According to Ria.ru on September 14, scientists from the Moscow University of Geometry and Mapping have proposed a new spatial index method for objects on the surface of the earth, which will increase its productivity by 5-6 times.

2025/03/0121:22:34 science 1506

According to Ria.ru on September 14, scientists from the Moscow University of Geometry and Mapping (MIIGAiK) have proposed a new spatial index method for objects on the surface of the earth, which will increase its productivity by 5-6 times. In their view, the new approach will be applied to environmental monitoring systems, urban management, logistics and any other spatial models of scale and purpose.

index is the cornerstone of all modern databases. Thanks to indexing, it is possible to find the necessary records from millions and billions of records almost immediately. The simplest and most familiar index is the letter index in the book, says Oleg Gvozdev, associate professor in the Department of Information and Measurement Systems, University of Geometry and Mapping of Moscow (MIIGAiK).

According to Ria.ru on September 14, scientists from the Moscow University of Geometry and Mapping have proposed a new spatial index method for objects on the surface of the earth, which will increase its productivity by 5-6 times. - DayDayNews

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According to Oleg Gvozdev, the proposed method is particularly useful in systems such as "smart cities" or "digital twins", where data appears in continuous streams, with the number of requests reaching tens of thousands per second, and has been able to reach millions per second in this decade.

Another potential application area of ​​this development is "data science" and big data analytics, the basis for modern approaches to developing rational management decisions in commercial organizations and public institutions.

The scientist added that any method that releases 5% or even 2% of computing power can allow you to conduct more experiments, analyze more data, and make new discoveries in the future. Furthermore, the proposed method fundamentally extends the tool base of data science experts.

(Compiled by Tu Lihui)

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