Adaptive Scientific Visualization Tools for a Smart Paleontological Museum

Ryabinin, Konstantin; Kolesnik, Mariia

doi:10.1134/s0361768819040066

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…It is also an indispensable part of smart city for providing a platform for culture, education, and propaganda to build a contemporary public cultural service system. The main areas of museum intellectualisation are artificial intelligence digital exhibition and visitor interaction [1,[4][5][6], preventive conservation of cultural relics based on immerging high-techs [7,8], integrated management of exhibition rooms [9], and intelligent visitors service [10][11][12]. Among them, the preventive conservation of cultural relics is a major concern to all museums.…”

Section: Introductionmentioning

confidence: 99%

Energy balanced routing protocol based on improved particle swarm optimisation and ant colony algorithm for museum environmental monitoring of cultural relics

2023

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The environmental monitoring of cultural relics based on wireless sensor networks in museums demands for the transmission and processing of massive data, which in turn leads to problems, such as heavy network traffic, high time delay, and unbalanced node energy consumption. To solve these problems, an energy balanced routing protocol which can minimise the network energy consumption is proposed. The improved swarm intelligence optimisation algorithm which combined particle swarm optimisation with ant colony optimisation is adopted to construct an environmental monitoring system for cultural relics preservation. Simulation results show that the decrease of the path length for data transmission under the proposed algorithm is 2.5% higher than that of other classical algorithms, indicating that the proposed algorithm can effectively reduce the length of network path and improve the transmission performance of network system. In view of optimisation rounds and simulation time, the energy consumption of the network system under our algorithm is 57.5% less compared with other classical algorithms, and the average residual energy variance is 57.1% less. The cultural relics environmental monitoring system based on the proposed routing protocol has better network load balancing performance.

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Section: Introductionmentioning

confidence: 99%

Energy balanced routing protocol based on improved particle swarm optimisation and ant colony algorithm for museum environmental monitoring of cultural relics

2023

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“…Knowledge base level. This level is available for the SciVi administrators who can change the underlying ontologies to build so-called workbenches: sets of available microservices suitable for solving problems of a particular class (for example, problems related to DH [21], Smart Museum [24], Internet of Things [25], Human-Computer Interaction [26], etc.). 4.…”

Section: Introductionmentioning

confidence: 99%

Automatic Areas of Interest Detector for Mobile Eye Trackers

Ryabinin

Alexeeva

Petrova

2022

Proceedings of the 32nd International Conference on Computer Graphics and Vision

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Thе paper deals with automatic areas of interest detection in video streams derived from mobile eye trackers. Defining such areas on a visual stimulus viewed by an informant is an important step in setting up any eye-tracking-based experiment. If the informant’s field of view is stationary, areas of interest can be selected manually, but when we use mobile eye trackers, the field of view is usually constantly changing, so automation is badly needed. We propose using computer vision algorithms to automatically locate the given 2D stimulus template in a video stream and construct the homography transform that can map the undistorted stimulus template to the video frame coordinate system. In parallel to this, the segmentation of a stimulus template into the areas of interest is performed, and the areas of interest are mapped to the video frame. The considered stimuli are texts typed in specific fonts and the interest areas are individual words in these texts. Optical character recognition leveraged by the Tesseract engine is used for segmentation. The text location relies on a combination of Scale-Invariant Feature Transform and Fast Library for Approximate Nearest Neighbors. The homography is constructed using Random Sample Consensus. All the algorithms are implemented based on the OpenCV library as microservices within the SciVi ontology-driven platform that provides high-level tools to compose pipelines using a data-flow-based visual programming paradigm. The proposed pipeline was tested on real eye tracking data and proved to be efficient and robust.

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“…e scientific visualization support in the generated software is based on hardware graphics acceleration through OpenGL ESAPI [11]. Based on the SciVi adaptive multiplatform scientific visualization system, Kolesnik and Ryabinin are committed to developing tools that allow museum staff to use the Internet of ings (IoT) technology to create interactive exhibits and propose a unified software and hardware solution to enable users without in-depth electronics and programming knowledge; various devices can be assembled and interconnected through the principle of construction set [12].…”

Section: Introductionmentioning

confidence: 99%

Digital Design of Smart Museum Based on Artificial Intelligence

Wang

2021

Mobile Information Systems

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Today, as the soft power of culture is becoming more and more important, it is very important to pay attention to the learning and dissemination of culture. As the carrier of this process, the use of advanced technology to improve the museum is of great significance. This paper studies the digital design of smart museum based on artificial intelligence in order to explore the application of smart museum in artificial intelligence, analyze the spatial design of smart museum by using digital technology, explore a feasible method to give full play to the function of smart museum, and put forward some suggestions on the spatial design of smart museum. The design of the smart museum is no longer restricted by time and space and uses digital technology to double use virtual things and dynamic space. Through the detailed analysis of the application of artificial intelligence and digitization in the spatial design of the smart museum, combined with the information decision tree algorithm and data heterogeneous network algorithm, this study constructs the model of the information processing architecture of smart museum and the requirements of digital museum and makes a decision-making analysis of the comparison results of existing data. It includes the digital design of smart museum display technology, display effect, and other display-related contents. Analyzing the impact of smart museum on the object can provide data support for the feasibility of digital space design of smart museum based on artificial intelligence. The results of regression data processing show that the spatial visual sense of digital design wisdom museum is very strong, reaching the level of 5.0, and the picture aesthetic effect is up to 4.8.

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Adaptive Scientific Visualization Tools for a Smart Paleontological Museum

Cited by 7 publications

References 8 publications

Energy balanced routing protocol based on improved particle swarm optimisation and ant colony algorithm for museum environmental monitoring of cultural relics

Energy balanced routing protocol based on improved particle swarm optimisation and ant colony algorithm for museum environmental monitoring of cultural relics

Automatic Areas of Interest Detector for Mobile Eye Trackers

Digital Design of Smart Museum Based on Artificial Intelligence

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