scholarly journals An internet of things system for urban flood monitoring and short-term flood forecasting in Colima, Mexico

2020 ◽  
Author(s):  
Abdou Khouakhi ◽  
Ian Pattison ◽  
Jesús López-de la Cruz ◽  
Oliver Mendoza-Cano ◽  
Robert Edwards ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Water Level ◽  
Machine Learning Algorithms ◽  
Urban Flooding ◽  
Time Data ◽  
Short Term ◽  
Urban Flood ◽  
Web Based ◽  
Data Platform ◽  
The City

<p>Urban flooding is one of the major issues in many parts of the world and its management often challenging. Here we present Internet of Things (IoT) approach for monitoring urban flooding in the City of Colima, Mexico. A network of water level and weather sensors have been developed along with a web-based data platform integrated with IoT techniques to retrieve data using 3G/4G and Wi-Fi networks. The developed architecture uses the Message Queuing Telemetry Transport protocol to send real-time data packages from fixed nodes to a server that stores retrieved data in a non-relational database. Data can be accessed and displayed through different queries and graphical representations, allowing future use in flood analysis and prediction. Additionally, machine learning algorithms are integrated into the system for short-range water level predictions at different nodes of the network.</p>

scholarly journals Urban flood modelling in Qiqihar city based on MIKE flood

2020 ◽  
Vol 383 ◽  
pp. 185-192
Author(s):  
Jiahong Liu ◽  
Zejin Li ◽  
Weiwei Shao ◽  
Dianyi Yan ◽  
Chao Mei
Keyword(s):  
Water Level ◽  
River Basin ◽  
Return Period ◽  
Flood Risk ◽  
Main Stream ◽  
Urban Flood ◽  
Songhua River ◽  
Mike Flood ◽  
The City ◽  
Flood Diversion

Abstract. Qiqihar is a significant city on the Nen River in China, which is the main stream of the Songhua River basin. The length of the return period of Qiqihar's flood control design standard is fifty years. If a 100-year flood event happened, Qiqihar would face the risk of a burst levee. To quantitatively evaluate flood risk to the city from a burst levee or proactive flood diversion, a model for analysing flood submergence from a burst levee in the City of Qiqihar is established based on MIKE Flood. The model integrates one- and two-dimensional hydrodynamic models to implement coupled simulation. The terrain data are from city elevation data on a scale of 1:10 000. Following local modifications made based on survey data, such as on levees, roads, and buildings, a 20 m × 20 m grid of terrain data was formed as the terrain input of the model. The model simulates the water level of Nen River and the flood path, submerged time/depth/area, and duration in floodplain under three scenarios: baseline, proactive downstream flood diversion, and an upstream levee burst under a flood with a one hundred-year return period. Proactive downstream flood diversion can reduce the maximum water level by 0.068 m and correspondingly decrease peak flood flow by 1120 m3 s−1. These results provide basic information to support urban flood risk analysis and flood dispatching and management across the whole river basin.

scholarly journals Adaptive photovoltaic solar module based on internet of things and web-based monitoring system

2022 ◽  
Vol 12 (1) ◽  
pp. 924
Author(s):  
Murizah Kassim ◽  
Fadila Lazim
Keyword(s):  
Internet Of Things ◽  
Solar Rotation ◽  
Tracking System ◽  
Solar Panel ◽  
Time Data ◽  
Solar Module ◽  
Web Based ◽  
Pv Module ◽  
Shading Effects ◽  
Power And Energy

<span>This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through </span><span>internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.</span>

Urban Flooding and Measures

2007 ◽  
Vol 2 (3) ◽  
pp. 143-152 ◽  
Author(s):  
Keiichi Toda ◽  
Keyword(s):  
Urban Environment ◽  
River Basins ◽  
Urban Flooding ◽  
Urban Floods ◽  
Urban Flood ◽  
Flood Model ◽  
Flood Disasters ◽  
Simulation Results ◽  
The City ◽  
Inundation Model

Urban flood disasters occur often worldwide, and Japan is no exception, as indicated by the 1999 Fukuoka flood. Urban floods result from changes in the urban environment influenced by the specific features of the city involved. We review recent urban floods, their causes and characteristics, together with the results of recent studies. Focusing on two mathematical models -- the integrated urban flood model of urban river basins and the underground inundation model -- we discuss their simulation results. To demonstrate the dangers of underground inundations, we introduce evacuation experiments conducted using full-scale staircase and door models. Based on these studies, we propose comprehensive measures against urban floods, including underground inundations.

Designing of Data Communication System for Night Bus Services Using Web-Based Barcodes and GPS Shields and Raspberry Pi

2017 ◽  
Vol 4 (1) ◽  
pp. 1-7
Author(s):  
Adi Putra Wijaya
Keyword(s):  
Rapid Development ◽  
Data Communication ◽  
Raspberry Pi ◽  
Mass Transportation ◽  
Test Results ◽  
Time Data ◽  
Web Based ◽  
The Status ◽  
Bus Services ◽  
The City

The bus is one of the mass transportation used by many people. With the rapid development of technology to find out the position of the bus, you can use a GPS tracker which has the ability to transmit real-time data. Use the barcode added to the bus ticket to find out the status of passengers getting on or off. Raspberry Pi functions to control Modem, Barcode Scanner, GPS Tracker. Raspberry Pi will process the GPS Tracker data on the bus to find out the coordinates of the bus. Barcode and GPS Tracker information will be retrieved from the webserver. Users will get bus information via a web smartphone by sending the bus police ID number. The application features contain agent information, bus destination code information, bus departure hours, bus tracking, and passenger status. Based on the test results, the tolerance value is 0.1" for latitude, the distance meter longitude value is 0.2". GPS Tracker will send more accurate data when in the city. In the Malang-Jakarta GPS Tracker test, there were not too many tree obstacles. Barcodes that have been scanned using a barcode reader will turn the seats on the display green.

scholarly journals Multivariate Analysis and Machine Learning Approach for Mapping the Variability and Vulnerability of Urban Flooding: The Case of Tangier City, Morocco

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 182
Author(s):  
Tarik Bouramtane ◽  
Ilias Kacimi ◽  
Khalil Bouramtane ◽  
Maryam Aziz ◽  
Shiny Abraham ◽  
...  
Keyword(s):  
Machine Learning ◽  
Multivariate Analysis ◽  
Population Density ◽  
Learning Algorithms ◽  
Drainage Density ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Urban Flooding ◽  
Flood Vulnerability ◽  
Urban Flood

Urban flooding is a complex natural hazard, driven by the interaction between several parameters related to urban development in a context of climate change, which makes it highly variable in space and time and challenging to predict. In this study, we apply a multivariate analysis method (PCA) and four machine learning algorithms to investigate and map the variability and vulnerability of urban floods in the city of Tangier, northern Morocco. Thirteen parameters that could potentially affect urban flooding were selected and divided into two categories: geo-environmental parameters and socio-economic parameters. PCA processing allowed identifying and classifying six principal components (PCs), totaling 73% of the initial information. The scores of the parameters on the PCs and the spatial distribution of the PCs allow to highlight the interconnection between the topographic properties and urban characteristics (population density and building density) as the main source of variability of flooding, followed by the relationship between the drainage (drainage density and distance to channels) and urban properties. All four machine learning algorithms show excellent performance in predicting urban flood vulnerability (ROC curve > 0.9). The Classifications and Regression Tree and Support Vector Machine models show the best prediction performance (ACC = 91.6%). Urban flood vulnerability maps highlight, on the one hand, low lands with a high drainage density and recent buildings, and on the other, higher, steep-sloping areas with old buildings and a high population density, as areas of high to very-high vulnerability.

scholarly journals IoT Based WSN Ground Water Monitoring System with Cloud-Based Monitoring as a Service (Maas) and Prediction using Machine Learning

2019 ◽  
Vol 9 (1) ◽  
pp. 816-821
Keyword(s):  
Machine Learning ◽  
Water Level ◽  
Monitoring System ◽  
Indian Subcontinent ◽  
Current System ◽  
Water Monitoring ◽  
Machine Learning Algorithms ◽  
Sensor Nodes ◽  
Raspberry Pi ◽  
Time Data

The main source of water in the Indian Subcontinent is Groundwater. It is also the most rapidly depleting resource due to various reasons such as rampant unchecked irrigation and exploitation of groundwater by industries and other organizations. The current system is limited by short communication range, high power consumption and the system monitors only the water level and the report is available only to the consumer i.e. it is a single-user system. Due to the unavailability of a centralized system to monitor and prevent overuse of water resources, sudden water crises have become a major issue in India. This project aims at implementing an IoT (Internet of things) based water monitoring system that monitors the water level and the quality of groundwater and updates real-time data to the database. This system is designed to monitor the groundwater level of an entire village or a town. It updates the people and the concerned government authorities in case of any decrease in water level and water quality below the threshold value, and also monitors the water consumption during a period and predicts exhaustion time. This system predicts the availability of water in the future based on current demand and usage and the recharge rate using machine learning algorithms. The data collected and the analysis of the data is made available in a Public Cloud. The modules are based on Raspberry Pi Zero, sensor nodes and LoRa (Long Range) Module or Wi-Fi module according to the network requirement for connectivity

Digitalization for Effective Performance Management Using Key Performance Indicators in Miscible Gas Injection Projects in South Oman

2021 ◽  
Author(s):  
Kamlesh Kumar ◽  
Tushar Narwal ◽  
Zaal Alias ◽  
Pankaj Agrawal ◽  
Ali Farsi ◽  
...  
Keyword(s):  
Performance Management ◽  
Real Time ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Production Optimization ◽  
Utilization Efficiency ◽  
Analysis Tool ◽  
Time Data ◽  
Short Term ◽  
Web Based

Abstract South Oman has several pre-Cambrian reservoirs that are highly pressured (400-1000 bar), deep (3-5 km) and critically sour (H2S up to 10%). The combined STOIIP of these reservoirs makes it one of the largest gas EOR projects in the world. The objective here is to highlight the key performance indicators and digitalization techniques used for continuous and effective well, reservoir and facility management (WRFM) and production optimization, while honoring the facility constraints and gas export requirements. Real time pressure data such as tubing head pressures, injection/production rates along with other data including maps, static pressures and production logs are used to define an appropriate set of performance metric at various levels, e.g. reservoir, sector or well. Digitalization of surveillance data helps in real time production optimization such as offtake management based on creaming curves according to gas sink availability and facility constraints. Key business performance indicators include gas utilization efficiency; MGI performance indicators include incremental oil, throughput, instantaneous and cumulative voidage replacement ratios, gas breakthrough level and time, ratio of reservoir pressure to the target minimum miscibility pressure; and facility constraints are optimized through gas balance, along with tracking field performance against the initial FDP forecasts. Real time performance data is tracked using a commercial Real-Time Data Analysis tool (RTDA) and Database Analytics Visualization Tool (DAVT), with surveillance indicators targeted at well, reservoir and facility level. The above-defined Key Performance Indicators (KPI) are tracked against predictions from the field development plan in web-based portal developed at PDO (Nibras). Digitalization has enabled quick and effective monitoring of these KPI, short-term optimization of injection distribution and offtake rates to maximize oil production and overall value within facilities constraints and varying export gas commitments based on South Oman Gas Line (SOGL) network optimization. Using dimensionless plots and a standardized set of parameters help in developing a common understanding and benchmarking the MGI reservoir response with analogs and amongst different reservoirs. This work presents a set of performance KPIs and short-term optimization methodology using digitalization and LEAN framework that are tracked in a web-based portal, RTDA and DAVT. It provides means to facilitate offtake decisions to meet variable export requirements while honoring facilities constraints, assess reservoir performance, providing valuable insights that helps in speedy reservoir management decisions. This process has been replicated across PDO for all related MGI projects and can benefit other development types, e.g. chemical/steam injection.

scholarly journals Inundated Areas Extraction Based on Raindrop Photometric Model (RPM) in Surveillance Video

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1332 ◽  
Author(s):  
Yunzhe Lv ◽  
Wei Gao ◽  
Chen Yang ◽  
Ning Wang
Keyword(s):  
Traditional Method ◽  
Extraction Method ◽  
Low Cost ◽  
Urban Flooding ◽  
Surveillance Video ◽  
Time Data ◽  
Urban Flood ◽  
Data Source ◽  
Constraint Information ◽  
Background Image

Monitoring and assessing urban flood disasters is the key to reducing the damage of this hazard. The urban surveillance video, with the advantages of flexibility and low cost, has been used as an effective real-time data source to monitor urban flooding. The paper presents an inundated area extraction method based on raindrop photometric model. The proposed method operates on the video and divides the task into two steps: (1) extracting water surface, followed by (2) refining inundated areas. At the first step in the process, the water covered areas are extracted from the variation of video in time series. This procedure was an improved version of the raindrop photometric model. Constrained information, especially road ranges, was obtained from video background image which has eliminated interference factors. Then inundated areas can be refined with the constraint information. Experiments performed on different locations show that the proposed method can provide more reliable results than the traditional method based on spectral features.

scholarly journals Technical challenges and perspectives in batch and stream big data machine learning

2017 ◽  
Vol 7 (1.3) ◽  
pp. 48 ◽  
Author(s):  
KVSN Rama Rao ◽  
Sivakannan S ◽  
M.A. Prasad ◽  
R. Agilesh Saravanan
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Internet Of Things ◽  
Social Networking ◽  
Paradigm Shift ◽  
Machine Learning Algorithms ◽  
Smart Phones ◽  
Time Data ◽  
Predominant Role ◽  
Real Time Data

Machine Learning is playing a predominant role across various domains. However traditional Machine Learning algorithms are becoming unsuitable for majority of applications as the data is acquiring new characteristics. Sensors, devices, servers, Internet, Social Networking, Smart phones and Internet of Things are contributing the major sources of data. Hence there is a paradigm shift in the Machine learning with the advent of Big Data. Research works are in evolution to deal with Big Data Batch and stream real time data. In this paper, we highlighted several research works that contributed towards Big Data Machine Learning.

PENGELOLAAN DATA ANGGOTA BERBASIS WEBSITE DI YAMAHA VIXION CLUB CABANG BANDUNG

2020 ◽  
Vol 2 (2) ◽  
pp. 113-127
Author(s):  
Nova Indrayana Yusman
Keyword(s):  
Data Management ◽  
Organizational Structure ◽  
Human Resource Development ◽  
Human Resource ◽  
Programming Language ◽  
The Internet ◽  
Web Based ◽  
Management Software ◽  
The City ◽  
Data Management Software

Yamaha Vixion Club Bandung (YVCB) was formed on July 7, 2007 in the city of Bandung, as a place of friendship between Yamaha Vixion motorcyclists. In its organizational structure, YVCB has a Human Resource Development (HRD) division. Until now, there are more than 800 Yamaha Vixion Club Bandung members. This software is made to facilitate the work of the Yamaha Vixion Club Bandung HRD Division in processing member data. Created using Microsoft Webmatrix as an editor with the PHP programming language. The database uses MySQL with PHPMyAdmin as the software. The method used in making this software is prototyping so that between developers and customers can understand each other what the customer wants. The purpose of making web-based member data management software is that in terms of managing member data it can be done anytime and anywhere by just accessing the internet. In the use of the program, the author chose to use PHP, because PHP is the best and easiest to use in website programming language. Based on the last paragraph, the author intends to make aplication based computerized attendance so that become effective and efficient in terms of time.

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