IoT-driven smart agricultural technology for real-time soil and crop optimization by Hammad Shahab, Muhammad Naeem, Muhammad Iqbal, Muhammad Aqeel, Syed Sajid Ullah

“…By integrating advanced IoT technologies, cloud computing, predictive algorithms, and a smart soil sensor, this system revolutionizes agriculture by enabling real-time monitoring of critical factors influencing rice crops metabolism. …”
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Communications Security in Industry X: A Survey by Ijaz Ahmad, Felipe Rodriguez, Tanesh Kumar, Jani Suomalainen, Senthil Kumar Jagatheesaperumal, Stefan Walter, Muhammad Zeeshan Asghar, Gaolei Li, Nikolaos Papakonstantinou, Mika Ylianttila, Jyrki Huusko, Thilo Sauter, Erkki Harjula

“…Most of the novel technologies, such as cyber-physical systems, industrial Internet of things, machine learning, advances in cloud computing, such as edge and fog computing, and blockchain, to name a few, are converged through advanced communication networks. …”
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Industry 4.0 and circular economy for bolstering healthcare sector: A comprehensive view on challenges, implementation, and futuristic aspects by Mohd Javaid, Abid Haleem, Ibrahim Haleem Khan, Ravi Pratap Singh, Abid Ali Khan

“…Industry 4.0 uses advanced technologies like the Internet of Things (IoT), Cloud computing, Big Data, and Artificial Intelligence (AI) to enhance productivity, satisfy customers, and generate new business opportunities. …”
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Modular architecture of the intellectual system for solving the problems of the internet of things by Vasiliy M. Trembach

“…For the development of the Internet of things, fog computing is used that extends and complements cloud computing. One of the central places on the Internet of things is machine learning. …”
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Digital-based emergency prevention and control system: enhancing infection control in psychiatric hospitals by Mi Yang, Xiaojun Zhu, Fei Yan, Xincheng Huang, Zhixue Wu, Xin Jiang, Yan Huang, Zezhi Li

“…Methods The system incorporates modern technologies such as cloud computing, big data, streaming media, and knowledge graphs. …”
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Photonics Breakthroughs 2024: Multidimensional Integrated (de)Multiplexers for Optical Fiber Communications by Xianyi Feng, Wu Zhou, Hao Chen, Yuzhe Ma, Yeyu Tong

“…The growing demand for higher data transmission capacity, particularly driven by advancements in artificial intelligence and cloud computing, has spurred the exploration of various degrees of freedom (DoF) of light in optical communication systems, including wavelength, polarization, and spatial modes. …”
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AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…In addition, it examines the role of cloud computing, edge AI, and distributed systems in enabling real-time transaction monitoring and fraud detection. …”
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Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi, Alina Blume, Isabel Caballero, Gabriel Navarro, Dimosthenis Traganos

“…Our synoptic tool uses Sentinel-2 A/B satellite imagery at 10 m spatial resolution to generate a multi-temporal composite (2016–2022) of the Balearic Islands’ coastal waters within the Google Earth Engine cloud computing platform, optimizing image processing and highlighting the importance of a high-resolution bathymetric dataset to increase seagrass mapping accuracies. …”
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Glacier, Wetland, and Lagoon Dynamics in the Barroso Mountain Range, Atacama Desert: Past Trends and Future Projections Using CA-Markov by German Huayna, Edwin Pino-Vargas, Jorge Espinoza-Molina, Carolina Cruz-Rodríguez, Fredy Cabrera-Olivera, Lía Ramos-Fernández, Bertha Vera-Barrios, Karina Acosta-Caipa, Eusebio Ingol-Blanco

“…Employing advanced remote sensing techniques through the Google Earth Engine (GEE) cloud computing platform, we analyzed historical trends (1985–2022) using Landsat satellite imagery. …”
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Evaluation of classification algorithms in the Google Earth Engine platform for the identification and change detection of rural and periurban buildings from very high-resolution i... by Alejandro Coca-Castro, Maycol A. Zaraza-Aguilera, Yilsey T. Benavides-Miranda, Yeimy M. Montilla-Montilla, Heidy B. Posada-Fandiño, Angie L. Avendaño-Gomez, Hernando A. Hernández-Hamon, Sonia C. Garzón-Martinez, Carlos A. Franco-Prieto

“…The results are relevant for institutions tracking the dynamics of building areas from cloud computing platfo future assessments of classifiers in likewise platforms in other contexts.…”
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From Technical Prerequisites to Improved Care: Distributed Edge AI for Tomographic Imaging by Bilgehan Akdemir, Hafiz Faheem Shahid, Mikael A. K. Brix, Juho Laakkola, Johirul Islam, Tanesh Kumar, Jarmo Reponen, Miika T. Nieminen, Erkki Harjula

“…Consequently, despite the undisputed benefits of cloud computing, dedicated standalone local computers are still used for image reconstruction in today’s systems. …”
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Evaluation of the digital medicine perception by the youth consumer segment by Anna B. Tsvetkova, Anatoliy V. Shishkin

“…New technologies are being introduced, the key areas of development of which are focused on the Internet of things for medicine (IoT), artificial intelligence, mobile apps, genome editing, telemedicine, blockchain projects and cloud computing. The Russian market is slowly developing. …”
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A digital twin-enabled fog-edge-assisted IoAT framework for Oryza Sativa disease identification and classification by Goluguri N.V. Rajareddy, Kaushik Mishra, Satish Kumar Satti, Gurpreet Singh Chhabra, Kshira Sagar Sahoo, Amir H. Gandomi

“…In response to this critical need, the research introduces a timely detection system that leverages the power of Digital Twin (DT)-enabled Fog computing, integrated with Edge and Cloud Computing (CC), and supported by sensors and advanced technologies. …”
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Value Chain Modeling in Digital Strategic Management by I. M. Stepnov, Yu. A. Kovalchuk

“…The analysis of existing approaches reveals the following unsolved problems: frst, the absence of direct interconnection between the expenses on digitalization and the results received with the use of digital platforms, and second, information is not singled out as a separate expense category in cost accounting, management and control regardless of the considerable percentage increase of an enterprise expenses on cloud computing service and technology. The authors model the newly created value in digital environment by a) defning a service (not fnished goods) as an integrating element which is typical of digital economy; b) singling out the variants of market cooperation with the use of platforms on the basis of traditional contracts, agreements “by default”, registered users of the platforms, smart contracts; c) choosing basic parameters — investments in the capital which is aggregated by the process and the costs of operating activity participants (by technological limits) supplemented by semi fixed costs; d) using the concept of limits to represent operating activity which is sensitive to special features and proportions among separate stages of a technological process and introducing two information limits (“Data collection, storage and processing” and “Digital representation and market design”) which resulted in creation of the information and communication costs accounting object. …”
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Recursive feature elimination for summer wheat leaf area index using ensemble algorithm-based modeling: The case of central Highland of Ethiopia by Dereje Biru, Berhan Gessesse, Gebeyehu Abebe

“…This study explored the use of ensemble algorithm-based recursive feature elimination (RFE) for summer wheat LAI estimation using the Google Earth Engine (GEE) cloud computing platform. Remote sensing datasets, including Sentinel-1/2 and digital elevation models, encompassing spectral bands, vegetation indices, texture metrics, and topographic variables, were used. …”
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Assessment of war-induced agricultural land use changes in Ukraine using machine learning applied to Sentinel satellite data by Nataliia Kussul, Andrii Shelestov, Bohdan Yailymov, Hanna Yailymova, Guido Lemoine, Klaus Deininger

“…This study presents a multi-year assessment of war-induced agricultural land use changes in Ukraine using machine learning-based classification applied to Sentinel-1 and Sentinel-2 satellite imagery. By leveraging cloud computing platforms, including Google Earth Engine (GEE) and the Copernicus Data Space Ecosystem (CDSE), we develop high-resolution KPI-Ukraine (Igor Sikorsky Kyiv Polytechnic Institute (KPI) in Ukraine) land use maps spanning from 2016 to 2024. …”
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Estimating Chlorophyll-<i>a</i> and Phycocyanin Concentrations in Inland Temperate Lakes across New York State Using Sentinel-2 Images: Application of Google Earth Engine for Effic... by Sara Akbarnejad Nesheli, Lindi J. Quackenbush, Lewis McCaffrey

“…We used Google Earth Engine (GEE) as a cloud computing platform to develop an efficient methodology to process Sentinel-2 image collections at a large spatial and temporal scale. …”
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DEM-bond model: A computational framework for designing mechanically enhanced polymer nanosphere-based ordered nanostructures by Dan Chen, Zhiren Chen, Tengfang Zhang, Zhihong Zhu, Qingwei Zhou, Fang Luo, Fan Wu, Yunming Wang, Chucai Guo

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Going, going, gone: Landscape drying reduces wetland function across the American West by J. Patrick Donnelly, Johnnie N. Moore, John S. Kimball, Kelsey Jencso, Mark Petrie, David E. Naugle

“…To improve our understanding of rapid ecosystem change, we reconstructed monthly wetland surface water hydrology in the western U.S. from 1984 to 2023 using cloud computing and ∼ 150,000 satellite images to measure shifts in the timing and duration of inundations. …”
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Synergistic use of multi-sensor satellite data for mapping crop types and land cover dynamics from 2021 to 2023 in Northeast Thailand by Savittri Ratanopad Suwanlee, Surasak Keawsomsee, Emma Izquierdo-Verdiguier, Álvaro Moreno-Martínez, Sarawut Ninsawat, Jaturong Som-ard

“…This study presents a novel classification workflow designed to generate archaic/historic and reliable land cover (LC) maps from integrating time series data from multiple EO sources—Sentinel-1, Sentinel-2, and the Highly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM)—with the Random Forest (RF) classifier and cloud computing technology. To the evaluate the effectiveness of this approach, Northeast (NE) Thailand was selected as a case study region, focusing on the classification of 14 crop types between 2021 and 2023. …”
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