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A Problem of Detecting Stops While Tracking Moving Objects Under the Stream Processing Regime

Białoń Paweł M.

Journal of Telecommunications and Information Technology

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2023

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nr 4

123—132

EN

The tracking of moving objects with the use of GPS/GNSS or other techniques is relied upon in numerous applications, from health monitoring and physical activity support, to social investigations to detection of fraud in transportation. While monitoring movement, a common subtask consists in determining the object’s moving periods, and its immobility periods. In this paper, we isolate the mathematical problem of automatic detection of a stop of tracking objects under the stream processing regime (ideal data processing algorithm regime) in which one is allowed to use only a constant amount of memory, while the stream of GNSS positions of the tracked object increases in size. We propose an approximation scheme of the stop detection problem based on the fuzziness in the approximation of noise level related to the position reported by GNSS. We provide a solving algorithm that determines some upper bounds for the problem’s complexity. We also provide an experimental illustration of the problem at hand.

2

A preliminary feasibility study of a short-term prognosis of mining towers tops' displacements with the use of artificial neural networks

Dudzik M., Łątka D., Repelewicz M., Stewarski E., Stręk A. M.

Czasopismo Techniczne. Budownictwo

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2014

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R. 111, z. 5-B

59--64

EN

Mining industry is a key sector of many national economies, thus even a small crack in a mining site echoes nationwide. This strategic sector is subjected to special safety care in every aspect, including operational safety of engineering structures. The newest technologies are employed to diagnose and monitor the working structures and buildings. In this article we propose an innovative idea of combining GPS monitoring system with artificial neural network prognosing to build a prediction tool for displacement of mining shafts in operational conditions. The paper describes a training of a neural network system whose task is to prognose the displacements of the top of a mine shaft tower in direction in a selected period of time. The data used for the training come from the GPS monitoring of displacements of the top of the S 1.2 mining shaft tower. The tower is located in the mining works LW "Bogdanka".

PL

Przemysł wydobywczy jest kluczowym sektorem wielu gospodarek narodowych, w związku z tym nawet najmniejsza usterka w obrębie kopalni zawsze odbija się echem w całym kraju. Ten strategiczny sektor jest więc poddany szczególnej trosce o bezpieczeństwo, w każdym aspekcie, włączając bezpieczeństwo eksploatacji konstrukcji inżynierskich. Najnowsze technologie są używane do badania i monitorowania pracujących obiektów i budowli. W tym artykule proponujemy nowatorski pomysł połączenia monitoringu GPS z prognozowaniem za pomocą sztucznych sieci neuronowych w celu zbudowania narzędzia prognozowania przemieszczenia szybów kopalni w warunkach eksploatacyjnych. Artykuł prezentuje trening sztucznej sieci neuronowej, której zadaniem jest prognozowanie przemieszczenia szczytu wieży szybu kopalnianego dla jednego kierunku w wybranym okresie czasu. Analizowane w artykule wyniki pomiarów pochodzą z monitoringu przemieszczeniowego szczytu wieży szybu S 1.2 w kopalni LW "Bogdanka". Uzyskane wyniki obliczeń dla wybranego fragmentu okresu letniego prezentują się obiecująco.

3

Position accuracy evaluation of the modernized Polish DGPS

Dziewicki M., Szpecht C.

Polish Maritime Research

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2009

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nr 4

57-61

EN

Polish Maritime DGPS system has been modernized to meet the requirements set out in IMO resolution for a future GNSS, but also to preserve backward signal compatibility of user equipment. Having finalized installation of the new technology L1, L2 reference equipment performance tests were performed. This paper presents results of the long-term signal measuring campaign of the DGPS reference station Rozewie, which was performed in July 2009. Final results allowed to verify repeatable and absolute accuracy of the system after the modernization. Obtained statistics were compared to past measurements performed in 2005 when previous system infrastructure was in operation.