Flood Monitoring and Alerting System for Low Lying Urban Areas

2021 ◽  
pp. 273-282
Author(s):  
S. Pradeep Reddy ◽  
T. R. Vinay ◽  
K. Manasa ◽  
D. V. Mahalakshmi ◽  
S. Sandeep ◽  
...  
Keyword(s):  
Urban Areas ◽  
Flood Monitoring ◽  
Alerting System

scholarly journals IoT-based Flood Monitoring and Alerting System using Raspberry Pi

2020 ◽  
Vol 981 ◽  
pp. 042078
Author(s):  
K Subramanya Chari ◽  
Maturi Thirupathi ◽  
. Ch Hariveena
Keyword(s):  
Raspberry Pi ◽  
Flood Monitoring ◽  
Alerting System

scholarly journals Integrate Weather Radar and Monitoring Devices for Urban Flooding Surveillance

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 825 ◽  
Author(s):  
Shih-Yen Hsu ◽  
Tai-Been Chen ◽  
Wei-Chang Du ◽  
Jyh-Horng Wu ◽  
Shih-Chieh Chen
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Weather Radar ◽  
Water Levels ◽  
Mitigation Measures ◽  
Extreme Weather Events ◽  
Television System ◽  
Urban Flood ◽  
Flood Monitoring ◽  
Image Capturing

With the increase of extreme weather events, the frequency and severity of urban flood events in the world are increasing drastically. Therefore, this study develops ARMT (automatic combined ground weather radar and CCTV (Closed Circuit Television System) images for real-time flood monitoring), which integrates real-time ground radar echo images and automatically estimates a rainfall hotspot according to the cloud intensity. Furthermore, ARMT combines CCTV image capturing, analysis, and Fourier processing, identification, water level estimation, and data transmission to provide real-time warning information. Furthermore, the hydrograph data can serve as references for relevant disaster prevention, and response personnel may take advantage of them and make judgements based on them. The ARMT was tested through historical data input, which showed its reliability to be between 83% to 92%. In addition, when applied to real-time monitoring and analysis (e.g., typhoon), it had a reliability of 79% to 93%. With the technology providing information about both images and quantified water levels in flood monitoring, decision makers can quickly better understand the on-site situation so as to make an evacuation decision before the flood disaster occurs as well as discuss appropriate mitigation measures after the disaster to reduce the adverse effects that flooding poses on urban areas.

scholarly journals Iot Based Flood Monitoring and Alerting System with Weather Forecasting

2020 ◽  
Vol 9 (6) ◽  
pp. 559-563 ◽  
Keyword(s):  
Water Flow ◽  
Humidity Sensor ◽  
Weather Forecasting ◽  
Android Application ◽  
Sound Waves ◽  
Flood Monitoring ◽  
Alerting System ◽  
Set Up ◽  
Final System ◽  
Early Detection And Prevention

This paper represents the development strategies of Internet of Things based flood monitoring and alerting system with weather forecasting through open weather API. This project is based on the open source electronic platform i.e. Arduino. The Arduino Uno R3 is to be set up multiple different devices such as ultrasonic sensor for the water level detection by capturing the time between transmitting and receiving sound waves, temperature and humidity sensor DHT11/AM2302 for analyzing the moisture content and water flow sensor for evaluating the speed of water flow. Further, these values received by different sensors are to be transferred to the Android Application which is developed with the technologies such as Java, XML, Android studio. The final system will be deployed in the flood prone areas for early detection and prevention of flood.

scholarly journals A cloud-based cognitive computing solution with interoperable applications to counteract illegal dumping in smart cities

2021 ◽  
Author(s):  
Mauro Coccoli ◽  
Vincenzo De Francesco ◽  
Antonio Fusco ◽  
Paolo Maresca
Keyword(s):  
Urban Areas ◽  
Visual Recognition ◽  
Smart Cities ◽  
Traffic Monitoring ◽  
Cognitive Computing ◽  
Development Environment ◽  
Illegal Dumping ◽  
Alerting System ◽  
Environment Control ◽  
Control And Management

AbstractThe study presented in this paper is the outcome of the activity carried on within the program “Party Cloud Challenge per Genova”, promoted by IBM in collaboration with the city municipality of Genoa, Italy. This challenge aimed to show how using cognitive computing solutions in an integrated cloud-based development environment enables the rapid deployment of advanced services with interoperable applications. Specifically, we investigated a solution to cope with the problem of illegal dumping prevention in a smart city. In this respect, we will describe the study of the prototype of an automated visual recognition and alerting system. The presented solution relies on the use of cognitive computing technologies to analyze videos provided by cameras installed in urban areas, to identify trash, especially bulky waste, where it should not be, and trigger an alarm to the municipality. In particular, we want to take advantage of the pictures, frames and videos continuously recorded by cameras installed for traffic monitoring, for surveillance, etc. in smart cities where the waste management system is supposed to be integrated with other municipality services for environment control and management. Besides, an organization plan is also proposed for intelligent waste collection as well as some organizational ideas for scalability.

Flood Monitoring and Mitigation Strategies for Flood-Prone Urban Areas

2020 ◽  
Author(s):  
Pat Finley ◽  
Grayson Gatti ◽  
Jonathan Goodall ◽  
Mac Nelson ◽  
Kiri Nicholson ◽  
...  
Keyword(s):  
Urban Areas ◽  
Mitigation Strategies ◽  
Flood Monitoring

scholarly journals Rainfall Monitoring Based on Next-Generation Millimeter-Wave Backhaul Technologies in a Dense Urban Environment

2020 ◽  
Vol 12 (6) ◽  
pp. 1045 ◽  
Author(s):  
Congzheng Han ◽  
Juan Huo ◽  
Qingquan Gao ◽  
Guiyang Su ◽  
Hao Wang
Keyword(s):  
Communication Networks ◽  
Millimeter Wave ◽  
Urban Areas ◽  
Multiple Input Multiple Output ◽  
Rain Attenuation ◽  
Rain Gauge ◽  
Microwave Technology ◽  
Flood Monitoring ◽  
Input Multiple Output ◽  
Backhaul Links

High-resolution and accurate rainfall monitoring is of great importance to many applications, including meteorology, hydrology, and flood monitoring. In recent years, microwave backhaul links from wireless communication networks have been suggested for rainfall monitoring purposes, complementing the existing monitoring systems. With the advances in microwave technology, new microwave backhaul solutions have been proposed and applied for 5G networks. Examples of the latest microwave technology include E-band (71–76 and 81–86 GHz) links, multi-band boosters, and line-of-sight multiple-input multiple-output (LOS-MIMO) backhaul links. They all rely on millimeter-wave (mmWave) technology, which is the fastest small-cell backhaul solution. In this paper, we will study the rain attenuation characteristics of these new microwave backhaul techniques at different mmWave frequencies and link lengths. We will also study the potential of using these new microwave solutions for rainfall monitoring. Preliminary results indicate that all the test mmWave links can be very effective for estimating the path-averaged rain rates. The correlation between the mmWave link measurement-derived rain rate and the local rain gauge is in the range of 0.8 to 0.9, showing a great potential to use these links for precipitation and flood monitoring in urban areas.

Flood monitoring in remote areas: integration of multi-frequency SAR data

2021 ◽  
Author(s):  
Alberto Refice ◽  
Annarita D'Addabbo ◽  
Marco Chini ◽  
Marina Zingaro
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Microwave Remote Sensing ◽  
Integrated Analysis ◽  
Satellite Mission ◽  
Flood Monitoring ◽  
L Band ◽  
Sar Data ◽  
Sar Imagery ◽  
Flooded Areas

<p>The monitoring of inundation phenomena through synthetic aperture radar (SAR) data on vegetated areas can be improved through an integrated analysis of different spectral bands. The combination of data with different penetration depths beneath the vegetated canopy can help determine the response of flooded areas with distinct types of vegetation cover to the microwave signal. This is useful especially in cases, which actually constitute the majority, where ground data are scarce or not available.</p><p>The present study concerns the application of multi-temporal, multi-frequency, and multi-polarization SAR images, specifically data from the Sentinel-1 and PALSAR 2 SAR sensors, operating in C band, VV polarization, and L band, HH and HV polarizations, respectively, in synergy with globally-available land cover data, for improving flood mapping in densely vegetated areas, such as the Zambezi-Shire basin, Mozambique [1], characterized by wetlands, open and closed forest, cropland, grassland (herbaceous and shrubs), and a few urban areas.</p><p>We show how the combination of various data processing techniques and the simultaneous availability of data with different frequencies and polarizations can help to monitor floodwater evolution over various land cover classes. They also enable detection of different scattering mechanisms, such as double bounce interaction of vegetation stems and trunks with underlying floodwater, giving precious information about the distribution of flooded areas among the different ground cover types present on the site.</p><p>This kind of studies are expected to assume increasing importance as the availability of multi-frequency data from SAR satellite constellations will increase in the future, thanks to initiatives such as the EU Copernicus program L-band satellite mission ROSE-L [2], and their tight integration with Sentinel-1 as well as with other national constellations such as ALOS 2, or SAOCOM.</p><p><strong>References</strong></p><p>[1] Refice, A.; Zingaro, M.; D’Addabbo, A.; Chini, M. Integrating C- and L-Band SAR Imagery for Detailed Flood Monitoring of Remote Vegetated Areas. Water <strong>2020</strong>, 12, 2745, doi:10.3390/w12102745.</p><p>[2] Pierdicca, N.; Davidson, M.; Chini, M.; Dierking, W.; Djavidnia, S.; Haarpaintner, J.; Hajduch, G.; Laurin, G.V.; Lavalle, M.; López-Martínez, C.; et al. The Copernicus L-band SAR mission ROSE-L (Radar Observing System for Europe). In Active and Passive Microwave Remote Sensing for Environmental Monitoring III; SPIE: Washington, DC, USA, 2019; Volume 11154, p. 13.</p>

scholarly journals Sensor-Based Gas Leakage Detector System

2020 ◽  
Vol 2 (1) ◽  
pp. 28
Author(s):  
Mohammad Monirujjaman Khan
Keyword(s):  
Urban Areas ◽  
Detection System ◽  
Industrial Sector ◽  
Leakage Detection ◽  
Liquefied Petroleum Gas ◽  
Residential Areas ◽  
Compressed Natural Gas ◽  
Gas Leakage ◽  
Alerting System ◽  
And Control

Liquefied Petroleum Gas (LPG) is a main source of fuel, especially in urban areas because it is clean compared to firewood and charcoal. Gas leakage is a major problem in the industrial sector, residential premises, etc. Nowadays, home security has become a major issue because of increasing gas leakage. Gas leakage is a source of great anxiety with ateliers, residential areas and vehicles like Compressed Natural Gas (CNG), buses, and cars which are run on gaspower. One of the preventive methods to stop accidents associated with the gas leakage is to install a gas leakage detection kit at vulnerable places. The aim of this paper is to propose and discuss a design of a gas leakage detection system that can automatically detect, alert and control gas leakage. This proposed system also includes an alerting system for the users. The system is based on a sensor that easily detects a gas leakage.

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