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 comprehensive review of deep learning applications in hydrology and water resources DOI Open Access
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang

и другие.

Water Science & Technology, Год журнала: 2020, Номер 82(12), С. 2635 - 2670

Опубликована: Авг. 5, 2020

Abstract 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 that 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

398

Towards a smart water city: A comprehensive review of applications, data requirements, and communication technologies for integrated management DOI Creative Commons
Martin Oberascher, Wolfgang Rauch, Robert Sitzenfrei

и другие.

Sustainable Cities and Society, Год журнала: 2021, Номер 76, С. 103442 - 103442

Опубликована: Окт. 19, 2021

Smart cities are an innovate concept for managing urban to enhance sustainability and increase quality of life citizens. Although water infrastructure (UWI) performs important functions in a city (e.g., supply drinking water), information communication technologies (ICT) system-wide management network-based UWI not yet widely deployed. Therefore, this review summarises first both existing potential applications related UWI, characterised by different spatial temporal resolution measurement control data. Second, comprehensive analysis ICT is provided, which extended with exemplary the field. The reveals that coordination between intended application usable technology required realise efficient monitoring network field networks. To overcome limitation, detailed framework developed, can be used researcher, operators, stakeholder identify suitable or determine possible system. Following, applicability demonstrated selected examples. As also indicates, integrated approach towards smart requires combination satisfy all specifications.

Язык: Английский

Процитировано

117

Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education DOI Creative Commons
Ramteja Sajja, Yusuf Sermet,

Muhammed Cikmaz

и другие.

Information, Год журнала: 2024, Номер 15(10), С. 596 - 596

Опубликована: Сен. 30, 2024

This paper presents a novel framework, artificial intelligence-enabled intelligent assistant (AIIA), for personalized and adaptive learning in higher education. The AIIA system leverages advanced AI natural language processing (NLP) techniques to create an interactive engaging platform. platform is engineered reduce cognitive load on learners by providing easy access information, facilitating knowledge assessment, delivering support tailored individual needs styles. AIIA’s capabilities include understanding responding student inquiries, generating quizzes flashcards, offering pathways. research findings have the potential significantly impact design, implementation, evaluation of AI-enabled virtual teaching assistants (VTAs) education, informing development innovative educational tools that can enhance outcomes, engagement, satisfaction. methodology, architecture, services, integration with management systems (LMSs) while discussing challenges, limitations, future directions

Язык: Английский

Процитировано

86

Agricultural flood vulnerability assessment and risk quantification in Iowa DOI
Enes Yıldırım, İbrahim Demir

The Science of The Total Environment, Год журнала: 2022, Номер 826, С. 154165 - 154165

Опубликована: Фев. 26, 2022

Язык: Английский

Процитировано

81

Flood mitigation data analytics and decision support framework: Iowa Middle Cedar Watershed case study DOI
Yazeed Alabbad, Enes Yıldırım, İbrahim Demir

и другие.

The Science of The Total Environment, Год журнала: 2022, Номер 814, С. 152768 - 152768

Опубликована: Янв. 3, 2022

Язык: Английский

Процитировано

78

What is Human-Centered about Human-Centered AI? A Map of the Research Landscape DOI Open Access
Tara Capel, Margot Brereton

Опубликована: Апрель 19, 2023

The application of Artificial Intelligence (AI) across a wide range domains comes with both high expectations its benefits and dire predictions misuse. While AI systems have largely been driven by technology-centered design approach, the potential societal consequences mobilized HCI researchers towards researching human-centered artificial intelligence (HCAI). However, there remains considerable ambiguity about what it means to frame, evaluate HCAI. This paper presents critical review large corpus peer-reviewed literature emerging on HCAI in order characterize community is defining as Our contributes an overview map research based work that explicitly mentions terms 'human-centered intelligence' or machine learning' their variations, suggests future challenges directions. reveals breadth happening HCAI, established clusters areas Interaction Ethical AI. new definition calls for greater collaboration between research, constructs.

Язык: Английский

Процитировано

75

U-net-based semantic classification for flood extent extraction using SAR imagery and GEE platform: A case study for 2019 central US flooding DOI Creative Commons
Zhouyayan Li, İbrahim Demir

The Science of The Total Environment, Год журнала: 2023, Номер 869, С. 161757 - 161757

Опубликована: Янв. 21, 2023

Язык: Английский

Процитировано

69

Platform-independent and curriculum-oriented intelligent assistant for higher education DOI Creative Commons
Ramteja Sajja, Yusuf Sermet, David M. Cwiertny

и другие.

International Journal of Educational Technology in Higher Education, Год журнала: 2023, Номер 20(1)

Опубликована: Июль 23, 2023

Abstract Miscommunication between instructors and students is a significant obstacle to post-secondary learning. Students may skip office hours due insecurities or scheduling conflicts, which can lead missed opportunities for questions. To support self-paced learning encourage creative thinking skills, academic institutions must redefine their approach education by offering flexible educational pathways that recognize continuous this end, we developed an AI-augmented intelligent assistance framework based on powerful language model (i.e., GPT-3) automatically generates course-specific assistants regardless of discipline level. The virtual teaching assistant (TA) system, at the core our framework, serves as voice-enabled helper capable answering wide range questions, from curriculum logistics course policies. By providing with easy access information, TA help improve engagement reduce barriers At same time, it also logistical workload TAs, freeing up time focus other aspects supporting students. Its GPT-3-based knowledge discovery component generalized system architecture are presented accompanied methodical evaluation system’s accuracy performance.

Язык: Английский

Процитировано

44

Comprehensive flood vulnerability analysis in urban communities: Iowa case study DOI
Yazeed Alabbad, İbrahim Demir

International Journal of Disaster Risk Reduction, Год журнала: 2022, Номер 74, С. 102955 - 102955

Опубликована: Апрель 8, 2022

Язык: Английский

Процитировано

63

Flood risk assessment and quantification at the community and property level in the State of Iowa DOI
Enes Yıldırım, Craig L. Just, İbrahim Demir

и другие.

International Journal of Disaster Risk Reduction, Год журнала: 2022, Номер 77, С. 103106 - 103106

Опубликована: Июнь 13, 2022

Язык: Английский

Процитировано

46