scholarly journals The Internet of Energy: Smart Sensor Networks and Big Data Management for Smart Grid

2015 ◽  
Vol 56 ◽  
pp. 592-597 ◽  
Author(s):  
Manar Jaradat ◽  
Moath Jarrah ◽  
Abdelkader Bousselham ◽  
Yaser Jararweh ◽  
Mahmoud Al-Ayyoub
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 ◽  
Vol 13 (23) ◽  
pp. 13322
Author(s):  
Vinoth Kumar Ponnusamy ◽  
Padmanathan Kasinathan ◽  
Rajvikram Madurai Elavarasan ◽  
Vinoth Ramanathan ◽  
Ranjith Kumar Anandan ◽  
...  

The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the end- users, and enhances the user experience by monitoring and controlling the energy transmission. The smart grid deals with an enormous amount of energy data, and the absence of proper techniques for data collection, processing, monitoring and decision-making ultimately makes the system ineffective. Big data analytics, in association with the smart grid, enable better grid visualization and contribute toward the attainment of sustainability. The current research work deals with the achievement of sustainability in the smart grid and efficient data management using big data analytics, that has social, economic, technical and political impacts. This study provides clear insights into energy data generated in the grid and the possibilities of energy theft affecting the sustainable future. The paper provides insights about the importance of big data analytics, with their effects on the smart grids’ performance towards the achievement of SDGs. The work highlights efficient real-time energy data management involving artificial intelligence and machine learning for a better future, to short out the effects of the conventional smart grid without big data analytics. Finally, the work discusses the challenges and future directions to improve smart grid technologies with big data analytics in action.


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.  


Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Yuanjun Guo ◽  
Zhile Yang ◽  
Shengzhong Feng ◽  
Jinxing Hu

Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. This paper proposed a modified and optimized structure of the Big Data processing platform according to the power data sources and different structures. Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. To fully investigate the proposed structure, three major applications are introduced: development of power grid topology and parallel computing using CIM files, high-efficiency load-shedding calculation, and power system transmission line tripping analysis using 3D visualization. The real-system cases demonstrate the effectiveness and great potential of the Big Data platform; therefore, data resources can achieve their full potential value for strategies and decision-making for smart grid. The proposed platform can provide a technical solution to the multidisciplinary cooperation of Big Data technology and smart grid monitoring.


Author(s):  
Vellingiri Jayagopal ◽  
Basser K. K.

The internet is creating 2.5 quintillion bytes of data, and according to the statistics, the percentage of data that has been generated from last two years is 90%. This data comes from many industries like climate information, social media sites, digital images and videos, and purchase transactions. This data is big data. Big data is the data that exceeds storage and processing capacity of conventional database systems. Data in today's world (big data) is usually unstructured and qualitative in nature and can be used for various applications like sentiment analysis, increasing business, etc. About 80% of data captured today is unstructured. All this data is also big data.


2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Houda Daki ◽  
Asmaa El Hannani ◽  
Abdelhak Aqqal ◽  
Abdelfattah Haidine ◽  
Aziz Dahbi
Keyword(s):  
Big Data ◽  

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