Capturing the value of place and time with geospatial-temporal insights

phys.org | 3/8/2018 | Staff
camkizzle (Posted by) Level 3
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IBM Research is introducing an experimental offering named IBM PAIRS Geoscope (Physical Analytics Integrated Data Repository & Services), a unique 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 quickly extract value from this superabundant resource will enjoy a decided advantage.

Value - Stores - Data - Challenge - Class

Extracting value from the vast and ever-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.

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...
(Excerpt) Read more at: phys.org
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