CONCEPT OF A FOREST PLOT DIGITAL TWIN: FROM IoT DATA COLLECTION TO COGNITIVE MODELS FOR RESOURCE MANAGEMENT

E. A. Golova; V. Antsiferova; A. A. Mazurov; A. S. Yagodkin

doi:doi:10.58168/MIST2026_762-770

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CONCEPT OF A FOREST PLOT DIGITAL TWIN: FROM IoT DATA COLLECTION TO COGNITIVE MODELS FOR RESOURCE MANAGEMENT

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CONCEPT OF A FOREST PLOT DIGITAL TWIN: FROM IOT DATA COLLECTION TO COGNITIVE MODELS FOR RESOURCE MANAGEMENT

Section: SECTION 2. COMPUTER-AIDED DESIGN SYSTEMS

Proceedings: MODELING INFORMATION SYSTEMS AND TECHNOLOGIES – 2026 : PROCEEDINGS OF THE INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE DEDICATED TO THE 5TH ANNIVERSARY OF THE FACULTY OF COMPUTER SCIENCE AND TECHNOLOGY, VORONEZH, MARTH 30, 2026

UDC 004.9

E. A. Golova ¹

V. Antsiferova ²

A. A. Mazurov ³

A. S. Yagodkin ⁴

Author and publication information

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

3. Voronezh State University of Forestry and Technologies named after G.F. Morozov

4. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

Type:

Сonference article

DOI:

https://doi.org/10.58168/MIST2026_762-770

Pages:

from 762 to 770

Published:

30.06.2026

Subject area:

UDC 004.9

Language:

Russian

Keywords:

digital twin, forestry, Internet of Things (IoT), cognitive models, artificial intelligence, predictive analytics, sustainable resource management

Abstract and keywords

Abstract:
This paper presents an approach to constructing a digital twin of a forest plot within a unified “data–model–decision” cycle. We describe how to organize the transition from distributed data collection (IoT sensors, remote sensing) to models that represent the state of the forest ecosystem and can be used in practice. The proposed system architecture represents the current state of the object and enables forecasting of its dynamics, supporting management decisions aimed at resource conservation and risk reduction.

Keywords:
digital twin, forestry, Internet of Things (IoT), cognitive models, artificial intelligence, predictive analytics, sustainable resource management

References

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