Filtering strategies for smartphone emitted digital signals

• Autorzy: Obretin Alexandru Marius , Cornea Andreea-Alina

Identyfikatory

DOI

10.35784/acs-2024-09

• Języki publikacji: EN

Abstrakty

EN

In today's digitalized and technology-driven society, where the number of IoT devices and the volume of collected data is exponentially increasing, the use of sensor data has become a necessity in certain fields of activity. This paper presents a concise history of sensor evolution and specialization, with a focus on the sensors used for localization, particularly those present in microelectromechanical systems (MEMS) that make up inertial measurement units. The study starts with a general overview and progresses towards a more specific analysis of data sets collected from an accelerometer. In the materials and methods section, it emphasizes the imperfect nature of sensor measurements and the need to filter digital signals. Three different digital signal filtering techniques belonging to distinct filter categories are comparatively analyzed, with each technique having its own particularities, advantages and disadvantages. The analysis considers the effectiveness in reducing measurement errors, the impact of the filtering process on the original signal, the ability to highlight the underlying phenomenon, as well as the performance of the analyzed algorithms. The ultimate purpose of this article is to determine which filtration method is best suited for the signal at hand in the context of an indoor localization application.

Słowa kluczowe

EN

signal processing; digital filters; sensors; technology

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2024
• Tom: Vol. 20, no 1
• Strony: 139--156
• Opis fizyczny: Bibliogr. 52 poz., fig., tab.

Twórcy

autor

Obretin Alexandru Marius

• Bucharest University of Economic Studies, Faculty of Cybernetics, Statistics and Economic Informatics, Department of Economic Informatics, Romania

• https://orcid.org/0009-0001-0952-9109

autor

Cornea Andreea-Alina

• Bucharest University of Economic Studies, Faculty of Cybernetics, Statistics and Economic Informatics, Department of Economic Informatics, Romania

• https://orcid.org/0009-0004-4373-3949

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