In Floodmentioning

confidence: 99%

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Methodology for Simulation of IoT-Based Flood Data Collection Infrastructure

Ghapar¹,

Yussof²

2021

eJCSIT

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Internet of Things (IoT) is a potential technology to be used for data collection tasks in real-world environments. However, due to the difficulty of deploying and testing a real IoT implementation, many researchers end up having to use software simulation to evaluate their proposed techniques. This paper focuses on the use of IoT for collecting flood-related data, which would then use by flood-related applications such as flood prediction applications and flood early warning systems. This paper proposed a methodology for simulating the IoT system used for flood data collection. The proposed methodology consists of four main steps which are identifying the flood environment, defining the architecture for flood data collection, simulating the IoT-based flood data collection infrastructure and analyzing the results. The activities for each step are described in detail as to guide other researchers in the same area to adapt the methodology to their research work.

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Section: Flood Simulation Methodologiesmentioning

confidence: 99%

Section: Iot-based Wsn In Floodmentioning

confidence: 99%

Methodology for Simulation of IoT-Based Flood Data Collection Infrastructure

Ghapar¹,

Yussof²

2021

eJCSIT

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“…Figure 9 illustrates the EWS structure. The Mehran University of Engineering and Technology developed a flood/drought forecasting system (FDFS) using WSN to help the Pakistani government obtain early information about flooding and drought possibilities to take timely measures [23]. The system covers 19 barrages of 27 mainstream rivers in Pakistan and comprise a mechanical buoy equipped with water level sensors in the river and weather stations to monitor wind, pressure, humidity, and water pressure.…”

Section: Bangladeshmentioning

confidence: 99%

Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas

Acosta-Coll

Solano-Escorcia

Ortega-Gonzalez

et al. 2021

IJECE

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Fluvial flooding occurs when a river overspills its banks due to excessive rainfall, and it is the most common flood event. In urban areas, the increment of urbanization makes communities more susceptible to fluvial flooding since the excess of impervious surfaces reduced the natural permeable areas. As flood prevention strategies, early warning systems (EWS) are used to reduce damage and protect people, but key elements need to be selected. This manuscript proposes the monitoring instruments, communication protocols, and media to forecast and disseminate EWS alerts efficiently during fluvial floods in urban areas. First, we conducted a systematic review of different EWS architectures for fluvial floods in urban areas and identified that not all projects monitor the most important variables related to the formation of fluvial floods and most use communication protocols with high-energy consumption. ZigBee and LoRaWAN are the communication protocols with lower power consumption from the review, and to determine which technology has better performance in urban areas, two wireless sensor networks were deployed and simulated in two urban areas susceptible to fluvial floods using Radio Mobile software. The results showed that although Zigbee technology has better-received signal strength, the difference with LoRAWAN is lower than 2 dBm, but LoRaWAN has a better signal-to-noise ratio, power consumption, coverage, and deployment cost.

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“…The proposed models have been designed and implemented in various geographical locations in India. Moreover, in [6] the flood/drought monitoring and detection in Pakistan is proposed in an alarming situation. They proposed a low-cost and reliable flood/drought forecasting system that may help in extreme situations of natural disasters.…”

Section: Introductionmentioning

confidence: 99%

A Wireless Smart Sensor Network for Flood Management Optimization

Alfarra¹,

Alsibai²

2017

IJETS

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Recent development in the sensing technologies and wireless sensor networks has encouraged many innovative applications in disaster management and forecasting. Flood is one of the most dangerous natural disasters that occurs frequently in south Asia. Therefore, water level monitoring and flood early prediction, play an important role in lives and properties saving. In this paper, an optimized Flood Warning System (FWS) is presented. The system is based on multi parameters Wireless Smart Sensor Network (WSSN) for early flood warning. WSSN performs pre-processing procedures at sensor level before sending the data to a base data analyzing station. This pre-processing step is to improve the reliability, data quality and transmission quality. For the purpose of validation, the proposed method is applied using two parameters: The water level (L) and streamflow of water (R) in rivers. The proposed system provides early flood detection by continuously measuring R and L in real-time. The collected data is to be used to predict flood time and place. Data is exchanged among sensors in real-time. Pre-analyzing is performed and reports are sent to the base station only if the analysis gave a high risk level. The main purpose is to cut down the data size. Analysis and simulation showed that the data size is improved significantly using this method. Calculations considers real cases on a part of Pahang River (Sungai Pahang).

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Wireless sensor network based flood/drought forecasting system

Cited by 14 publications

References 7 publications

Methodology for Simulation of IoT-Based Flood Data Collection Infrastructure

Methodology for Simulation of IoT-Based Flood Data Collection Infrastructure

Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas

A Wireless Smart Sensor Network for Flood Management Optimization

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