In Analytics, Use Cases

When I say “water transportation,” your mind might conjure romantic images of the canals of Venice, Italy, with gondolas and vaporettos ferrying locals and tourists down the Grand Canal. Or maybe you’re the cruise ship type.

But did you know that

Commuters, tourists, trade and cargo move along these and many other waterways around the world, which are vital parts of their surrounding economies.

Like their terrestrial highway cousins, waterways are linear assets. Linear assets pose different challenges from fixed assets, such as power transformers, and mobile assets, such as ships. Highways and waterways share a similar set of concerns about quality, environmental impact, accommodating mixed use, seasonal weather and traffic patterns, and more.

Instead of parts like a machine, linear assets have segments. The size and numbering of segments can vary widely. Characteristics of the asset can change over distance, such as water depth and rate of flow for a waterway. Different characteristics can change at different points in and across different segments.

Plus, there are relationships with parallel linear assets, such as power lines that supply energy to the fixed assets along a waterway. There’s constant interplay between the fixed, mobile and linear assets based on time of year, time of day, weather and other factors. All this change and variability means that analyzing linear assets quick gets complicated.

Situational intelligence applications, with the combination of spatial and network analytics and visualizations, work well for monitoring, managing and optimizing linear assets such as waterways. They offer the breadth and flexibility of data integration, analytics and visualization to handle the complexity of waterways and the myriad other related assets—fixed, mobile and linear. Users can analyze and visualize characteristics in real time across dynamic segments.

I apologize if I’ve ruined your romantic conceptions about water transportation.

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