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Conflation of datasets into higher quality Digital Evelation Models, at low cost

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOSI20200114001
Publicado:
21/01/2020
Caducidad:
21/01/2021
Resumen:
Slovenian researchers have developed an intelligently conflated Digital Elevation Model (DEM). Instead of a single data source, the algorithm uses a multi-data approach. In this way, elevation models of unprecedented quality can be created. The associated cost saving (factor 25!) gives the tool another decisive competitive advantage. Industrial partners in topography are sought for licensing and commercial agreements, with technical assistance.

Details

Tittle:
Conflation of datasets into higher quality Digital Evelation Models, at low cost
Summary:
Slovenian researchers have developed an intelligently conflated Digital Elevation Model (DEM). Instead of a single data source, the algorithm uses a multi-data approach. In this way, elevation models of unprecedented quality can be created. The associated cost saving (factor 25!) gives the tool another decisive competitive advantage. Industrial partners in topography are sought for licensing and commercial agreements, with technical assistance.
Description:
The client is higher education and scientific research institution founded in 1919. The client has close ties with Slovenian companies and foreign enterprises. Their partners include multinational corporations and the most successful Slovenian companies. As they are fully aware of the importance of knowledge and skills in obtaining they own financial sources, they are increasingly developing their market oriented activities every year. Researchers developed an algorithm to combine reliable positional, semantical and geomorphic properties of various data to the conflated Digital Elevation model (DEM).

Background
Imagine a Digital Elevation Model (DEM) as a soft foil hugging every aspect of the terrain that can coat all objects upon it. The data used to create these models usually comes from a large single source. The fact is that, since the millennium, the quantity of data has increased at an enormous rate, but the quality has not increased by the same degree. The motivation was the use of data from multiple sources. This goes beyond the typical research issues and the capacity of commonly used software.

Description of the Invention
A working prototype for spatial data conflation ensures better results when compared to even the best single source. An algorithm to combine reliable positional, semantical and geomorphic properties of various data to the conflated DEM has been developed. The invention is well-timed, due to recent advances in spatial data analytics and quality control, and my solutions for the national conflated DEM.

The research institution is looking for an industrial partner, active on the fields of intelligent vehicle navigation, intelligent communications, transport and storage utilities; positioning (LBS); renewable energy, water supply, communications (network planning); local, regional, national and global elevation data frame, maps, planning; climate change management; disaster/hazard management, flood risk management, insurance and prediction; natural resources conservation; agriculture, precision farming, forestry, fisheries; mining; defence and national security; maritime and aviation safety; computer forensics, security; planning space missions; tourism, health and ageing; landscape archaeology; virtual reality; applications in natural, environmental, social sciences; SMART (digital territories, cities, governance, mass appraisal, people, living, mobility, navigation, economy, environment, climate change management).
Advantages and Innovations:
The traditional solutions offer tools for processing data from single-data sources, while their invention provokes a paradigm shift towards multi-data and methods, ensuring better quality DEM through conflation/fusion. Effectiveness: up to 25-times reduced cost of the final products. The solution is highly compatible with the Zero Waste philosophy, which encourages the redesign of resource life cycles so that the existing data is reused and the big data is reduced and cleansed. The difference between the single and proposed multiple data sets approaches could make a difference in savings of multimillion -Y-euro; in Flood-risk management, Natural disaster management, a difference to soil management, erosion strategies, etc. They can offer a proven concept and solution that could make a difference among key players in the industry.
Stage of Development:
Available for demonstration
IPs:
Secret Know-how,Copyright

Partner sought

Type and Role of Partner Sought:
Founder or a long-term strategic investor that have experiences in the fields intelligent vehicle navigation, intelligent communications, transport and storage utilities; positioning (LBS); renewable energy, water supply, communications (network planning); local, regional, national and global elevation data frame, maps, planning; climate change management; disaster/hazard management, flood risk management, insurance and prediction; natural resources conservation; agriculture, precision farming, forestry, fisheries; mining; defence and national security; maritime and aviation safety; computer forensics, security; planning space missions; tourism, health and ageing; landscape archaeology; virtual reality; applications in natural, environmental, social sciences; SMART (digital territories, cities, governance, mass appraisal, people, living, mobility, navigation, economy, environment, climate change management).

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English

Keywords

Technology Keywords:
01004003 Applications for Transport and Logistics
01004006 Environment Management Systems
01004007 GIS Geographical Information Systems
01001002 Sistemas digitales, representación digital
01005006 Visualización, realidad virtual