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Journal articles on the topic 'Fog layer'

Author: Grafiati

Published: 6 September 2023

Last updated: 25 July 2025

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1

Yan, Shuqi, Hongbin Wang, Xiaohui Liu, Fan Zu, and Duanyang Liu. "Effect of the boundary layer low-level jet on fast fog spatial propagation." Atmospheric Chemistry and Physics 23, no. 21 (2023): 13987–4002. http://dx.doi.org/10.5194/acp-23-13987-2023.

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Abstract. The spatiotemporal variation of fog reflects the complex interactions among fog, boundary layer thermodynamics and synoptic systems. Previous studies revealed that fog can present a fast spatial propagation feature and attribute it to the boundary layer low-level jet (BLLJ), but the effect of the BLLJ on fog propagation is not quantitatively understood. Here we analyze a large-scale fog event in Jiangsu, China, from 20 to 21 January 2020. Satellite retrievals show that fog propagates from the southeast coastal area to the northwest inland area with a speed of 9.6 m s−1, which is 3 ti

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2

Singh, Sonia, Ankita Bansal, Rajinder Sandhu, and Jagpreet Sidhu. "Fog computing and IoT based healthcare support service for dengue fever." International Journal of Pervasive Computing and Communications 14, no. 2 (2018): 197–207. http://dx.doi.org/10.1108/ijpcc-d-18-00012.

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Purpose This paper has proposed a Fog architecture-based framework, which classifies dengue patients into uninfected, infected and severely infected using a data set built in 2010. The aim of this proposed framework is to developed a latency-aware system for classifying users into different categories based on their respective symptoms using Internet of Things (IoT) sensors and audio and video files. Design/methodology/approach To achieve the aforesaid aim, a smart framework is proposed, which consist of three components, namely, IoT layer, Fog infrastructure and cloud computing. The latency o

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3

Han, Yu, De Liu, Huan Wang, and Fan Hua Min. "Cause Analysis of Rainy Fog and Radiation Fog in Chongqing." Advanced Materials Research 599 (November 2012): 261–67. http://dx.doi.org/10.4028/www.scientific.net/amr.599.261.

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With the NCEP reanalysis data and L-band radar data to analyze the circulation situation and the vertical structure of temperature, humidity and wind speed of radiation fog and rainy fog in Chongqing by compositely analysis method. The result shows that: When radiation fog takes place, the 500hPa areas of Central Asia and Qinghai-Tibet plateau become high pressure ridge, and the cold front have reached the South China. When rainy fog takes place, the 500hPa area of Qinghai-Tibet plateau is controlled by the low pressure trough and the center of ground cold anticyclone will be in the northern a

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Wang, Zhao Yu, Bin Gui Wu, and He Huang. "Tower Atmosphere Characteristic of Advection Fog." Applied Mechanics and Materials 137 (October 2011): 369–73. http://dx.doi.org/10.4028/www.scientific.net/amm.137.369.

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Using the profile data observed by the Tianjin 250m Meteorological Tower, vertical distribution characteristic of meteorological elements in the advection fog on Feb. 13, 2006 has been analyzed. The results show that the meteorological elements distribution of the fog is distinct from known fog structure. The lower atmosphere state gradually became moist unstable which the temperature decreased at wet-adiabatic lapse rate and humidity increased obviously in 250m companied with the process of the low level jet stream. During the fog continuance, there is a temperature inversion layer in the sur

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Hu, Jianqiang, Keshou Wu, and Wei Liang. "An IPv6-based framework for fog-assisted healthcare monitoring." Advances in Mechanical Engineering 11, no. 1 (2019): 168781401881951. http://dx.doi.org/10.1177/1687814018819515.

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The new generation healthcare monitoring system combines technologies of wireless body sensor network, cloud computing, and Bigdata, and there are still limitations in protocol security, response delay, and prediction of potential severity disease. In response to the above situation, an Internet Protocol Version 6 (IPv6)-based framework for fog-assisted healthcare monitoring is proposed. This framework is composite of body-sensing layer, fog layer, and cloud layer. The body-sensing layer generates physiological data, and fog computing node in fog layer collects and analyses time-sensitive data

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Izett, Jonathan G., and Bas J. H. van de Wiel. "Why Does Fog Deepen? An Analytical Perspective." Atmosphere 11, no. 8 (2020): 865. http://dx.doi.org/10.3390/atmos11080865.

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The overall depth of a fog layer is one of the important factors in determining the hazard that a fog event presents. With discrete observations and often coarse numerical grids, however, fog depth cannot always be accurately determined. To address this, we derive a simple analytical relation that describes the change in depth of a fog interface with time, which depends on the tendencies and vertical gradients of moisture. We also present a lengthscale estimate for the maximum depth over which mixing can occur in order for the fog layer to be sustained, assuming a uniform mixing of the vertica

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Aleisa, Mohammed A., Abdullah Abuhussein, Faisal S. Alsubaei, and Frederick T. Sheldon. "Examining the Performance of Fog-Aided, Cloud-Centered IoT in a Real-World Environment." Sensors 21, no. 21 (2021): 6950. http://dx.doi.org/10.3390/s21216950.

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The fog layer provides substantial benefits in cloud-based IoT applications because it can serve as an aggregation layer and it moves the computation resources nearer to the IoT devices; however, it is important to ensure adequate performance is achieved in such applications, as the devices usually communicate frequently and authenticate with the cloud. This can cause performance and availability issues, which can be dangerous in critical applications such as in the healthcare sector. In this paper, we analyze the efficacy of the fog layer in different architectures in a real-world environment

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Liu, Ruolan, Duanyang Liu, Shujie Yuan, Hong Wu, Fan Zu, and Ruixiang Liu. "Double Inversion Layers Affect Fog–Haze Events over Eastern China—Based on Unmanned Aerial Vehicles Observation." Remote Sensing 15, no. 18 (2023): 4541. http://dx.doi.org/10.3390/rs15184541.

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The goal of this work is to analyze how double inversion layers affect fog–haze events and boundary layers over Eastern China based on unmanned aerial vehicle observations. During 10–12 December 2020, two successive fog–haze events occurred in Eastern China. Based on the unmanned aerial vehicle (UAV), wind, temperature, relative humidity (RH), and aerosol mass concentration were monitored simultaneously in Lianyungang, China. Several observations were found after analyzing the physical fields of these data. The results show that the concentrations of air pollutants during fog events were negat

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Mangla, Cherry, Shalli Rani, and Henry Kwame Atiglah. "Secure Data Transmission Using Quantum Cryptography in Fog Computing." Wireless Communications and Mobile Computing 2022 (January 22, 2022): 1–8. http://dx.doi.org/10.1155/2022/3426811.

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Fog computing’s idea is to bring virtual existence into objects used on a daily basis. The “objects” layer of fog architecture is also known as the smart object layer (SOL). SOL has provided the fog network with a strong platform to outperform. Although the fog architecture decentralizes data, uses more data centers, and collects and transmits it to adjacent servers for faster processing in fog networks, it faces several security challenges. The security problems of fog computing need to be alleviated for the exploitation of all benefits of fog computing in classical networks. This article has

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G., Shruthi, Monica R. Mundada, S. Supreeth, and Bryan Gardiner. "Deep Learning-based Resource Prediction and Mutated Leader Algorithm Enabled Load Balancing in Fog Computing." International Journal of Computer Network and Information Security 15, no. 4 (2023): 84–95. http://dx.doi.org/10.5815/ijcnis.2023.04.08.

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Load balancing plays a major part in improving the performance of fog computing, which has become a requirement in fog layer for distributing all workload in equal manner amongst the current Virtual machines (VMs) in a segment. The distribution of load is a complicated process as it consists of numerous users in fog computing environment. Hence, an effectual technique called Mutated Leader Algorithm (MLA) is proposed for balancing load in fogging environment. Firstly, fog computing is initialized with fog layer, cloud layer and end user layer. Then, task is submitted from end user under fog la

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11

Elmansy, Hossam, Khaled Metwally, and Khaled Badran. "Reinforcement learning-based security schema mitigating manin-the-middle attacks in fog computing." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5908–21. https://doi.org/10.11591/ijece.v13i5.pp5908-5921.

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The fast emerging of internet of things (IoTs) has introduced fog computing as an intermediate layer between end-users and the cloud datacenters. Fog computing layer characterized by its closeness to end users for service provisioning than the cloud. However, security challenges are still a big concern in fog and cloud computing paradigms as well. In fog computing, one of the most destructive attacks is man-in-the-middle (MitM). Moreover, MitM attacks are hard to be detected since they performed passively on the network level. This paper proposes a MitM mitigation scheme in fog computing archi

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Bergot, Thierry, Enric Terradellas, Joan Cuxart, et al. "Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog." Journal of Applied Meteorology and Climatology 46, no. 4 (2007): 504–21. http://dx.doi.org/10.1175/jam2475.1.

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Abstract The short-term forecasting of fog is a difficult issue that can have a large societal impact. Radiation fog appears in the surface boundary layer, and its evolution is driven by the interactions between the surface and lower layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP models are needed before improving the prediction of fog. Six numerical model simulations are compared for two cases from the Paris-Charles de Gaulle (Paris-CdG) fog field experiment. This intercomparison includes both operational and research models, which have si

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13

Li, Pengyuan, Gang Fu, Chungu Lu, Dan Fu, and Shuai Wang. "The Formation Mechanism of a Spring Sea Fog Event over the Yellow Sea Associated with a Low-Level Jet." Weather and Forecasting 27, no. 6 (2012): 1538–53. http://dx.doi.org/10.1175/waf-d-11-00152.1.

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Abstract In this paper, a dense sea fog event that occurred over the Yellow Sea (YS) on 9 March 2005 is investigated using the Weather Research and Forecasting Model version 3.1.1 (WRF v3.1.1). It is shown that the WRF can reasonably reproduce the main features of this fog case with a newly implemented planetary boundary layer (PBL) scheme developed by Mellor–Yamada–Nakanishi–Niino (MYNN). The low-level jet (LLJ) associated with this fog episode played an important role in triggering the turbulence. During the fog formation, sea fog extended vertically with the aid of turbulence. The mechanica

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Kuchuk, Heorhii, Oleksandr Mozhaiev, Serhii Tiulieniev, et al. "Devising a method for forming a stable mobile cluster of the internet of things fog layer." Eastern-European Journal of Enterprise Technologies 1, no. 4 (133) (2025): 6–14. https://doi.org/10.15587/1729-4061.2025.322263.

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The object of this study is the process of clustering the fog layer of the Internet of Things (IoT) with high and ultra-high density. The task to increase the stability of mobile components in the fog layer has been solved by modifying the clustering method. In the process of conducting research, an approach was devised to form the architecture of the mobile component in the fog layer of the IoT. The development took into account the decentralization of the fog layer and the specific features of mobile IoT devices. This has made it possible to propose a four-level architecture, which, unlike t

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15

Gultepe, I. "Fog and Boundary Layer Clouds: Introduction." Pure and Applied Geophysics 164, no. 6-7 (2007): 1115–16. http://dx.doi.org/10.1007/s00024-007-0209-4.

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Chegini, Hossein, Ranesh Kumar Naha, Aniket Mahanti, and Parimala Thulasiraman. "Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy." IoT 2, no. 1 (2021): 92–118. http://dx.doi.org/10.3390/iot2010006.

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The number of IoT sensors and physical objects accommodated on the Internet is increasing day by day, and traditional Cloud Computing would not be able to host IoT data because of its high latency. Being challenged of processing all IoT big data on Cloud facilities, there is not enough study on automating components to deal with the big data and real-time tasks in the IoT–Fog–Cloud ecosystem. For instance, designing automatic data transfer from the fog layer to cloud layer, which contains enormous distributed devices is challenging. Considering fog as the supporting processing layer, dealing w

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Elmansy, Hossam, Khaled Metwally, and Khaled Badran. "Learning agent-based security schema mitigating man-in-the-middle attacks in fog computing." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5908. http://dx.doi.org/10.11591/ijece.v13i5.pp5908-5921.

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<div style="text-align: start;" align="center"><span lang="EN-US">The fast emerging of internet of things (IoTs) has introduced fog computing as an intermediate layer between end-users and the cloud datacenters. Fog computing layer characterized by its closeness to end users for service provisioning than the cloud. However, security challenges are still a big concern in fog and cloud computing paradigms as well. In fog computing, one of the most destructive attacks is man-in-the-middle (MitM). Moreover, MitM attacks are hard to be detected since they performed passively on the netw

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18

Bergot, Thierry, and Renaud Lestringant. "On the Predictability of Radiation Fog Formation in a Mesoscale Model: A Case Study in Heterogeneous Terrain." Atmosphere 10, no. 4 (2019): 165. http://dx.doi.org/10.3390/atmos10040165.

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This study evaluates the predictability of the formation phase of a radiation fog event observed during the night of 31 October 2015 to 01 November 2015 in the north-east of France at three sites managed by OPE (Observatoire Pérenne de l’Environnement). The fog layer shows significantly different behaviors at the three areas, which are located only a few kilometers apart. Three fog life cycles were observed: the formation of a dense adiabatic fog, the formation of a thin patchy fog, or no fog formation despite favorable conditions. This event was studied with the Meso-NH numerical mesoscale mo

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19

Yazdani, Azita, Seyedeh Fatemeh Dashti, and Yeganeh Safdari. "A fog-assisted information model based on priority queue and clinical decision support systems." Health Informatics Journal 29, no. 1 (2023): 146045822311527. http://dx.doi.org/10.1177/14604582231152792.

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Objectives Telehealth monitoring applications are latency-sensitive. The current fog-based telehealth monitoring models are mainly focused on the role of the fog computing in improving response time and latency. In this paper, we have introduced a new service called “priority queue” in fog layer, which is programmed to prioritize the events sent by different sources in different environments to assist the cloud layer with reducing response time and latency. Material and Methods We analyzed the performance of the proposed model in a fog-enabled cloud environment with the IFogSim toolkit. To pro

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Xiao, Jingxu, Chaowen Chang, Ping Wu, and Yingying Ma. "Attribute identification based IoT fog data security control and forwarding." PeerJ Computer Science 9 (December 20, 2023): e1747. http://dx.doi.org/10.7717/peerj-cs.1747.

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As Internet of Things (IoT) applications continue to proliferate, traditional cloud computing is increasingly unable to meet the low-latency demands of these applications. The IoT fog architecture solves this limitation by introducing fog servers in the fog layer that are closer to the IoT devices. However, this architecture lacks authentication mechanisms for information sources, security verification for information transmission, and reasonable allocation of fog nodes. To ensure the secure transmission of end-to-end information in the IoT fog architecture, an attribute identification based s

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Ngabo, Desire, Dong Wang, Celestine Iwendi, Joseph Henry Anajemba, Lukman Adewale Ajao, and Cresantus Biamba. "Blockchain-Based Security Mechanism for the Medical Data at Fog Computing Architecture of Internet of Things." Electronics 10, no. 17 (2021): 2110. http://dx.doi.org/10.3390/electronics10172110.

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The recent developments in fog computing architecture and cloud of things (CoT) technology includes data mining management and artificial intelligence operations. However, one of the major challenges of this model is vulnerability to security threats and cyber-attacks against the fog computing layers. In such a scenario, each of the layers are susceptible to different intimidations, including the sensed data (edge layer), computing and processing of data (fog (layer), and storage and management for public users (cloud). The conventional data storage and security mechanisms that are currently i

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Alraddady, Sara, Ben Soh, Mohammed A. AlZain, and Alice S. Li. "Fog Computing: Strategies for Optimal Performance and Cost Effectiveness." Electronics 11, no. 21 (2022): 3597. http://dx.doi.org/10.3390/electronics11213597.

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The proliferation of IoT devices has amplified the challenges for cloud computing, causing bottleneck congestion which affects the delivery of the required quality of service. For some services that are delay sensitive, response time is extremely critical to avoid fatalities. Therefore, Cisco presented fog computing in 2012 to overcome such limitations. In fog computing, data processing happens geographically close to the data origin to reduce response time and decrease network and energy consumption. In this paper, a new fog computing model is presented, in which a management layer is placed

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Huang, Huijun, Hongnian Liu, Jian Huang, Weikang Mao, and Xueyan Bi. "Atmospheric Boundary Layer Structure and Turbulence during Sea Fog on the Southern China Coast." Monthly Weather Review 143, no. 5 (2015): 1907–23. http://dx.doi.org/10.1175/mwr-d-14-00207.1.

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Abstract Small-scale turbulence has an essential role in sea-fog formation and evolution, but is not completely understood. This study analyzes measurements of the small-scale turbulence, together with the boundary layer structure and the synoptic and mesoscale conditions over the life cycle of a cold advection fog event and a warm advection fog event, both off the coast of southern China. The measurement data come from two sites: one on the coast and one at sea. These findings include the following: 1) For cold advection fog, the top can extend above the inversion base, but formation of an ov

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Hrushevskyi, Oleh, Natalia Mishchenko, and Anatolii Yatsyshen. "The role of turbulent heat flows of the atmospheric boundary layer in the formation of radiation fogs." Visnyk of V.N. Karazin Kharkiv National University, series Geology. Geography. Ecology, no. 61 (December 1, 2024): 156–65. https://doi.org/10.26565/2410-7360-2024-61-13.

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Introduction. The article presents an approach to forecasting the evolution of radiation fog by determining the turbulent heat fluxes in the fog formation layer. Utilizing high temporal resolution data from atmospheric radio sondes at Lindenberg station, a database of radiation fog cases has been established. Based on the frequency of different types of stratification of the atmospheric boundary layer, it has been found that the formation of radiation fog is associated with the development of a near-surface inversion layer, where the upper boundary fluctuates between 200 and 800 meters. The ai

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Bhatt, Chintan, and C. K. Bhensdadia. "Fog Computing." International Journal of Grid and High Performance Computing 9, no. 4 (2017): 105–13. http://dx.doi.org/10.4018/ijghpc.2017100107.

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The Internet of Things could be a recent computing paradigm, defined by networks of extremely connected things – sensors, actuators and good objects – communication across networks of homes, buildings, vehicles, and even individuals whereas cloud computing could be ready to keep up with current processing and machine demands. Fog computing provides architectural resolution to deal with some of these issues by providing a layer of intermediate nodes what's referred to as an edge network [26]. These edge nodes provide interoperability, real-time interaction, and if necessary, computational to th

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Tahmasebi-Pouya, Niloofar, Mehdi-Agha Sarram, and Seyedakbar Mostafavi. "A Blind Load-Balancing Algorithm (BLBA) for Distributing Tasks in Fog Nodes." Wireless Communications and Mobile Computing 2022 (August 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/1533949.

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In the distributed infrastructure of fog computing, fog nodes (FNs) can process user requests locally. In order to reduce the delay and response time of a user’s requests, incoming requests must be evenly distributed among FNs. For this purpose, in this paper, we propose a blind load-balancing algorithm (BLBA) to improve the load distribution in the fog environment. In the proposed algorithm, the mobile device sends a task to a FN. Then, the FN decides to process that task using the Double- Q -learning algorithm. One of the critical advantages of BLBA is that decision-making on tasks is done w

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Prieto González, Lisardo, Corvin Jaedicke, Johannes Schubert, and Vladimir Stantchev. "Fog computing architectures for healthcare." Journal of Information, Communication and Ethics in Society 14, no. 4 (2016): 334–49. http://dx.doi.org/10.1108/jices-05-2016-0014.

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Purpose The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range comm

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Gudla, Surya Pavan Kumar, Sourav Kumar Bhoi, Soumya Ranjan Nayak, and Amit Verma. "DI-ADS: A Deep Intelligent Distributed Denial of Service Attack Detection Scheme for Fog-Based IoT Applications." Mathematical Problems in Engineering 2022 (August 8, 2022): 1–17. http://dx.doi.org/10.1155/2022/3747302.

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Nowadays, fog computing plays a very vital role in providing many services to end-based IoT (Internet of Things) systems. The end IoT devices communicate with the middle layer fog nodes and to the above cloud layer to process the user tasks. However, this large data communication experiences many security challenges as IoT devices are being compromised and thus the fog nodes at the fog layer are more prone to a very critical attack known as Distributed Denial of Service (DDoS) attack. The attackers or the compromised IoT devices need to be detected well in the network. Deep Learning (DL) plays

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Ijaz, Muhammad, Gang Li, Huiquan Wang, et al. "Intelligent Fog-Enabled Smart Healthcare System for Wearable Physiological Parameter Detection." Electronics 9, no. 12 (2020): 2015. http://dx.doi.org/10.3390/electronics9122015.

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Wearable technology plays a key role in smart healthcare applications. Detection and analysis of the physiological data from wearable devices is an essential process in smart healthcare. Physiological data analysis is performed in fog computing to abridge the excess latency introduced by cloud computing. However, the latency for the emergency health status and overloading in fog environment becomes key challenges for smart healthcare. This paper resolves these problems by presenting a novel tri-fog health architecture for physiological parameter detection. The overall system is built upon thre

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R.Deepika, .Kalpana R.A, Sree R.Sharmikha, and S.Meera. "Fog Assisted Computing Architecture for Healthcare IOT." Recent Trends in Cloud Computing and Web Engineering 5, no. 3 (2023): 11–16. https://doi.org/10.5281/zenodo.8207698.

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<em>IOT generates associate new knowledge that may be processed exploitation cloud computing. except for time period remote health watching applications, the delay caused by transferring information to the cloud and back to the applying is unacceptable .Due to continuous watching of Iot devices Cloud storage got accumulated with bulk of junk files. process the information in cloud takes terribly while that makes slow alerts. To reduce the delay, the patient’s real-time data is processed by fog layer using fog node by event based triggering. In Fog Layer edge level computing is performed

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Wu, Bin Gui, Zhao Yu Wang, and Yi Yang Xie. "Analysis of Air Flow and Turbulent Fluxes Features of Night Fog." Applied Mechanics and Materials 137 (October 2011): 297–301. http://dx.doi.org/10.4028/www.scientific.net/amm.137.297.

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The air flow and turbulent fluxes features during the radiation fog formed on the dawn of 17 October 2007 is discussed in order to study the mechanism of an unexpected night fog, based on the meteorological and turbulent data obtained from the 250 m height tower in Tianjin, as well as the NCEP reanalysis data and other observational data. The results show that the lower layer easterly flow coming from the south region of the Northeast cold high pressure led to remarkable temperature fall and humidity value increase in the daytime prior to the fog formation, which quickly turned the dry boundar

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Singh, Jagdeep, Parminder Singh, El Mehdi Amhoud, and Mustapha Hedabou. "Energy-Efficient and Secure Load Balancing Technique for SDN-Enabled Fog Computing." Sustainability 14, no. 19 (2022): 12951. http://dx.doi.org/10.3390/su141912951.

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The number of client applications on the fog computing layer is increasing due to advancements in the Internet of Things (IoT) paradigm. Fog computing plays a significant role in reducing latency and enhancing resource usage for IoT users’ tasks. Along with its various benefits, fog computing also faces several challenges, including challenges related to resource overloading, security, node placement, scheduling, and energy consumption. In fog computing, load balancing is a difficult challenge due to the increased number of IoT devices and requests, which requires an equal load distribution th

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Aleisa, Mohammed A., Abdullah Abuhussein, Faisal S. Alsubaei, and Frederick T. Sheldon. "Novel Security Models for IoT–Fog–Cloud Architectures in a Real-World Environment." Applied Sciences 12, no. 10 (2022): 4837. http://dx.doi.org/10.3390/app12104837.

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With the rise of the Internet of Things (IoT), there is a demand for computation at network edges because of the limited processing capacity of IoT devices. Fog computing is a middle layer that has appeared to address the latency issues between the Internet of things (IoT) and the cloud. Fog computing is becoming more important as companies face increasing challenges in collecting and sending data from IoT devices to the cloud. However, this has led to new security and privacy issues as a result of the large number of sensors in IoT environments as well as the massive amount of data that must

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Liu, Zhou-zhou, and Shi-ning Li. "Sensor-cloud data acquisition based on fog computation and adaptive block compressed sensing." International Journal of Distributed Sensor Networks 14, no. 9 (2018): 155014771880225. http://dx.doi.org/10.1177/1550147718802259.

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The emergence of sensor-cloud system has completely changed the one-to-one service mode of traditional wireless sensor networks, and it greatly expands the application field of wireless sensor networks. As the high delay of large-scale data processing tasks in sensor-cloud, a sensor-cloud data acquisition scheme based on fog computing and adaptive block compressive sensing is proposed. First, the sensor-cloud framework based on fog computing is constructed, and the fog computing layer includes many wireless mobile nodes, which helps to realize the implementation of information transfer managem

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Andersen, Hendrik, Jan Cermak, Julia Fuchs, et al. "Synoptic-scale controls of fog and low-cloud variability in the Namib Desert." Atmospheric Chemistry and Physics 20, no. 6 (2020): 3415–38. http://dx.doi.org/10.5194/acp-20-3415-2020.

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Abstract. Fog is a defining characteristic of the climate of the Namib Desert, and its water and nutrient input are important for local ecosystems. In part due to sparse observation data, the local mechanisms that lead to fog occurrence in the Namib are not yet fully understood, and to date, potential synoptic-scale controls have not been investigated. In this study, a recently established 14-year data set of satellite observations of fog and low clouds in the central Namib is analyzed in conjunction with reanalysis data in order to identify synoptic-scale patterns associated with fog and low-

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Westcott, Nancy E. "Some Aspects of Dense Fog in the Midwestern United States." Weather and Forecasting 22, no. 3 (2007): 457–65. http://dx.doi.org/10.1175/waf990.1.

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Abstract To better understand dense fog events in the midwestern United States, a fog climatology was developed that examines the surface weather conditions at dense fog onset and during dense fog events, in relationship to fog duration. Surface airways hourly observations for the period 1948–96 were examined, focusing primarily on Peoria, Illinois, during the cold season (October–March). Temperature, winds, and visibility at dense fog onset did not prove to be useful in differentiating between short- (1–2 h) and long- (&gt;5 h) duration dense fog events. However, it was found that once de

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van der Velde, I. R., G. J. Steeneveld, B. G. J. Wichers Schreur, and A. A. M. Holtslag. "Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions." Monthly Weather Review 138, no. 11 (2010): 4237–53. http://dx.doi.org/10.1175/2010mwr3427.1.

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Abstract A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high-resolution NWP model. Results by the Weather Research and Forecasting model (WRF) and the High-Resolution Limited-Area Model (HIRLAM) are evaluated against detailed observations to determine the state-of-the-art in fog forecasting and to derive requirements for further research and development. For this particular difficult case, WRF is unable to correctly simulate the fog for any of the parameterizations and model configurations utilized. Contrary, HIRLAM does model

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Sugimoto, Shiori, Tomonori Sato, and Kazuki Nakamura. "Effects of Synoptic-Scale Control on Long-Term Declining Trends of Summer Fog Frequency over the Pacific Side of Hokkaido Island." Journal of Applied Meteorology and Climatology 52, no. 10 (2013): 2226–42. http://dx.doi.org/10.1175/jamc-d-12-0192.1.

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AbstractIn this study, long-term visibility data for the Pacific Ocean side of Hokkaido Island, northeast Japan, are investigated to clarify the relationship between interannual variation in summer fog frequency (FF) and large-scale circulation patterns. At Kushiro, a significant FF decrease is found during 1931–2010 even without the influence of the observatory's relocation after 2000. In particular, since the late 1970s, a linear declining trend has accelerated, as evidenced by an increased number of years with very low FF in July and August. To clarify the climatological factor causing the

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Penov, Nikolay, and Guergana Guerova. "Sofia Airport Visibility Estimation with Two Machine-Learning Techniques." Remote Sensing 15, no. 19 (2023): 4799. http://dx.doi.org/10.3390/rs15194799.

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Fog is a weather phenomenon with visibility below 1 km. Fog heavily influences ground and air traffic, leading to accidents and delays. The main goal of this study is to use two machine-learning (ML) techniques—the random forest (RF) and long short-term memory (LSTM) models—to estimate visibility using 11 meteorological parameters. Several meteorological elements related to fog are investigated, including pressure, temperature, wind speed, and direction. The seasonal cycle shows that fog in Sofia has a peak in winter, but a small secondary peak in spring was found in this study. Fog occurrence

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Ma, Kun, Antoine Bagula, Clement Nyirenda, and Olasupo Ajayi. "An IoT-Based Fog Computing Model." Sensors 19, no. 12 (2019): 2783. http://dx.doi.org/10.3390/s19122783.

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The internet of things (IoT) and cloud computing are two technologies which have recently changed both the academia and industry and impacted our daily lives in different ways. However, despite their impact, both technologies have their shortcomings. Though being cheap and convenient, cloud services consume a huge amount of network bandwidth. Furthermore, the physical distance between data source(s) and the data centre makes delays a frequent problem in cloud computing infrastructures. Fog computing has been proposed as a distributed service computing model that provides a solution to these li

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Hu, Jianqiang, Wei Liang, Zhiyong Zeng, Yong Xie, and Jianxun Yang. "A framework for Fog-assisted healthcare monitoring." Computer Science and Information Systems 16, no. 3 (2019): 753–72. http://dx.doi.org/10.2298/csis180930025h.

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In order to tackle some challenges in ubiquitous healthcare monitoring such as mobility, scalability, and network latency, a framework for Fog-assisted healthcare monitoring is proposed in this paper. This framework is composite of body-sensing layer, Fog layer (Fog-assisted gateway), Cloud layer (health Cloud). And then, this paper makes an intensive study in some key technologies of the proposed framework such as an IPv6-based network architecture, intelligent warning model based on subband energy feature, security framework of HL7 RIM-based data exchange, health risk assessment based on fus

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Priyadarshini, Rojalina, Rabindra Kumar Barik, Harish Chandra Dubey, and Brojo Kishore Mishra. "A Survey of Fog Computing-Based Healthcare Big Data Analytics and Its Security." International Journal of Ambient Computing and Intelligence 12, no. 2 (2021): 53–72. http://dx.doi.org/10.4018/ijaci.2021040104.

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Growing use of wearables within internet of things (IoT) creates ever-increasing multi-modal data from various smart health applications. The enormous volume of data generation creates new challenges in transmission, storage, and processing. There were challenges such as communication latency and data security associated with processing medical big data in cloud backend. Fog computing (FC) is an emerging distributed computing paradigm that solved these problems by leveraging local data processing, storage, filtering, and machine intelligence within an intermediate fog layer that resides betwee

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Zhang, Lei. "Exploration of Intelligent Manufacturing Methods for Complex Products Driven by Multisource Data." Advances in Multimedia 2022 (January 12, 2022): 1–10. http://dx.doi.org/10.1155/2022/2452533.

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In order to improve the multisource data-driven fusion effect in the intelligent manufacturing process of complex products, based on the proposed adaptive fog computing architecture, this paper takes into account the efficient processing of complex product intelligent manufacturing services within the framework and the rational utilization of fog computing layer resources to establish a fog computing resource scheduling model. Moreover, this paper proposes a fog computing architecture for intelligent manufacturing services for complex products. The architecture adopts a three-layer fog computi

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Boers, R., H. Klein Baltink, H. J. Hemink, F. C. Bosveld, and M. Moerman. "Ground-Based Observations and Modeling of the Visibility and Radar Reflectivity in a Radiation Fog Layer." Journal of Atmospheric and Oceanic Technology 30, no. 2 (2013): 288–300. http://dx.doi.org/10.1175/jtech-d-12-00081.1.

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Abstract The development of a radiation fog layer at the Cabauw Experimental Site for Atmospheric Research (51.97°N, 4.93°E) on 23 March 2011 was observed with ground-based in situ and remote sensing observations to investigate the relationship between visibility and radar reflectivity. The fog layer thickness was less than 200 m. Radar reflectivity values did not exceed −25 dBZ even with visibilities less than 100 m. The onset and evaporation of fog produce different radar reflectivity–visibility relationships. The evolution of the fog layer was modeled with a droplet activation model that us

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Nagasundaram, Devamekalai, Selvakumar Manickam, Shams Ul Arfeen Laghari, and Shankar Karuppayah. "Proposed fog computing-enabled conceptual model for semantic interoperability in internet of things." Bulletin of Electrical Engineering and Informatics 13, no. 2 (2024): 1183–96. http://dx.doi.org/10.11591/eei.v13i2.5748.

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Semantic interoperability has emerged as a key barrier amidst the major developments and challenges brought about by the rapid expansion of internet of things (IoT) applications. Establishing interoperability is essential for IoT systems to function optimally, especially across diverse organizations. Despite extensive research in achieving semantic interoperability, dynamic interoperability, a vital facet, remains inadequately addressed. This paper addresses this gap by presenting a fog-based conceptual model designed to facilitate dynamic semantic interoperability in IoT. The model incorporat

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Giles Harrison, R., Keri A. Nicoll, and Maarten HP Ambaum. "Charge in non-thunderstorm clouds and fogs." Journal of Physics: Conference Series 2702, no. 1 (2024): 012001. http://dx.doi.org/10.1088/1742-6596/2702/1/012001.

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Abstract The global atmospheric electric circuit links charge separation in thunderclouds with current flow throughout the atmosphere. This current flow causes charge accumulation on the upper and lower boundaries of clouds and fogs. Thunderclouds are therefore not the only charged clouds in the atmosphere, and other forms of clouds, especially extensive horizontal layer clouds (stratus) are much more abundant globally. To investigate possible effects of charging of natural droplets in clouds, experiments have been undertaken using corona ion emission into fogs, releasing from within and above

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Liu, Shuo, Li Tian, Zhongyan Lu, Han Sai, Chenghan Liu, and Ping Li. "The Boundary Layer Characteristics and Development Mechanism of a Warm Advective Fog Event over the Yellow Sea." Journal of Physics: Conference Series 2486, no. 1 (2023): 012004. http://dx.doi.org/10.1088/1742-6596/2486/1/012004.

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Abstract A large-scale persistent fog event occurred over the Yellow Sea of China from April 27 to May 4, 2015. In this study, we used satellite remote sensing data, ground meteorological observed data, global sounding data, and reanalysis data from the National Centers for Environmental Prediction (NCEP) and sea surface temperature (SST) data from the National Oceanic and Atmospheric Administration (NOAA) to analyze the evolutionary characteristics, the boundary-layer marine meteorological characteristics, and the development mechanism of the sea fog event. The results show that the sea fog e

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Zhang, Li, Hao Shi, Shanhong Gao, and Shun Li. "Overestimated Fog-Top Entrainment in WRF Simulation Leading to Unrealistic Dissipation of Sea Fog: A Case Study." Remote Sensing 16, no. 10 (2024): 1656. http://dx.doi.org/10.3390/rs16101656.

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Entrainment at the top of the planetary boundary layer (PBL) is of significant importance because it controls the upward growth of the PBL height. An option called ysu_topdown_pblmix, which provides a parameterization of fog-top entrainment, has been proposed for valley fog modeling and introduced into the YSU (Yonsei University) PBL scheme in the Weather Research and Forecasting (WRF) model. However, enabling this option in simulations of sea fog over the Yellow Sea typically results in unrealistic dissipation near the fog bottom and even within the entire fog layer. In this study, we theoret

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Yang, Liu, Saisai Ding, Jing-Wu Liu, and Su-Ping Zhang. "Effects of radiative cooling on advection fog over the northwest Pacific Ocean: observations and large-eddy simulations." Atmospheric Chemistry and Physics 24, no. 11 (2024): 6809–24. http://dx.doi.org/10.5194/acp-24-6809-2024.

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Abstract. During boreal summer, prevailing southerlies traverse the sharp sea surface temperature (SST) front in the northwest Pacific (NWP) Ocean, creating a stable air–sea interface characterized by surface air temperature (SAT) higher than SST, which promotes the frequent occurrence of advection fog. However, long-term shipborne observations reveal that during episodes of advection fog, SAT usually decreases below SST, with a peak relative frequency (∼ 34.5 %) in all fog observations before sunrise and a minimum relative frequency (∼ 18.8 %) before sunset. From a Lagrangian perspective, thi

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Na, Uikyun, and Eun-Kyu Lee. "Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System." Sustainability 12, no. 7 (2020): 2831. http://dx.doi.org/10.3390/su12072831.

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It has been found that a cloud building energy management system (BEMS) alone cannot support increasing numbers of end devices (e.g., energy equipment and IoT devices) and emerging energy services efficiently. To resolve these limitations, this paper proposes Fog BEMS, which applies an emerging fog computing concept to a BEMS. Fog computing places small computing resources (fog nodes) just next to end devices, and these nodes process data in real time and manage local contexts. In this way, the BEMS becomes distributed and scalable. However, existing fog computing models have barely considered

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