IoT-Based Smart Water Management Systems for Residential Buildings in Saudi Arabia DOI Open Access
Rayed AlGhamdi, Sunil Kumar Sharma

Processes, Год журнала: 2022, Номер 10(11), С. 2462 - 2462

Опубликована: Ноя. 21, 2022

Water is a precious resource that can be intelligently managed. Effective water usage demands computerized home supply management in culture where tanks, motors, and pumps are ubiquitous. crucial for the government citizens countries like Saudi Arabia. The issue providing constant, high-quality, low-cost supply. This study introduces smart (IoT-SWM) system may used structures do not have access to constant but instead stored enormous tanks underneath. GSM module collects use data from each community transmits it cloud, analyzed. A grid hybrid application uses an inspection mode identify leaks measure resulting height differences keep track of tank’s level. automatically deactivates affected section after detecting any shortage or malfunction mechanism, such as broken valves, pumps, pipes. It sends emergency signal building managers. monitors essential quality elements regularly, if they fall below acceptable levels, warning signals management, who take action. Over extended period, monitored recorded all metrics. restarts when pump has been reconnected alert. As result, suggested excellent replacement Arabia’s mechanically operated system.

Язык: Английский

A web-based analytical urban flood damage and loss estimation framework DOI
Yazeed Alabbad, Enes Yıldırım, İbrahim Demir

и другие.

Environmental Modelling & Software, Год журнала: 2023, Номер 163, С. 105670 - 105670

Опубликована: Март 7, 2023

Язык: Английский

Процитировано

33
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources DOI Open Access
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang

и другие.

EarthArXiv (California Digital Library), Год журнала: 2020, Номер unknown

Опубликована: Июнь 17, 2020

The global volume of digital data is expected to reach 175 zettabytes by 2025. volume, variety, and velocity water-related are increasing due large-scale sensor networks increased attention topics such as disaster response, water resources management, climate change. Combined with the growing availability computational popularity deep learning, these transformed into actionable practical knowledge, revolutionizing industry. In this article, a systematic review literature conducted identify existing research which incorporates learning methods in sector, regard monitoring, governance communication resources. study provides comprehensive state-of-the-art approaches used industry for generation, prediction, enhancement, classification tasks, serves guide how utilize available future challenges. Key issues challenges application techniques domain discussed, including ethics technologies decision-making management governance. Finally, we provide recommendations directions models hydrology

Язык: Английский

Процитировано

55
HydroLang: An open-source web-based programming framework for hydrological sciences DOI
Carlos Erazo Ramirez, Yusuf Sermet,

Frank Molkenthin

и другие.

Environmental Modelling & Software, Год журнала: 2022, Номер 157, С. 105525 - 105525

Опубликована: Сен. 14, 2022

Язык: Английский

Процитировано

33
Flood susceptibility mapping using fuzzy analytical hierarchy process for Cedar Rapids, Iowa DOI

Beyza Atiye Cikmaz,

Enes Yıldırım, İbrahim Demir

и другие.

International Journal of River Basin Management, Год журнала: 2023, Номер 23(1), С. 1 - 13

Опубликована: Май 24, 2023

Floods affect over 2.2 billion people worldwide, and their frequency is increasing at an alarming rate compared to other disasters. Presidential disaster declarations have issued increasingly almost every year in Iowa for the past 30 years, indicating that state on rise of flood risk. A multi-disciplinary approach required, which underlying hydrologic processes cause floods are closely linked with watershed-level socio-economic functions using effective collaboration tools ensure community participation co-production mitigation plans while paying attention socio-environmental justice principles. Considering existing limitations needs, we conducted a risk assessment by utilizing geophysical datasets case study Cedar Rapids, Iowa. Flood outputs generated based three main groups: geophysical-based risk, socioeconomic combined An extensive literature review determine pairwise comparison matrices parameters used analytical hierarchy process (AHP) fuzzy AHP methods. Our results indicate high- very-high-risk susceptibility zones primarily located central urban areas lower elevations, regardless method type (AHP or FAHP). According overall results, large area Rapids consists medium level according map method. The show high very high-risk 16% studied region, medium, low low-risk correspond 84%. Besides, nearly 40% population lives zones.

Язык: Английский

Процитировано

18
MA-SARNet: A one-shot nowcasting framework for SAR image prediction with physical driving forces DOI
Zhouyayan Li, Zhongrun Xiang, Bekir Zahit Demiray

и другие.

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2023, Номер 205, С. 176 - 190

Опубликована: Окт. 12, 2023

Язык: Английский

Процитировано

14
Comparative analysis of performance and mechanisms of flood inundation map generation using Height Above Nearest Drainage DOI Creative Commons
Zhouyayan Li,

Felipe Quintero Duque,

Trevor Grout

и другие.

Environmental Modelling & Software, Год журнала: 2022, Номер 159, С. 105565 - 105565

Опубликована: Ноя. 4, 2022

Язык: Английский

Процитировано

20
TempNet – temporal super-resolution of radar rainfall products with residual CNNs DOI Creative Commons
Muhammed Sit, Bong‐Chul Seo, İbrahim Demir

и другие.

Journal of Hydroinformatics, Год журнала: 2023, Номер 25(2), С. 552 - 566

Опубликована: Март 1, 2023

Abstract The temporal and spatial resolution of rainfall data is crucial for environmental modeling studies in which its variability space time considered as a primary factor. Rainfall products from different remote sensing instruments (e.g., radar, satellite) have space-time resolutions because the differences their capabilities post-processing methods. In this study, we developed deep-learning approach that augments with increased to complement relatively lower-resolution products. We propose neural network architecture based on Convolutional Neural Networks (CNNs), namely TempNet, improve radar-based compare proposed model an optical flow-based interpolation method CNN-baseline model. While TempNet achieves mean absolute error 0.332 mm/h, comparison methods achieve 0.35 0.341, respectively. methodology presented study could be used enhancing maps better imputation missing frames sequences 2D support hydrological flood forecasting studies.

Язык: Английский

Процитировано

12
HydroLang Markup Language: Community-driven web components for hydrological analyses DOI Creative Commons
Carlos Erazo Ramirez, Yusuf Sermet, İbrahim Demir

и другие.

Journal of Hydroinformatics, Год журнала: 2023, Номер 25(4), С. 1171 - 1187

Опубликована: Июль 1, 2023

Abstract We introduce HydroLang Markup Language (HL-ML), a programming interface that uses markup language to perform environmental analyses using the hydrological and framework HydroLang. The software acts as self-contained HTML tags powered by web component specification generate simple computations enable data analysis, visualization, manipulation via semantically driven instructions. It enables researchers professionals use retrieve, analyze, visualize, map with basic skills. components' adaptability users run analytical routines complex on client side. present implementation details of approach, custom elements in technologies academia, share sample usages demonstrate simplicity human-readable computer-executable framework.

Язык: Английский

Процитировано

12
Realising smarter stormwater management: A review of the barriers and a roadmap for real world application DOI Creative Commons
Chris Sweetapple, James L. Webber,

Anna Hastings

и другие.

Water Research, Год журнала: 2023, Номер 244, С. 120505 - 120505

Опубликована: Авг. 19, 2023

Effective management of stormwater systems is necessary for protection both the built and natural environments. However, facing multiple, growing challenges, including climate change, ageing infrastructure, population growth, urbanisation, environmental concerns, regulatory institutional changes public awareness. While potential 'smart', internet-of-things enabled to address these challenges increasingly being recognised, with considerable evidence in literature benefits more data-driven approaches, implementation date remains low. This paper, therefore, provides a comprehensive review barriers adoption smarter practices that require addressing, roadmap real world application. Barriers related all elements management, from asset sensing data analytics online optimisation, are identified. Technical discussed include availability reliability technologies, technological physical limitations, decision making, uncertainty security. rapidly reducing there increasing academic efficacy smart technologies. socio-economic remain significant challenge, issues such as trust lack confidence, resistance expense, knowledge guidance reviewed. A 'smart wheel' flexible iterative approach implementing functionality also presented. Whilst acting roadmap, this aims facilitate structured methodology overcoming benchmarking progress, may be used explore trade-offs relationships between differing levels each constituent technologies system.

Язык: Английский

Процитировано

12
Camera-based intelligent stream stage sensing for decentralized environmental monitoring DOI Creative Commons
Yusuf Sermet, İbrahim Demir

Journal of Hydroinformatics, Год журнала: 2023, Номер 25(2), С. 163 - 173

Опубликована: Фев. 15, 2023

Abstract Accurate, vast, and real-time coverage of water level monitoring is crucial for the advancement environmental research, specifically in areas climate change, distribution, natural disaster preparedness management. The current state network requires an immediate solution to produce low-cost accurate measurement sensors. This research presents a novel methodology intelligent stream stage measurement, creating distinct opportunity low-cost, camera-based embedded system that will measure levels share surveys support decision-making. It implemented as stand-alone device utilizes registry structures points interest (POI) along with core modules application logic: (1) deep-learning powered segmentation; (2) visual servoing; (3) POI geolocation computation. implementation relies on Raspberry-Pi motorized camera automated measurements supported by Proportional–Integral–Derivative controller multiprocessing. For future work, involvement supports further use cases such recognizing objects (e.g., debris, trees, humans, boats) surface. Additionally, method shown can be made into Progressive Web Application (PWA) used smartphones allow crowdsourced citizen science applications monitoring.

Язык: Английский

Процитировано

11