Big Spatial Data Management for the Internet of Things: A Survey

2020 ◽  
Vol 28 (4) ◽  
pp. 990-1035
Author(s):  
Isam Mashhour Al Jawarneh ◽  
Paolo Bellavista ◽  
Antonio Corradi ◽  
Luca Foschini ◽  
Rebecca Montanari
2020 ◽  
pp. 89-103
Author(s):  
Amrit Sahani ◽  
Ranjit Kumar ◽  
Suchismita Chinara ◽  
Anjali Kumari ◽  
Bina Patro

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Martin Forstner

AbstractThe Internet of things will influence all professional environments, including translation services. Advances in machine learning, supported by accelerating improvements in computer linguistics, have enabled new systems that can learn from their own experience and will have repercussions on the workflow processes of translators or even put their services at risk in the expected digitalized society. Outsourcing has become a common practice and working in the cloud and in the crowd tend to enable translating on a very low-cost level. Confronted with promising new labels like


2021 ◽  
Author(s):  
AISDL

The Internet of Things (IoT) infrastructure forms a gigantic network of interconnected and interacting devices. This infrastructure involves a new generation of service delivery models, more advanced data management and policy schemes, sophisticated data analytics tools, and effective decision making applications. IoT technology brings automation to a new level wherein nodes can communicate and make autonomous decisions in the absence of human interventions. IoT enabled solutions generate and process enormous volumes of heterogeneous data exchanged among billions of nodes. This results in Big Data congestion, data management, storage issues and various inefficiencies. Fog Computing aims at solving the issues with data management as it includes intelligent computational components and storage closer to the data sources.


2018 ◽  
Vol 7 (4.37) ◽  
pp. 86
Author(s):  
Marwah Nihad ◽  
Alaa Hassan ◽  
Nadia Ibrahim

The field internet of things and Big Data has become a necessity in our everyday lives due to the broadening of its technology and the exponential increase in devices, services, and applications that drive different types of data. This survey shows the study of Internet of Things (IoT), Big Data, data management, and intermediate data. The survey discusses intermediate data on Big Data and Internet of Things (IoT) and how it is managed. Internet of Things (IoT) is an essential concept of a new technology generation. It is a vision that allows the embedded devices or sensors to be interconnected over the Internet. The future Internet of Things (IoT) will be greatly presented by the massive quantity of heterogeneous networked embedded devices that generate intensively "Big data". Referring to the term intermediate data as the information that is provoked as output data along the process. However, this data is temporary and is erased as soon as you run a model or a sample tool. Also, the existence of intermediate data in both of the Internet of Things (IoT) and Big Data are explained. Here, various aspects of the internet of things, Big Data, intermediate data and data management will be reviewed. Moreover, the schemes for managing this data and its framework are discussed.  


. A perception that is being enacted by numerous in the world is an ample range of day to day things associated and interfacing with one another across world network economically- "the Internet of Things." The gadgets around us trigger extensive amounts of data and an endless interaction between these electronic appliances and the Internet produces useful data for analysis and future prediction. These gadgets are often classified as data sources like sensors, end-user devices like displays, databases and even a knowledge source and sink such as Actuator and Smartphone. Internet of Things (IoT) has promised to facilitate ease and enhanced standard of living for users. Data management for IoT takes part during essential function in its efficient activities and has become a key research theme of IOT. This paper brings the representations of IOT architecture, various techniques for data acquisition, collection, pre-processing and visualization


2019 ◽  
Vol 90 ◽  
pp. 405-422 ◽  
Author(s):  
Edward Curry ◽  
Wassim Derguech ◽  
Souleiman Hasan ◽  
Christos Kouroupetroglou ◽  
Umair ul Hassan

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