{"id":39409,"date":"2026-07-30T13:20:53","date_gmt":"2026-07-30T11:20:53","guid":{"rendered":"https:\/\/www.risc-software.at\/referenzprojekte\/viseba-virtual-sensors-through-sensor-fusion-in-mining\/"},"modified":"2026-10-28T10:54:15","modified_gmt":"2026-10-28T09:54:15","slug":"viseba-virtual-sensors-through-sensor-fusion-in-mining","status":"publish","type":"project","link":"https:\/\/www.risc-software.at\/en\/referenceprojects\/viseba-virtual-sensors-through-sensor-fusion-in-mining\/","title":{"rendered":"ViSeBa: Virtual Sensors Through Sensor Fusion in Mining"},"content":{"rendered":"\n
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As part of the ViSeBa research project, RISC Software GmbH, together with its partners, is researching and validating AI-supported sensor fusion in salt mining to improve measurement accuracy and safety.<\/p>\n<\/div>\n\n\n\n

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\"Mining<\/figure>\n<\/div>\n<\/div>\n\n

AI-Powered Sensor Fusion in Salt Mining<\/h3>\n\n

In ViSeBa, Salinen Austria AG, iba Austria GmbH, and RISC Software GmbH are collaborating to research and validate AI-supported sensor fusion in brine mining. The goal is to develop a generic, component-based research framework that can be flexibly adapted to various use cases. Within this framework, data from different sensors is combined (multimodal sensor fusion of images, time series, sound, and more) to reliably detect inaccuracies and anomalies. In doing so, the latest findings from fundamental AI research are applied to the mining sector, and the methods are adapted and expanded. Two main areas of focus are being pursued for validation. <\/p>\n\n

Improving Measurement Accuracy<\/h3>\n\n

Accurate measurements are crucial, as they form the basis for precise process control in mining. One problem is the contamination of sensors and piping by deposits, which causes measurement drift and thus leads to incorrect data, impairing the efficiency of production processes. Sensor fusion is intended to correct sensor drift and maintain high measurement accuracy over an extended period of time. <\/p>\n\n

Detection of Changes<\/h3>\n\n

The second focus area deals with the detection of changes. The goal is to identify even the smallest deviations in mining structures or the pipeline network at an early stage. This allows potential hazards to facilities and personnel to be identified and minimized in a timely manner. <\/p>\n\n

Expected Benefits<\/h3>\n\n

It is expected that measurement errors will be reduced by 60 percent and the effort required for manual inspections will be cut by 30 percent. With this comprehensive approach, ViSeBa offers an innovative solution that makes brine mining more efficient, safer, and more reliable, thereby making a significant contribution to securing mining sites and ensuring job stability in the Austrian and European mining industries. <\/p>\n\n

The project is funded by the Austrian Research Promotion Agency (FFG) as part of the “Raw Materials 2024” call for proposals.<\/p>\n\n

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Project partners<\/h2>\n\n\n
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Project details<\/h2>\n\n\n\n