ORIGINAL PAPER
Automated on-demand inventory of coal dumps and heaps using UAV imagery and IoT-driven data processing
1
KOMAG Institute of Mining Technology, Gliwice
Submission date: 2025-04-30
Final revision date: 2025-06-02
Acceptance date: 2025-07-28
Publication date: 2025-09-26
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2025;41(3):117-143
KEYWORDS
TOPICS
- Scientific background of mineral resource management
- Optimization of resources and reserves management
- Rational and efficient development and utilization of mineral resources
- Effective mineral deposits exploitation
- Preparation and processing of mineral raw materials
- Waste management from extractive industries
- Economics of mineral industries
- Rational use of mineral raw materials
ABSTRACT
The efficient management of coal resources is becoming increasingly important in Poland and Europe, especially during the ongoing energy transition. This paper presents an automated methodology for on-demand inventory of coal dumps and heaps, addressing the limitations of traditional manual surveying techniques. The proposed system integrates Unmanned Aerial Vehicles (UAVs) for rapid spatial data acquisition, IoT sensors for real-time monitoring of environmental parameters, and the QGIS open-source Geographic Information System for data processing and volume calculation. The methodology details the process of generating accurate Digital Elevation Models (DEMs) from UAV imagery using OpenDroneMap software and subsequent volume calculation using a custom algorithm developed within the QGIS Model Designer. This algorithm addresses the challenges of data processing, including the removal of “bad pixels” and geometric correction, to ensure accurate volume estimations. The results demonstrate the potential of the integrated system to provide accurate and timely inventory data, crucial for optimizing coal demand forecasting, production planning, and distribution logistics. This approach offers significant advantages over traditional methods by enhancing safety, reducing labor intensity, and enabling more frequent and precise measurements. The developed solution aligns with the goals of the Polish “Dynamic management of coal demand, production, resource management, and distribution logistics in an economy implementing a decarbonized energy mix” (DynGOSP) project, supporting the modernization of the Polish coal mining sector.
FUNDING
The work was financed by the National Centre for Research and Development under the Strategic Programme for Scientific Research and Development “Social and economic development of Poland in the conditions of globalising markets” GOSPOSTRATEG – competition IX (“Open” projects).
CONFLICT OF INTEREST
The Authors have no conflict of interest to declare.
METADATA IN OTHER LANGUAGES:
Polish
Zautomatyzowany system inwentaryzacji zwałów i hałd węgla, wykorzystujący technologię UAV i przetwarzanie danych oparte na IoT
węgiel, drony, objętość, DynGOSP, zwały
Efektywne zarządzanie zasobami węgla staje się coraz ważniejsze w Polsce i Europie, zwłaszcza w trakcie trwającej transformacji energetycznej. W niniejszym artykule przedstawiono zautomatyzowaną metodologię inwentaryzacji na żądanie składowisk i hałd węgla, rozwiązując ograniczenia tradycyjnych ręcznych technik geodezyjnych. Proponowany system integruje bezzałogowe statki powietrzne (UAV) w celu szybkiego pozyskiwania danych przestrzennych, czujniki IoT do monitorowania parametrów środowiskowych w czasie rzeczywistym oraz system informacji geograficznej QGIS typu open source do przetwarzania danych i obliczania objętości. Metodologia szczegółowo opisuje proces generowania dokładnych modeli wysokościowych (DEM) z obrazów UAV przy użyciu oprogramowania OpenDroneMap i późniejszego obliczania objętości przy użyciu niestandardowego algorytmu opracowanego w QGIS Model Designer. Algorytm ten rozwiązuje problemy związane z przetwarzaniem danych, w tym usuwaniem „złych pikseli” i korektą geometryczną, aby zapewnić dokładne oszacowanie objętości. Wyniki pokazują potencjał zintegrowanego systemu do dostarczania dokładnych i terminowych danych inwentaryzacyjnych, które są kluczowe dla optymalizacji prognozowania zapotrzebowania na węgiel, planowania produkcji i logistyki dystrybucji. To podejście oferuje znaczące zalety w porównaniu z tradycyjnymi metodami, zwiększając bezpieczeństwo, zmniejszając pracochłonność i umożliwiając częstsze i dokładniejsze pomiary. Opracowane rozwiązanie jest zgodne z celami polskiego projektu DynGOSP – „Dynamiczne zarządzanie popytem na węgiel, produkcją, zarządzaniem zasobami i logistyką dystrybucji w gospodarce wdrażającej zdekarbonizowany miks energetyczny”, wspierającego modernizację polskiego sektora górnictwa węglowego.
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