Recommendation based rescue operation model for flood victim using smart IoT devices

Goyal, Himanshu Rai; Ghanshala, Kamal Kumar; Sharma, Sachin

doi:10.1016/j.matpr.2020.12.959

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…Detection and localization comprise the first in a series of steps [ 1 ], which also include the assessment of the victim’s status, communication, release and, transfer to a safe localization. The localization task is performed traditionally either with direct observation by the first responders (often with prior approximate information on where the victims might be located) [ 2 ] or with trained canine units [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Victim Detection and Localization in Emergencies

Álvarez‐Merino

Khatib

Luo-Chen

et al. 2022

Sensors

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Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victims in catastrophic scenarios. In this work, we present the benefits of using WiFi Fine Time Measurement (FTM), Ultra-Wide Band (UWB), and fusion technologies to locate victims under rubble. Integrating WiFi FTM and UWB in a drone may cover vast areas in a short time. Moreover, the detection capacity of WiFi and UWB for finding individuals is also compared. These findings are then used to propose a method for detecting and locating victims in disaster scenarios.

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Section: Introductionmentioning

confidence: 99%

Victim Detection and Localization in Emergencies

Álvarez‐Merino

Khatib

Luo-Chen

et al. 2022

Sensors

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“…The use of various types of monitoring technology has been updated by using Radar Doppler media [7], [8], ultrasonic sensors and SMS gateway instruments [9], pressure sensors used to obtain water level [2], a combination of ultrasonic sensors, flow sensors and wireless technology [10], using smart IoT devices [11] and so on. In this article, a water level monitoring system is described, equipped with the measurement of ripple waves and the area affected by water ripples.…”

Section: Introductionmentioning

confidence: 99%

Prototype of water level monitoring system using magnetic sensor and ultrasonic based on Arduino Mega 2560

Indrasari

Kadarwati

2022

J. Phys.: Conf. Ser.

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Water level monitoring is an activity to observe the water level by identifying and anticipating flood problems that will arise for action to be taken as early as possible. This system is connected by water level measurement. This prototype uses two types of sensors to measure the water level, the UGN3503 magnetic sensor will detect the water level horizontally, and ultrasonic sensors will detect vertically. Arduino Mega 2560, as a control system, regulates the work of the integrated sensors. The experiment using one UGN3503 sensor is obtained the maximum deviation on the addition or reduction of water by 3 mm. The overall system experiment shows that the measurement results of the UGN3503 sensor are closer to the actual height than ultrasonic. The data region affected by the water overflow is processed in ArcGIS software to predict that area. The relationship between height alterations to the overflow area is described in a linear equation.

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“…In this work, our area of study is Rajasthan which is the largest state of India and the 60% of its area falls under the arid category which makes it very environmentally sensitive [17]. Even after being an arid to semi-arid zone, Rajasthan has observed several floods in the past [24,77,57]and also observed several droughts [34,5,23,47,52]. An early indication of the amount of monsoon rainfall a particular region is going to receive, can be very handy in terms of managing the water resource for the entire year.…”

Section: Introductionmentioning

confidence: 99%

A Deep and Wide Neural Network-based Model for Rajasthan Summer Monsoon Rainfall (RSMR) Prediction

Bajpai¹,

Bansal²

2021

Preprint

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Importance of monsoon rainfall cannot be ignored as it affects round the year activities ranging from agriculture to industrial. Accurate rainfall estimation and prediction is very helpful in decision making in the sectors of water resource management and agriculture. Due to dynamic nature of monsoon rainfall, it's accurate prediction becomes very challenging task. In this paper, we analyze and evaluate various deep learning approaches such as one dimensional Convolutional Neutral Network, Multi-layer Perceptron and Wide Deep Neural Networks for the prediction of summer monsoon rainfall in Indian state of Rajasthan.For our analysis purpose we have used two different types of datasets for our experiments. From IMD grided dataset, rainfall data of 484 coordinates are selected which lies within the geographical boundaries of Rajasthan. We have also collected rainfall data of 158 rain gauge station from water resources department. The comparison of various algorithms on both these data sets is presented in this paper and it is found that Deep Wide Neural Network based model outperforms the other two approaches.

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Recommendation based rescue operation model for flood victim using smart IoT devices

Cited by 8 publications

References 14 publications

Victim Detection and Localization in Emergencies

Victim Detection and Localization in Emergencies

Prototype of water level monitoring system using magnetic sensor and ultrasonic based on Arduino Mega 2560

A Deep and Wide Neural Network-based Model for Rajasthan Summer Monsoon Rainfall (RSMR) Prediction

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