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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 37, Number 7(4) (2025)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 3191-3205
S&M4112 Technical paper of Special Issue https://doi.org/10.18494/SAM5580 Published: July 31, 2025 Big Data and Novel Sensors to Enhance Effectiveness of Monetary Policy in Internet of Things Era [PDF] Xin Zhang, Sha Yang, Changping Lu, and Fengchang Fei (Received January 27, 2025; Accepted June 20, 2025) Keywords: monetary policy, big data, sensor technologies, economic growth
Sensor technologies with big data analytics provide effective solutions to monetary policy. When deriving the economic parameter indexes from historical data, policymaking cannot effectively respond to current economic situations. Therefore, near real-time transactional data is required for the prediction of energy consumption, consumer behavior, and economic parameters. By using sensor technology, data leakage, technical discrepancies, and restricted expansiveness in the prediction can be addressed. By using encryption protocols, the reliability of present and predicted data can be used for industrial development and allows for the efficiency of real-time analysis of the data. Effective decisions can also be made on economic policies to enhance economic stability in the complicated global economy.
Corresponding author: Xin Zhang  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Xin Zhang, Sha Yang, Changping Lu, and Fengchang Fei, Big Data and Novel Sensors to Enhance Effectiveness of Monetary Policy in Internet of Things Era, Sens. Mater., Vol. 37, No. 7, 2025, p. 3191-3205. |
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Special Issue on Novel Sensors, Materials, and Related Technologies on Artificial Intelligence of Things Applications
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
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Special Issue on Unique Physical Behavior at the Nano to Atomic Scales
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Special Issue on Innovations in Multimodal Sensing for Intelligent Devices, Systems, and Applications
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Special Issue on Advanced Materials and Technologies for Sensor and Artificial- Intelligence-of-Things Applications (Selected Papers from ICASI 2025)
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- Flood Susceptibility Mapping Using Machine Learning Models with Novel Flood Inventory Sampling Strategies
Gen Long, Sarintip Tantanee, Korakod Nusit, and Pitikhate Sooraksad
- Flood Susceptibility Mapping Using Machine Learning Models with Novel Flood Inventory Sampling Strategies
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Special Issue on Materials, Devices, Circuits, and Analytical Methods for Various Sensors (Selected Papers from ICSEVEN 2025)
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Mu-Chun Wang (Minghsin University of Science and Technology), Shih-Hung Lin (Chung Shan Medical University), Ja-Hao Chen (Feng Chia University)
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Special Issue on Sensing and Data Analysis Technologies for Living Environment, Health Care, Production Management, and Engineering/Science Education Applications (2025)
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Special Issue on Sustainable Sensor Materials, Processes, and Applications
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