DOI: 10.17587/prin.17.475-485

Distributed Architecture for Multilevel Sensor Data Processing in Intellectual Environment

O. Yu. Bogoiavlenskaia, Cand. Sc. (Eng.), Associate Professor, olbgvl@cs.petrsu.ru, Petrozavodsk State University, Petrozavodsk, 185910, Russian Federation

Corresponding author: Olga Yu. Bogoiavlenskaia, Cand. Sc. (Eng.), Associate Professor, Petrozavodsk State University, Petrozavodsk, 185910, Russian Federation, E-mail: olbgvl@cs.karelia.ru

Substantial volume of sensed data available and high complexity of data analysis methods create a need for increasing the effectiveness of monitoring and data selection for real-time application with the aim for deploying the high-complexity algorithms on distributed platforms with mobile components and autonomous power supply. The paper describes a distributed architecture for multi-level processing of these raw data, based on the presentation of the intellectual environment as a set of states. The algorithms have been developed as well to reduce the load on hardware and network infrastructure and to improve the accuracy of data classification through contextual correction of intellectual classification results.

Keywords: sensor, data analysis, holistic approach, architecture, delay, algorithm, context-aware method

pp. 475—485

For citation:
Bogoiavlenskaia O. Yu. Distributed Architecture for Multilevel Sensor Data Processing in Intellectual Environment, Programmnaya Ingeneria, 2026, vol. 17, no. 9, pp. 475—485. DOI: 10.17587/prin.17.475-485 (in Russian).

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