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Journal articles on the topic 'Network embedded cloud'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Wang, Jinglu, Bo Sun, and Yan Lu. "MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8949–56. http://dx.doi.org/10.1609/aaai.v33i01.33018949.

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In this paper, we address the problem of reconstructing an object’s surface from a single image using generative networks. First, we represent a 3D surface with an aggregation of dense point clouds from multiple views. Each point cloud is embedded in a regular 2D grid aligned on an image plane of a viewpoint, making the point cloud convolution-favored and ordered so as to fit into deep network architectures. The point clouds can be easily triangulated by exploiting connectivities of the 2D grids to form mesh-based surfaces. Second, we propose an encoder-decoder network that generates such kind

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Yan, Yan, Yuxing Mao, and Bo Li. "SECOND: Sparsely Embedded Convolutional Detection." Sensors 18, no. 10 (2018): 3337. http://dx.doi.org/10.3390/s18103337.

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LiDAR-based or RGB-D-based object detection is used in numerous applications, ranging from autonomous driving to robot vision. Voxel-based 3D convolutional networks have been used for some time to enhance the retention of information when processing point cloud LiDAR data. However, problems remain, including a slow inference speed and low orientation estimation performance. We therefore investigate an improved sparse convolution method for such networks, which significantly increases the speed of both training and inference. We also introduce a new form of angle loss regression to improve the

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Ghassemi, Sina, and Enrico Magli. "Convolutional Neural Networks for On-Board Cloud Screening." Remote Sensing 11, no. 12 (2019): 1417. http://dx.doi.org/10.3390/rs11121417.

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A cloud screening unit on a satellite platform for Earth observation can play an important role in optimizing communication resources by selecting images with interesting content while skipping those that are highly contaminated by clouds. In this study, we address the cloud screening problem by investigating an encoder–decoder convolutional neural network (CNN). CNNs usually employ millions of parameters to provide high accuracy; on the other hand, the satellite platform imposes hardware constraints on the processing unit. Hence, to allow an onboard implementation, we investigate experimental

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Zhang, Chunjiao, Shenghua Xu, Tao Jiang, et al. "Integrating Normal Vector Features into an Atrous Convolution Residual Network for LiDAR Point Cloud Classification." Remote Sensing 13, no. 17 (2021): 3427. http://dx.doi.org/10.3390/rs13173427.

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LiDAR point clouds are rich in spatial information and can effectively express the size, shape, position, and direction of objects; thus, they have the advantage of high spatial utilization. The point cloud focuses on describing the shape of the external surface of the object itself and will not store useless redundant information to describe the occupation. Therefore, point clouds have become the research focus of 3D data models and are widely used in large-scale scene reconstruction, virtual reality, digital elevation model production, and other fields. Since point clouds have various charac

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Dybedal, Joacim, Atle Aalerud, and Geir Hovland. "Embedded Processing and Compression of 3D Sensor Data for Large Scale Industrial Environments." Sensors 19, no. 3 (2019): 636. http://dx.doi.org/10.3390/s19030636.

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This paper presents a scalable embedded solution for processing and transferring 3D point cloud data. Sensors based on the time-of-flight principle generate data which are processed on a local embedded computer and compressed using an octree-based scheme. The compressed data is transferred to a central node where the individual point clouds from several nodes are decompressed and filtered based on a novel method for generating intensity values for sensors which do not natively produce such a value. The paper presents experimental results from a relatively large industrial robot cell with an ap

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Hu, Jin-Xin, Chin-Ling Chen, Chun-Long Fan, and Kun-hao Wang. "An Intelligent and Secure Health Monitoring Scheme Using IoT Sensor Based on Cloud Computing." Journal of Sensors 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/3734764.

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Internet of Things (IoT) is the network of physical objects where information and communication technology connect multiple embedded devices to the Internet for collecting and exchanging data. An important advancement is the ability to connect such devices to large resource pools such as cloud. The integration of embedded devices and cloud servers offers wide applicability of IoT to many areas of our life. With the aging population increasing every day, embedded devices with cloud server can provide the elderly with more flexible service without the need to visit hospitals. Despite the advanta

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Lee, Hyunsoo. "Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System." Processes 7, no. 3 (2019): 172. http://dx.doi.org/10.3390/pr7030172.

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Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend to the control of a key supplier’s real-time production planning for solving joint production goals with downstream producers. As a key supplier has several downstream producers in general, several uncertainties are embedded on the supply chain network such as the quality issue

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Issac, Namitha, Anandmayee Tej, Tie Liu, and Yuefang Wu. "G133.50+9.01: a likely cloud–cloud collision complex triggering the formation of filaments, cores, and a stellar cluster." Monthly Notices of the Royal Astronomical Society 499, no. 3 (2020): 3620–29. http://dx.doi.org/10.1093/mnras/staa3061.

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ABSTRACT We present compelling observational evidence of G133.50+9.01 being a bona fide cloud–cloud collision candidate with signatures of induced filament, core, and cluster formation. The CO molecular line observations reveal that the G133.50+9.01 complex is made of two colliding molecular clouds with systemic velocities, $\rm -16.9$ and $\rm -14.1\, km\, s^{-1}$. The intersection of the clouds is characterized by broad bridging features characteristic of collision. The morphology of the shocked layer at the interaction front resembles an arc-like structure with enhanced excitation temperatu

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Espinosa-Aranda, Jose, Noelia Vallez, Jose Rico-Saavedra, et al. "Smart Doll: Emotion Recognition Using Embedded Deep Learning." Symmetry 10, no. 9 (2018): 387. http://dx.doi.org/10.3390/sym10090387.

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Computer vision and deep learning are clearly demonstrating a capability to create engaging cognitive applications and services. However, these applications have been mostly confined to powerful Graphic Processing Units (GPUs) or the cloud due to their demanding computational requirements. Cloud processing has obvious bandwidth, energy consumption and privacy issues. The Eyes of Things (EoT) is a powerful and versatile embedded computer vision platform which allows the user to develop artificial vision and deep learning applications that analyse images locally. In this article, we use the deep

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Srirampavan, J. "Smart Secured Real Time Agriculture Monitoring System." International Journal of Engineering & Technology 7, no. 3.6 (2018): 281. http://dx.doi.org/10.14419/ijet.v7i3.6.15043.

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Embedded systems in Agriculture play a vital role in unifying the work involved and improve conservations. Designing a smart as well as a cost efficient and more user-friendly system will be idealistic challenge. The following system that has been proposed is designed with those ideal constraints in mind. It consists of a Raspberry pi3 as a gateway that links the sensor networks with the cloud. To improve security an MQTT protocol is used for cloud connectivity. The communication between the sensor networks is managed by NRF24L01. The Sensor network is a separate entity that can used like a pl

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Okafor, K. C., Ifeyinwa E. Achumba, Gloria A. Chukwudebe, and Gordon C. Ononiwu. "Leveraging Fog Computing for Scalable IoT Datacenter Using Spine-Leaf Network Topology." Journal of Electrical and Computer Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/2363240.

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With the Internet of Everything (IoE) paradigm that gathers almost every object online, huge traffic workload, bandwidth, security, and latency issues remain a concern for IoT users in today’s world. Besides, the scalability requirements found in the current IoT data processing (in the cloud) can hardly be used for applications such as assisted living systems, Big Data analytic solutions, and smart embedded applications. This paper proposes an extended cloud IoT model that optimizes bandwidth while allowing edge devices (Internet-connected objects/devices) to smartly process data without relyi

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Jing, Zhuangwei, Haiyan Guan, Peiran Zhao, et al. "Multispectral LiDAR Point Cloud Classification Using SE-PointNet++." Remote Sensing 13, no. 13 (2021): 2516. http://dx.doi.org/10.3390/rs13132516.

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A multispectral light detection and ranging (LiDAR) system, which simultaneously collects spatial geometric data and multi-wavelength intensity information, opens the door to three-dimensional (3-D) point cloud classification and object recognition. Because of the irregular distribution property of point clouds and the massive data volume, point cloud classification directly from multispectral LiDAR data is still challengeable and questionable. In this paper, a point-wise multispectral LiDAR point cloud classification architecture termed as SE-PointNet++ is proposed via integrating a Squeeze-a

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Gao, Yan Zeng, and Ling Yan Wei. "Implementation of Smart Home System Based on Internet of Things." Applied Mechanics and Materials 475-476 (December 2013): 1150–53. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.1150.

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Smart home can apply new internet of things concepts along cloud service technologies. This paper introduces a novel method for smart home system building. The system is driven by use case and it is composed of home control center, zigbee end devices, smart phone applications and cloud server. The home control center is based on arm-linux embedded system, it is the relay of cloud server and home devices. Wireless network of smart home devices was designed according to zigbee. A smart phone application was developed as the role of the user interface.

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Lian, Kuang Yow, Sung Jung Hsiao, and Wen Tsai Sung. "Employing Remote Mobile Scheme to Control Work Area via an Integrated Wireless Network." Applied Mechanics and Materials 423-426 (September 2013): 2419–22. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2419.

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This paper proposed method is to use a Smart phone in the real - time situation to carry out monitoring and controlling factory zone temperature, humidity, carbon dioxide concentration, the flame sensor. The size of the operation of the machine vibration frequency, butalso through smart phones to monitor and control, these methods are innovative research. Our research proposes the integration of ZigBee and Wi-Fi protocol intelligent monitoring system within the framework of the entire plant. The factory sensor using the ZigBee protocol to deliver the message, and real-time sensing data is sent

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Gupta, Shashank, and B. B. Gupta. "Smart XSS Attack Surveillance System for OSN in Virtualized Intelligence Network of Nodes of Fog Computing." International Journal of Web Services Research 14, no. 4 (2017): 1–32. http://dx.doi.org/10.4018/ijwsr.2017100101.

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This article introduces a distributed intelligence network of Fog computing nodes and Cloud data centres for smart devices against XSS vulnerabilities in Online Social Network (OSN). The cloud data centres compute the features of JavaScript, injects them in the form of comments and saved them in the script nodes of Document Object Model (DOM) tree. The network of Fog devices re-executes the feature computation and comment injection process in the HTTP response message and compares such comments with those calculated in the cloud data centres. Any divergence observed will simply alarm the signa

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Huang, R., Z. Ye, D. Hong, Y. Xu, and U. Stilla. "SEMANTIC LABELING AND REFINEMENT OF LIDAR POINT CLOUDS USING DEEP NEURAL NETWORK IN URBAN AREAS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W7 (September 16, 2019): 63–70. http://dx.doi.org/10.5194/isprs-annals-iv-2-w7-63-2019.

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<p><strong>Abstract.</strong> In this paper, we propose a framework for obtaining semantic labels of LiDAR point clouds and refining the classification results by combining a deep neural network with a graph-structured smoothing technique. In general, the goal of the semantic scene analysis is to assign a semantic label to each point in the point cloud. Although various related researches have been reported, due to the complexity of urban areas, the semantic labeling of point clouds in urban areas is still a challenging task. In this paper, we address the issues of how to eff

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Singh, Om Prakash, Ranjith Ranjith C. S, Karthik R., Sandeep Reddy, and Rashmi Soni. "Survey Report on Sending Data Securely using IOT Over Cloud." International Journal of Recent Technology and Applied Science 2, no. 1 (2020): 75–80. http://dx.doi.org/10.36079/lamintang.ijortas-0201.76.

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Survey Report on Sending Data Securely using IOT Over Cloud The Internet of Things (IOT) is the network of physical objects, computers, cars, houses, and other things embedded with electronics, software, sensors, and network connectivity, allowing these objects to collect and exchange data. In the new technology market, IOT innovations is the next major step, but with the big difference that it brings about massive changes in business usability. A flare in the number of connected devices as well as placed locations is anticipated over the next few years and the functions that they will p

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Testoni, Nicola, Cristiano Aguzzi, Valentina Arditi, et al. "A Sensor Network with Embedded Data Processing and Data-to-Cloud Capabilities for Vibration-Based Real-Time SHM." Journal of Sensors 2018 (July 2, 2018): 1–12. http://dx.doi.org/10.1155/2018/2107679.

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This work describes a network of low power/low-cost microelectromechanical- (MEMS-) based three-axial acceleration sensors with local data processing and data-to-cloud capabilities. In particular, the developed sensor nodes are capable to acquire acceleration time series and extract their frequency spectrum peaks, which are autonomously sent through an ad hoc developed gateway device to an online database using a dedicated transfer protocol. The developed network minimizes the power consumption to monitor remotely and in real time the acceleration spectra peaks at each sensor node. An experime

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Huang, Chung Chi, Chung Lin Huang, Cong Hui Huang, and Sheng Fone Yang. "Design and Implementation of Cloud-Dust Based Intelligent System." Applied Mechanics and Materials 764-765 (May 2015): 872–76. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.872.

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In the paper, design and Implementation of cloud-dust based intelligent system is proposed. For achieving applications of intelligent system, such as records, surveillance, assessments, predictions, diagnosis, prescription, scheduling and fool-proofing checks, an architecture named Cloud-Dust is developed. The intelligent system is separated into the cloud system and the dust system. The dust system contains (1) Wireless sensors network (2) Features extraction circuits (3) Intelligent computing circuits (4) Embedded system. It can play a role as real-time preprocessor very well, just like an i

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Li, Lei, Min Feng, Lianwen Jin, Shenjin Chen, Lihong Ma, and Jiakai Gao. "Domain Knowledge Embedding Regularization Neural Networks for Workload Prediction and Analysis in Cloud Computing." Journal of Information Technology Research 11, no. 4 (2018): 137–54. http://dx.doi.org/10.4018/jitr.2018100109.

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Online services are now commonly deployed via cloud computing based on Infrastructure as a Service (IaaS) to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). However, workload is not constant over time, so guaranteeing the quality of service (QoS) and resource cost-effectiveness, which is determined by on-demand workload resource requirements, is a challenging issue. In this article, the authors propose a neural network-based-method termed domain knowledge embedding regularization neural networks (DKRNN) for large-scale workload prediction. Based on analyzing the statistical prop

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Zhang, Jun, Yuan Sheng Liu, and Lin Xue. "A Remote Monitoring System Based on Measuring Instrument Cloud." Advanced Materials Research 1014 (July 2014): 525–29. http://dx.doi.org/10.4028/www.scientific.net/amr.1014.525.

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A remote lab room monitoring system based on measuring instrument cloud is presented in this paper. The system consists of cloud computing center, embedded front-end acquisition hardware, mobile terminal device, and network equipment. Measuring service software system located in cloud computing center sends control commands to front-end acquisition hardware and collects acquisition data. Then processing, analysis and integration of signals are completed in the cloud computing framework. Finally, all the information can be interacted with mobile terminals by Web service. The system can monitor

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Mora Mora, Higinio, David Gil, José Francisco Colom López, and María Teresa Signes Pont. "Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm." Mobile Information Systems 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/652462.

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The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling me

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Tsang, Philip. "Allegory of the Global Anglophone: Interconnectedness and Sublimity in Cloud Atlas." Novel 51, no. 3 (2018): 399–416. http://dx.doi.org/10.1215/00295132-7086444.

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Abstract The article situates David Mitchell's imagination of planetary interconnectedness in the historical development of global English. It argues that Cloud Atlas projects a denationalized, centrifugal vision of the world, only to entrench it in a cohesive, centripetal anglophone network through fictionalized scenes of reading. The novel assigns the English text a privileged position in fostering global connections and renders its cultural other unrepresentable in order to maintain a coherent representational system over a heterolingual world. Mitchell's imagination of a textually embedded

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Lee, Hakjun, Dongwoo Kang, Youngsook Lee, and Dongho Won. "Secure Three-Factor Anonymous User Authentication Scheme for Cloud Computing Environment." Wireless Communications and Mobile Computing 2021 (July 27, 2021): 1–20. http://dx.doi.org/10.1155/2021/2098530.

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Cloud computing provides virtualized information technology (IT) resources to ensure the workflow desired by user at any time and location; it allows users to borrow computing resources such as software, storage, and servers, as per their needs without the requirements of complicated network and server configurations. With the generalization of small embedded sensor devices and the commercialization of the Internet of Things (IoT), short- and long-range wireless network technologies are being developed rapidly, and the demand for deployment of cloud computing for IoT is increasing significantl

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Scirè, Alessandro, Fabrizio Tropeano, Aris Anagnostopoulos, and Ioannis Chatzigiannakis. "Fog-Computing-Based Heartbeat Detection and Arrhythmia Classification Using Machine Learning." Algorithms 12, no. 2 (2019): 32. http://dx.doi.org/10.3390/a12020032.

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Designing advanced health monitoring systems is still an active research topic. Wearable and remote monitoring devices enable monitoring of physiological and clinical parameters (heart rate, respiration rate, temperature, etc.) and analysis using cloud-centric machine-learning applications and decision-support systems to predict critical clinical states. This paper moves from a totally cloud-centric concept to a more distributed one, by transferring sensor data processing and analysis tasks to the edges of the network. The resulting solution enables the analysis and interpretation of sensor-da

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Kumar, Sumit, and Zahid Raza. "Internet of Things." International Journal of Systems and Service-Oriented Engineering 7, no. 3 (2017): 32–52. http://dx.doi.org/10.4018/ijssoe.2017070103.

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Internet of Things (IoT) is a novel approach of connecting things/objects and thus transmitting information between various entities of the physical world or to the control centers where this information can be interpreted. IoT has been poised as the next evolution of internet promising to change our lives by involving a seamless access to people and devices in a ubiquitous way leading to a smart world. These devices, often referred to as smart items or intelligent things can be home appliances, healthcare devices, vehicles, buildings, factories and almost anything networked and fitted with se

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U, Dhanush, Prasannasai S Hulikatti, Raghavendra H Malager, Sandur Shreesha, and Prakash Biswagar. "A Secure File Transfer over Virtual Machine Instances using Hybrid Encryption Technique." Journal of University of Shanghai for Science and Technology 23, no. 06 (2021): 77–84. http://dx.doi.org/10.51201/jusst/21/05219.

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Cloud Computing is used to share data, services, and resources via a network but this system is vulnerable to cyber-attacks by an unauthorized person denying the user privacy and confidentiality. The exponential growth in Information technology especially in the field of Cloud Computing has seen a rise in security attacks such as Interruption, Interception, Modification, Fabrication making it absolutely necessary to enhance cloud security as well as network security. To tackle the menace of security threats is to make use of the various encryption techniques and to ensure secure transmission o

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Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev, and Arnold Kiv. "Using spreadsheets as learning tools for computer simulation of neural networks." SHS Web of Conferences 75 (2020): 04018. http://dx.doi.org/10.1051/shsconf/20207504018.

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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet ad

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Luo, Nan, Hongquan Yu, Zhenfeng Huo, et al. "KVGCN: A KNN Searching and VLAD Combined Graph Convolutional Network for Point Cloud Segmentation." Remote Sensing 13, no. 5 (2021): 1003. http://dx.doi.org/10.3390/rs13051003.

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Semantic segmentation of the sensed point cloud data plays a significant role in scene understanding and reconstruction, robot navigation, etc. This work presents a Graph Convolutional Network integrating K-Nearest Neighbor searching (KNN) and Vector of Locally Aggregated Descriptors (VLAD). KNN searching is utilized to construct the topological graph of each point and its neighbors. Then, we perform convolution on the edges of constructed graph to extract representative local features by multiple Multilayer Perceptions (MLPs). Afterwards, a trainable VLAD layer, NetVLAD, is embedded in the fe

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Alessandrini, Michele, Giorgio Biagetti, Paolo Crippa, Laura Falaschetti, and Claudio Turchetti. "Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data." Electronics 10, no. 14 (2021): 1715. http://dx.doi.org/10.3390/electronics10141715.

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Photoplethysmography (PPG) is a common and practical technique to detect human activity and other physiological parameters and is commonly implemented in wearable devices. However, the PPG signal is often severely corrupted by motion artifacts. The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low cost, low power microcontroller, ensuring the required performance in terms of accuracy and low complexity. To reach this goal, (i) we first develop an RNN, which integrates PPG and tri-axial accele

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Et.al, S. V. Manikanthan. "Implementation and Design of Wireless IoT Network using Deep Learning." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 563–72. http://dx.doi.org/10.17762/turcomat.v12i3.761.

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The Internet of Things (IoT) is a technology and plays a key role in just this process. In designing better cities,embedded devices include this new technology, which the internet is similar to everybody. IoT solutions are spread through different regions, such as agriculture, healthcare, the motor industry, education, and home automation, etc. wireless communication (WC) is now becoming an efficient role for incorporating wireless communicationenvironment, computers, organizations, and governments. WC is a budding technology in IoT, and it involves further learning. This dilemma motivates the

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Pires, Felipe Marques, Leonardo de Souza Mendes, and Lorena León Quiñonez. "Integrated system architecture for decision-making and urban planning in smart cities." International Journal of Distributed Sensor Networks 15, no. 8 (2019): 155014771986782. http://dx.doi.org/10.1177/1550147719867829.

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Research and development of applications for smart cities are extremely relevant considering the various problems that population growth will bring to large urban centers in the next few years. Although research on cyber-physical systems, cloud computing, embedded devices, sensor and actuator networks, and participatory sensing, among other paradigms, is driving the growth of solutions, there are a lot of challenges that need to be addressed. Based on these observations, in this work, we present an integrated system architecture for decision-making support and urban planning by introducing its

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Balakrishna, Sunil, and Rama Parvathy L. "Distributed Network for Health Diagnosis Using Blockchain for Early Analysis and Detection of Health Aliment’s." International Journal of Engineering & Technology 7, no. 3.12 (2018): 449. http://dx.doi.org/10.14419/ijet.v7i3.12.16127.

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Information technology plays very important role in the healthcare sector and as new technology are introduced the potential of those technologies are tried out to see how better the healthcare sector could get advantage of these new technologies. From the time of internet age, the healthcare sector has undergone massive changes and with new technologies like Cloud Computing has bought enormous possibilities in having Personal Health Record (PHR) management. One of such latest technology which has been successfullytested and getting introduced is Blockchain. The growing interest in utilizing t

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Giuffrida, Gianluca, Lorenzo Diana, Francesco de Gioia, et al. "CloudScout: A Deep Neural Network for On-Board Cloud Detection on Hyperspectral Images." Remote Sensing 12, no. 14 (2020): 2205. http://dx.doi.org/10.3390/rs12142205.

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The increasing demand for high-resolution hyperspectral images from nano and microsatellites conflicts with the strict bandwidth constraints for downlink transmission. A possible approach to mitigate this problem consists in reducing the amount of data to transmit to ground through on-board processing of hyperspectral images. In this paper, we propose a custom Convolutional Neural Network (CNN) deployed for a nanosatellite payload to select images eligible for transmission to ground, called CloudScout. The latter is installed on the Hyperscout-2, in the frame of the Phisat-1 ESA mission, which

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Han, Chunqing, and Lin Li. "Design of Wireless Sensing Virtual Cloud Desktop System Based on ARM-Linux." International Journal of Online Engineering (iJOE) 13, no. 10 (2017): 123. http://dx.doi.org/10.3991/ijoe.v13i10.7743.

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Aiming at exploring the wireless sensing network with mass processing in data collection, an embedded wireless sensor system based on ARM-Linux is put forward and designed. The whole system is mainly divided into wireless ZigBee sensing node group part, ARM data processing part, and virtual cloud desktop terminal part. Users’ terminal can be connected to the cloud system server through wired or wireless ways. And it is possible to view user system data and wireless terminal data by logging in to an individual account. The results showed that the system can be applied in a lot of fields, such a

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Alsharif, Maram, and Danda B. Rawat. "Study of Machine Learning for Cloud Assisted IoT Security as a Service." Sensors 21, no. 4 (2021): 1034. http://dx.doi.org/10.3390/s21041034.

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Machine learning (ML) has been emerging as a viable solution for intrusion detection systems (IDS) to secure IoT devices against different types of attacks. ML based IDS (ML-IDS) normally detect network traffic anomalies caused by known attacks as well as newly introduced attacks. Recent research focuses on the functionality metrics of ML techniques, depicting their prediction effectiveness, but overlooked their operational requirements. ML techniques are resource-demanding that require careful adaptation to fit the limited computing resources of a large sector of their operational platform, n

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Mohamad, Mohd Saiful Adli, Roshidi Din, and Jasmin Ilyani Ahmad. "Research trends review on RSA scheme of asymmetric cryptography techniques." Bulletin of Electrical Engineering and Informatics 10, no. 1 (2021): 487–92. http://dx.doi.org/10.11591/eei.v10i1.2493.

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One of the cryptography classifications is asymmetric cryptography, which uses two different keys to encrypt and decrypt the message. This paper discusses a review of RSA scheme of asymmetric cryptography techniques. It is trying to present the domains of RSA scheme used including in public network, wireless sensor network, image encryption, cloud computing, proxy signature, Internet of Things and embedded device, based on the perspective of researchers’ effort in the last decade. Other than that, this paper reviewed the trends and the performance metrics of RSA scheme such as security, speed,

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Hang, Lei, Wenquan Jin, HyeonSik Yoon, Yong Hong, and Do Kim. "Design and Implementation of a Sensor-Cloud Platform for Physical Sensor Management on CoT Environments." Electronics 7, no. 8 (2018): 140. http://dx.doi.org/10.3390/electronics7080140.

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The development of the Internet of Things (IoT) has increased the ubiquity of the Internet by integrating all objects for interaction via embedded systems, leading to a highly distributed network of devices communicating with human beings as well as other devices. In recent years, cloud computing has attracted a lot of attention from specialists and experts around the world. With the increasing number of distributed sensor nodes in wireless sensor networks, new models for interacting with wireless sensors using the cloud are intended to overcome restricted resources and efficiency. In this pap

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Cabanes, Quentin, Benaoumeur Senouci, and Amar Ramdane-Cherif. "Embedded Deep Learning Prototyping Approach for Cyber-Physical Systems: Smart LIDAR Case Study." Journal of Sensor and Actuator Networks 10, no. 1 (2021): 18. http://dx.doi.org/10.3390/jsan10010018.

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Cyber-Physical Systems (CPSs) are a mature research technology topic that deals with Artificial Intelligence (AI) and Embedded Systems (ES). They interact with the physical world via sensors/actuators to solve problems in several applications (robotics, transportation, health, etc.). These CPSs deal with data analysis, which need powerful algorithms combined with robust hardware architectures. On one hand, Deep Learning (DL) is proposed as the main solution algorithm. On the other hand, the standard design and prototyping methodologies for ES are not adapted to modern DL-based CPS. In this pap

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Azrour, Mourade, Jamal Mabrouki, and Rajasekhar Chaganti. "New Efficient and Secured Authentication Protocol for Remote Healthcare Systems in Cloud-IoT." Security and Communication Networks 2021 (May 7, 2021): 1–12. http://dx.doi.org/10.1155/2021/5546334.

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Recently, Internet of Things and cloud computing are known to be emerged technologies in digital evolution. The first one is a large network used to interconnect embedded devices, while the second one refers to the possibility of offering infrastructure that can be used from anywhere and anytime. Due to their ability to provide remote services, IoT and cloud computing are actually integrated in various areas especially in the healthcare domain. However, the user private data such as health data must be secured by enhancing the authentication methods. Recently, Sharma and Kalra projected an aut

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Liu, Weiquan, Cheng Wang, Xuesheng Bian, et al. "AE-GAN-Net: Learning Invariant Feature Descriptor to Match Ground Camera Images and a Large-Scale 3D Image-Based Point Cloud for Outdoor Augmented Reality." Remote Sensing 11, no. 19 (2019): 2243. http://dx.doi.org/10.3390/rs11192243.

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Establishing the spatial relationship between 2D images captured by real cameras and 3D models of the environment (2D and 3D space) is one way to achieve the virtual–real registration for Augmented Reality (AR) in outdoor environments. In this paper, we propose to match the 2D images captured by real cameras and the rendered images from the 3D image-based point cloud to indirectly establish the spatial relationship between 2D and 3D space. We call these two kinds of images as cross-domain images, because their imaging mechanisms and nature are quite different. However, unlike real camera image

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Retikal, Anil Kumar. "Complicity of High-End SOC-FPGA’s for Data Centers." International Journal of Recent Technology and Engineering 9, no. 6 (2021): 6–10. http://dx.doi.org/10.35940/ijrte.f5352.039621.

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As the network traffic increasing significantly due to increase in Data streaming, Big Data Analytics, Cloud Computing, Increasing the load on Data Centers, Which leads to demand for high computational capabilities, low latency, high-bandwidth, power efficient data accelerators. As Re-Configurability of FPGA’s are more flexible for developing customized applications, so the FPGA hardware based data accelerators are the potential devices to achieve low latency and power efficient requirements. The modern FPGA’s are coming up with the embedded communication hard IP’s like PCIe, Ethernet, & D

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Ferrández-Pastor, Francisco Javier, Juan Manuel García-Chamizo, Sergio Gomez-Trillo, Rafael Valdivieso-Sarabia, and Mario Nieto-Hidalgo. "Smart Management Consumption in Renewable Energy Fed Ecosystems." Sensors 19, no. 13 (2019): 2967. http://dx.doi.org/10.3390/s19132967.

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Advances in embedded electronic systems, the development of new communication protocols, and the application of artificial intelligence paradigms have enabled the improvement of current automation systems of energy management. Embedded devices integrate different sensors with connectivity, computing resources, and reduced cost. Communication and cloud services increase their performance; however, there are limitations in the implementation of these technologies. If the cloud is used as the main source of services and resources, overload problems will occur. There are no models that facilitate

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Leary, Lesley A., and Elizabeth A. Ritchie. "Lightning Flash Rates as an Indicator of Tropical Cyclone Genesis in the Eastern North Pacific." Monthly Weather Review 137, no. 10 (2009): 3456–70. http://dx.doi.org/10.1175/2009mwr2822.1.

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Abstract Lightning flashes in convective tropical clusters of the eastern North Pacific Ocean are detected by the Long-Range Lightning Detection Network and are analyzed for temporal patterns in electrical activity. The rates of lightning flash discharge in the 2006 season are analyzed for both tropical cyclones and nondeveloping cloud clusters to 1) determine if there is a difference in the convective activity of these two populations and 2) find a level of electrical activity that constitutes development in a particular system. Convective activity is associated with tropical cyclogenesis and

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Haryanto, Eri, and Imam Riadi. "Forensik Internet Of Things pada Device Level berbasis Embedded System." Jurnal Teknologi Informasi dan Ilmu Komputer 6, no. 6 (2019): 703. http://dx.doi.org/10.25126/jtiik.2019661828.

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<p>Perangkat Internet of Things (IoT) merupakan perangkat cerdas yang memiliki interkoneksi dengan jaringan internet global. Investigasi kasus yang menyangkut perangkat IoT akan menjadi tantangan tersendiri bagi investigator forensik. Keberagaman jenis perangkat dan teknologi akan memunculkan tantangan baru bagi investigator forensik. Dalam penelitian ini dititikberatkan forensik di level internal device perangkat IoT. Belum banyak bahkan belum penulis temukan penelitian sejenis yang fokus dalam analisis forensik perangkat IoT pada level device. Penelitian yang sudah dilakukan sebelumnya

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Pantilimonescu, Florin, Lucian Constantin Hanganu, Mihaita Peptanariu, et al. "Modular Student Learning Kit for Internet of Things." Applied Mechanics and Materials 659 (October 2014): 601–6. http://dx.doi.org/10.4028/www.scientific.net/amm.659.601.

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The term Internet of Things as a component of Future Internet is a recent fast growing global network infrastructure which extends Internet with a sensors and actuators shield. The paper presents a hands-on learning kit based on an open standard embedded computer connected to Internet enabling live data processing. The system uses cloud programming tools to add significant value to the education purpose, by including up-to-date innovative technical approaches and pedagogical values for improving the attractiveness and efficiency of the education activities in the engineering area. The learning

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Priyadarshini, Rojalina, Rabindra Barik, and Harishchandra Dubey. "DeepFog: Fog Computing-Based Deep Neural Architecture for Prediction of Stress Types, Diabetes and Hypertension Attacks." Computation 6, no. 4 (2018): 62. http://dx.doi.org/10.3390/computation6040062.

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The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is trending. In traditional setups, the cloud backend receives the healthcare data and performs monitoring and prediction for diseases, diagnosis, and wellness prediction. Fog computing (FC) is a distributed computing paradigm that leverages low-power embedded processors in an intermediary node between the client layer and cloud layer. The diagnosis for wellness and fitness monitoring could be transferred to the fog layer from the cloud layer. Such a paradigm leads to a reduction in latency at an increased thr

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Zhou, Xiao Yan, Zhi Hua Hu, and Jian Kun Shun. "Security Architecture of Digital Library Research in General Knowledge Environment." Applied Mechanics and Materials 198-199 (September 2012): 601–5. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.601.

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Ubiquitous service is a bran-new service idea and model of digital library. It emphasizes that the library should be centered on users, provide services at anytime and anywhere, and be embedded into user's work. The ubiquitous service model of digital library is mainly embodied in the mobile library service, the user environment-embedded service, the “cloud computing” -based service and the global network library service. Combined with the relevant application examples, this paper expatiates on and analyzes the basic types, characteristics and application status of digital library ubiquitous s

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Pirahandeh, Mehdi, Shan Ullah, and Deok-Hwan Kim. "A Distributed Edge-Based Scheduling Technique with Low-Latency and High-Bandwidth for Existing Driver Profiling Algorithms." Electronics 10, no. 8 (2021): 972. http://dx.doi.org/10.3390/electronics10080972.

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The gradual increase in latency-sensitive, real-time applications for embedded systems encourages users to share sensor data simultaneously. Streamed sensor data have deficient performance. In this paper, we propose a new edge-based scheduling method with high-bandwidth for decreasing driver-profiling latency. The proposed multi-level memory scheduling method places data in a key-value storage, flushes sensor data when the edge memory is full, and reduces the number of I/O operations, network latency, and the number of REST API calls in the edge cloud. As a result, the proposed method provides

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Zhou, Kai, Yan Xie, Zhan Gao, Fang Miao, and Lei Zhang. "FuNet: A Novel Road Extraction Network with Fusion of Location Data and Remote Sensing Imagery." ISPRS International Journal of Geo-Information 10, no. 1 (2021): 39. http://dx.doi.org/10.3390/ijgi10010039.

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Road semantic segmentation is unique and difficult. Road extraction from remote sensing imagery often produce fragmented road segments leading to road network disconnection due to the occlusion of trees, buildings, shadows, cloud, etc. In this paper, we propose a novel fusion network (FuNet) with fusion of remote sensing imagery and location data, which plays an important role of location data in road connectivity reasoning. A universal iteration reinforcement (IteR) module is embedded into FuNet to enhance the ability of network learning. We designed the IteR formula to repeatedly integrate o

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