Energy big data acquisition and application based on service portfolio quality

In India, the agriculture sector has an adverse effect and day by day the crop production is getting reduced. So, it is important to identify and implement a solution for the problem in order to increase the production. Smart technologies are introduced in this domain to improve the agriculture industry. The technologies like IoT, big data, cloud-based services, and GPS are gaining its importance in the field of agriculture. There is a rising need due to the requirement of higher precision in crop analysis, transformation of live data from the field and automated farming techniques for further improvement. The expected result of this is to have smart agriculture industry with the implementation of these smart techniques. In this chapter, the authors have discussed the challenges and benefits of IoT and various types of sensor for data acquisition.

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Research on Data Acquisition and Sharing Methods Under Power Demand Side Management Based on Big Data Mining Analysis

Journal of Physics Conference Series ◽

10.1088/1742-6596/1992/3/032133 ◽

2021 ◽

Vol 1992 (3) ◽

pp. 032133

Author(s):

Zhaoguang Yang ◽

Mingjun Jiang ◽

Linxin Wang ◽

Xiaolong Wang ◽

Juan Shao

Keyword(s):

Data Mining ◽

Big Data ◽

Data Acquisition ◽

Demand Side Management ◽

Power Demand ◽

Demand Side ◽

Big Data Mining ◽

Data Mining Analysis

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BIG DATA APPLIED TO CYBER-PHYSICAL LOGISTIC SYSTEMS: CONCEPTUAL MODEL AND PERSPECTIVES

Brazilian Journal of Operations & Production Management ◽

10.14488/bjopm.2015.v12.n2.a12 ◽

2015 ◽

Vol 12 (2) ◽

pp. 330 ◽

Cited By ~ 3

Author(s):

Enzo Morosini Frazzon ◽

Moisés Lima Dutra ◽

William Barbosa Vianna

Keyword(s):

Big Data ◽

Supply Chain ◽

Data Acquisition ◽

Supply Chains ◽

Conceptual Model ◽

Critical Issue ◽

Research Management ◽

Conceptual Approach ◽

Flow Of Information ◽

Innovative Techniques

<p>The management of supply chains and their subsystems embodies strategic and contemporaneous challenges. The competitiveness of supply chains depends increasingly on their flexibility. Logistics as a supply chain function has to compensate increasing requirements regarding flexibility by means of a higher information density and the employment of innovative techniques for data acquisition and analytics. Indeed, the flow of information that commands the physical flow embodies a critical issue for the management of supply chains. Hence, by means of a theoretical and conceptual approach, this paper aims to propose to research management perspectives and propose a model for the application of innovative techniques for data acquisition and analytics in Cyber-Physical Logistic Systems.</p>

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Automatic Big Data Acquisition of Electrical Parameters in Wide Bandgap Devices

2019 IEEE 7th Workshop on Wide Bandgap Power Devices and Applications (WiPDA) ◽

10.1109/wipda46397.2019.8998833 ◽

2019 ◽

Author(s):

Chengkun Liu ◽

Ze Ni ◽

Mengxuan Wei ◽

Aaron Niehaus ◽

Dong Cao

Keyword(s):

Big Data ◽

Data Acquisition ◽

Wide Bandgap ◽

Electrical Parameters

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Data Acquisition and Mining Algorithm of Car Networking under Big Data Background

International Journal of Online and Biomedical Engineering (iJOE) ◽

10.3991/ijoe.v15i01.9772 ◽

2019 ◽

Vol 15 (01) ◽

pp. 4

Author(s):

Guohua Xiong

Keyword(s):

Big Data ◽

Data Acquisition ◽

Road Traffic ◽

Traffic Information ◽

Traffic Conditions ◽

Real Time Traffic ◽

Mining Algorithm ◽

Mining Algorithms ◽

Traffic Information Collection ◽

Networking Technology

In order to solve the problem of traffic jams, intelligent traffic technology and car networking technology were applied. In the context of big data, data acquisition and mining algorithms for vehicular network were studied. First, the overall architecture of the system was introduced. Then, the data acquisition technology based on the car network and the data mining technology based on the cloud plat-form were introduced. Finally, simulation experiments of real-time traffic information collection and recognition algorithms were performed. The results showed that the proposed mining algorithm had better data repair effect and better clustering effect, and the probability of misjudgment was smaller. Therefore, the algorithm can obtain accurate road traffic conditions.

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