Geo-Hiker™

Spatio-Temporal Big Data Boosting Engine

As the world is becoming progressively instrumented and interconnected, data is more ubiquitous and richer than ever before. Unbeknownst to many, 80% of all data is spatio-temporal (space-time) – data that has both location and time-series information.

The multi-dimensional nature of spatio-temporal big data itself makes it more complex and more hardware-heavy to aggregate and process than general big data. Thus, specialized technology and functions are required to do spatio-temporal big data processing more efficient.

Wherever spatio-temporal data exists, Geo-Hiker can be applied.

Dtonic’s Core Technology

Geo-Hiker™

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Spatio-Temporal Big Data Boosting Engine

Now, achieving high-efficiency big data processing is easy.

Realize the full potential of your data with Geo-Hiker’s distributed parallel architecture that enables cost-effecting and fast data spatial-temporal data aggregation, storing, indexing, processing and analysis.

No matter what type of data or big data system you are using, Geo-Hiker can help you to achieve faster and cheaper data processing in extreme scale.

Furthermore, Geo-Hiker is the core technology behind all of Dtonic’s solutions.

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Booster for efficient analysis and optimized decision-making

Geo-Hiker is Dtonic's proprietary spatio-temporal big data processing engine, designed to optimize large-scale data operations. It serves as the core technology behind Dtonic's solutions, D.hub and D.EView, powering advanced data-driven decision-making.

Unlike traditional big data processing systems, Geo-Hiker enhances system performance and efficiency by providing specialized technology for handling spatio-temporal data. By integrating Geo-Hiker, Dtonic's solutions enable businesses and organizations to analyze vast amounts of data more quickly and cost-effectively.

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Through 100% Hadoop Eco-System compatibility and support functions of various data stores and visualization tools, existing big data systems can enjoy the benefits of Geo-Hiker’s high-performing spatio-temporal data processing architecture without data or system migration.

High compatibility & scalability

Reduce resource Costs

90%

Increase System Speed

40x

GEO-HIKER USE CASES

While Geo-Hiker itself is not a standalone product, it serves as the engine behind Dtonic's industry-specific solutions, supporting use cases such as:

Nighttime cityscape in Tokyo with tall illuminated skyscrapers and a street with streetlights and parked cars, some emergency vehicle lights visible at the bottom.

Smart City

  • Road Safety Service (Commercial Drivers)

  • Fine-Dust and Pollution Analysis and Prediction Testing

  • Predicted 238B dollar industry by 2022

Aerial view of a rural landscape mixing fields, forests, and a highway with trees and farmland.

Forest/ Agriculture

  • Tourism & Forest Recreation Service Platform

  • AI-based Decision-Making Platform for Field Crops

An aerial view of a city street corner showing parked cars, pedestrians crossing the street, and a building with signs for a sports store and a mobile network provider.

Future Mobility

  • Autonomous Vehicle Communication system analysis

  • Aerospace and airport data enhancements

  • Predicted 620B dollar industry by 2025

A cityscape with high-rise office buildings shrouded in haze, a river in the foreground, and a highway passing through green areas.

Weather/Pollution

  • Air Quality Decision-Making Platform based on weather information

  • Smart Livestock Decision-Making Platform based on weather information

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Healthcare

Inside an automotive manufacturing plant, assembly lines with partially assembled cars, robotic arms, and manufacturing equipment.

Smart Factory

  • 2D/3D Monitoring, Automatic Meter Reading, Digital Twin

  • Energy Reduction, Automation Processing Control

  • Fault & Anomaly Detection

Geo-Hiker FAQs

  • Spatio-temporal big data consists of information that includes both time-series and location data. Examples include tracking vehicle movements, monitoring weather patterns, and analyzing demographic shifts. Due to its multidimensional nature, specialized processing functions are required to handle this data efficiently.

  • Geo-Hiker is built for seamless integration with big data platforms, including Hadoop, Apache Spark, and various cloud-based environments. It enhances existing infrastructures without requiring extensive data migration.

  • By utilizing Dtonic's solutions, businesses can leverage Geo-Hiker’s advanced spatio-temporal data processing to enhance decision-making, optimize operations, and reduce costs.

  • No, Geo-Hiker is not a standalone product for direct purchase. It is the core technology powering Dtonic's solutions, D.hub and D.EView, which leverage Geo-Hiker's capabilities for advanced spatio-temporal data processing.

    However, get in touch with us to discuss how Geo-Hiker could help in your data processing needs!

  • Yes, Geo-Hiker is designed to handle real-time spatio-temporal data streams, enabling businesses to gain immediate insights and make data-driven decisions faster.

  • Geo-Hiker powers solutions across various industries, including smart cities, mobility, healthcare, environmental monitoring, manufacturing, and more. Any organization dealing with large-scale spatio-temporal data can benefit from its capabilities.

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