Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5429
Author(s):  
Jianwen Guo ◽  
Minghu Zhang ◽  
Qingsheng Shang ◽  
Feng Liu ◽  
Adan Wu ◽  
...  

River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB.


1954 ◽  
Vol 73 (7) ◽  
pp. 647-647
Author(s):  
G. W. Johnson ◽  
D. P. Lindorff

Author(s):  
Mitsuo Hirata ◽  
Akiyo Murase ◽  
Takenori Atsumi ◽  
Kenzo Nonami

Abstract It has been proposed the design method of the two-degree-of-freedom (TDOF) controller which use the dynamical model of the feedback controller. In this study, we apply this design method to the sampled-data control system. The TDOF controller is obtained so that the output of the TDOF system follows the output of the model transfer function considering the intersample behaviors.


Author(s):  
Meghna Sharma ◽  
Niharika Garg

This chapter provides the relation between automated inventory control and generation of big data using the process. Conversion from manual to automated inventory process leads to generation and management of too much data. Possible boons and banes of the conversion of inventory control system to automated one are discussed in detail. In the initial sections explanation about inventory control and benefits of automating is given. Then overall architecture of big data and its management is discussed .Finally, tradeoff between the usage of automated inventory control system with its benefits and generation of too much data and handling it, is discussed.


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