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Shepard Erik2Every ten years or so, we achieve a technological breakthrough that drives innovation for the next decade. We are coming out of the age of emergence of the Internet, which has seen this enabling technology move from novel to ubiquitous. By 2010, cell phones and smart phones were on the path to becoming standard, with nearly always-connected Internet capabilities. Suddenly, we have the wealth of information at our fingertips, from maps to phone books, from web browsers to media players. And we’re not only consuming information with our smart devices, we’re generating information at amazing rates.

Every ten years or so, we achieve a technological breakthrough that drives innovation for the next decade. We are coming out of the age of emergence of the Internet, which has seen this enabling technology move from novel to ubiquitous. By 2010, cell phones and smart phones were on the path to becoming standard, with nearly always-connected Internet capabilities. Suddenly, we have the wealth of information at our fingertips, from maps to phone books, from web browsers to media players. And we’re not only consuming information with our smart devices, we’re generating information at amazing rates.

Which leads us to the next age, one into which we are now entering.

Sensors Everywhere

Smart phones are but one example of sensors in the environment, rich with opportunities. Across sectors, sensors are finding their way from novel or niche technologies to standard, even necessary components.

Smart meters are helping utilities move from a monthly read of consumption to a near real-time consumption profile that looks at usage and load patterns throughout times of day. Intelligent electric devices (IEDs, the good kind) help power utilities balance reliability and efficiency by gathering information on power quality throughout the network.

RFID tags aid in manufacturing and logistics, helping suppliers and shippers track merchandise throughout the supply chain. Traffic sensors monitor traffic flows for planning purposes, and infrastructure investment decisions. Military missions rely on airborne and spaceborne sensors to detect troop movements and to counteract threats.

Geoanalytics

In the 19th century, the United States experienced several mining booms – particularly the Gold Rush movements in California and Alaska. In the 21st century, we are experiencing a new kind of mining boom – a data mining boom. Data mining has been an emerging technology, along with data warehouses, for the past two decades. But we have wanted for the rich strata of data to mine, even as we developed the techniques.

Today we have so much data that it has become a problem. We’ve even given the problem a name: the “big data” problem. Big data refers to single datasets that are terabytes, even petabytes in size, and are characterized by the “three V’s”: volume, velocity and variety. Sensors are one of the biggest contributors of big data datasets.

The age we are now entering – or perhaps in which we are now firmly entrenched – is the sensor age. An age of generating massive datasets, with rich content gathered in real-time about a variety of information. Challenges abound, but opportunities abound as well.

This age is one that will showcase geospatial professionals. Sensor data is inherently locational. Consumers with cellphones are constantly on the move, with shifting interests and priorities. The usage of their phones reflects their wants, correlated with their place in space. Smart meters and IEDs have a place in space, as well as a place in their connected network topologies. Airborne and spaceborne platforms generate remotely sensed imagery that is georeferenced. RFID tags generate location of manufactured goods.

Geospatial professionals will be at the heart of this new age, because geospatial tools will be the tools that will be brought to bear in addressing the big data problem. Data mining big data datasets in a meaningful way requires that we take into account the locations, topologies and spatial patterns – in essence apply geoanalytics. Homogeneity, heterogeneity and spatial autocorrelation all must be considered for analytical results to accurately reflect reality.

Geovisualization

Geospatial tools have long been central in academia and research for visualization. Opportunities will abound for geospatial professionals trained in geovisualization tools and techniques. Several vendors have developed products in this space. These geovisualization tools allow for the visualization of analytical results against a cartographic backdrop, or conversely allow for the visualization of spatial or temporal patterns.

Another practical problem with a distinctly geospatial solution is the optimal distribution of sensors. The big data problem can be somewhat managed by reducing redundancy of data capture, and identifying overlapping coverage in space and time can facilitate the elimination of that redundancy.

This column will focus quarterly on these issues, and the use of geospatial tools to address these issues. Big data is a challenge for society at large, as well as for computing professionals. Much of the big data being acquired is through the sensors that are becoming so key to the functioning of our society. Sensor data is georeferenced, or at the very least topologically connected to related data sources. With the problem, comes a solution.

As we move into this new age in the early 21st century, the age of sensors, it is apparent that with vast sensors, we acquire big data – with all its promise and problems. But for geospatial professionals, with big data we have big opportunities to shine as the experts that can make sense of it all.

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