New IBM PAIRS Geoscope geospatial information and analytics cloud service can accelerate discovery of insights

IBM Research introduced this week an experimental offering named IBM PAIRS Geoscope (Physical Analytics Integrated Data Repository & Services), a cloud-centric geospatial information and analytics service that can accelerate the discovery of new insights.

Terms like big data, analytics, data science, and the Internet of Things (IoT) have arisen in recent years to help explain a world awash in data. Fueled by increasingly sophisticated and affordable electronics, the exponential growth rates of data created each day is expected to continue unabated for years to come.

Virtually all human activities will be impacted by this age of data, and those who can extract value from this superabundant resource will enjoy a decided advantage.

IBM PAIRS Geoscope arose from a project and engagement a few years ago with the E. & J. Gallo Winery. In an effort to conserve water while improving crop uniformity and yield, IBM and Gallo co-developed a precision irrigation system that incorporated a cloud-based communication network, hundreds of sensors and actuators, satellite imagery to measure the uniformity and health of the greenery, a complex model for estimating water loss from greenery and soil that required numerous meteorological and atmospheric parameters from a variety of sources, and a localized weather model to estimate future irrigation needs.

In addition to demonstrating a new form of a potentially commercial water-efficient drip irrigation technology, a two-season trial of this system on a ten-acre test ranch delivered a 26 percent increase in crop yield, a 50 percent increase in crop uniformity, and a doubling of a key crop quality index, all while using up to 22 percent less water.

The service is built on a highly scalable, cloud-based repository especially crafted for the complexities of geospatial-temporal information. This repository, currently growing by terabytes per day, can automatically ingest, curate, and seamlessly integrate all forms of geospatial-temporal data. Large, heterogeneous, and complex datasets are tamed into a tidy aligned and indexed structure designed for retrieval and query.

Extracting value from the vast and growing stores of geospatial-temporal big data poses a significant challenge. This class of big data, so named because of its inherent link to place and time, includes satellite and aerial imagery, global-scale data and models (weather, climate, oceans, etc.), geo-referenced IoT/sensor networks, and big-event data captured on platforms like Twitter and GDELT.  

Such data is often freely available, but its massive size and the complexities associated with its preparation for use make it difficult to exploit and scale, especially for large areas and time-critical applications.

Clients can now use PAIRS Geoscope at different levels to tap a vast and valuable source of previously underutilized data. As an information service, PAIRS Geoscope can quickly provide a variety of contextual information about a particular place and time. Used as a discovery service, it can identify a set of regions that share a similar set of client-defined characteristics.

As an advanced analytics service, it can leverage machine learning and artificial intelligence techniques to make predictions based on a complex mix of parameters, models, and historical data.

The ongoing development of PAIRS Geoscope remains intentionally tethered to its real-world origins and is currently in trial deployments with clients in the areas of agriculture, finance, energy, and meteorology.

For example, IHI Corporation, a global engineering, construction and manufacturing company that provides a range of products in aero engine, space and defense and other business areas, is working with the service to develop a new system for improving the accuracy of long-term (30 days or more) weather forecasts by more than 30 percent over all other techniques.

Specifically, the team uses data from GPS Radio Occultation sensors on satellites, which can yield three-dimensional temperature, pressure, and humidity profiles of the atmosphere. IHI and its customers use PAIRS Geoscope to blend this data with historical and long-term weather forecast data and machine learning techniques to produce improved weather forecast insights.

An interactive web interface for the service allows users to quickly and easily run queries across petabytes of geospatial-temporal data. Results appear as visualizations that can be downloaded in a variety of formats (that in future versions will include SPARK dataframes).

A REST API provides developers with a unified cloud-based interface to interact with the technology, thus allowing them to enhance their applications without replacing or disrupting their preferred set of mapping, visualization, data acquisition, and control platforms.

The world of digital discovery has been revolutionized by the ability to index and rapidly search web pages, social networks, and business transactions. Geospatial-temporal data, due to its size and complexity, has been resistant to this trend and remains underutilized.

IBM PAIRS Geoscope takes geospatial-temporal data out of the dark and enables clients to capture the value of this growing, ubiquitous, and vitally important class of information in their applications.

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