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Processing and Analysis of Data from Fiscal Electronic Cash Registers in the Context of IoT and Big Data

Guardado en:
Udgivet i:Studies in Informatics and Control vol. 34, no. 2 (2025), p. 107-117
Hovedforfatter: BARBU, Dragoș-Cătălin
Andre forfattere: BÂRA, Adela, OPREA, Simona-Vasilica
Udgivet:
National Institute for Research and Development in Informatics
Fag:
Big Data
Machine learning
Datasets
Trends
Data mining
Decision making
Tax collections
Data processing
Taxation
Data analysis
Data science
Compliance
Algorithms
Informatics
Research & development > R&D
Business analytics
Deadlines
Tax evasion
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Resumen:This paper proposes a framework for processing and analysing fiscal data from electronic cash registers using Big Data and IoT. The system is designed for handling large volumes of transactional data by integrating data collection, cleaning, transformation, and analysis through a modular architecture based on microservices, distributed messaging, and both relational and NoSQL databases. Before carrying out the data analysis, the missing or inconsistent values are addressed using regression models, which enhances data quality. In order to contribute to anomaly detection in fiscal activities, the proposed platform supports statistical analysis, time series analysis, and pattern recognition. Real-world data-based tests revealed that the proposed technological solution can help the tax authorities track data compliance and increase the effectiveness of fiscal data operations.
ISSN:1220-1766
DOI:10.24846/v34i2y202510
Fuente:Publicly Available Content Database