SPATIOWL is designed to effectively manage location data of moving objects in real-time through time series. By managing different type of data layers with latitude and longitude (Geographic Coordinates), SPATIOWL handles any kind of data varying from typical moving objects (such as vehicles, trains, trams, bikes, humans and static data (e.g., facility, building, roadside monitoring sensors) and external information like social network information).
By combining all this data, it allows users to visualize and understand conditions that have been very difficult to perceive before:
- For instance, we routinely rely on the roadside camera equipped at specified spots along the road to see current traffic conditions, but it is not easy to see the entire urban traffic flow in real-time. SPATIOWL makes it possible to visualize the urban traffic flow globally and provide a broader perspective on urban traffic conditions by collecting and aggregating myriads of real-time roadside sensors covering "wider areas" over urban locations.
In addition to accumulating vast amount of urban traffic data, it also generates new "insights" which have been difficult to get up till now.
- Another example is with delivery truck drivers who are used to decide which routes they take based on their experience. By mashing up real-time data to aggregate accidents, urban traffic congestion, data from internet instant messaging services to the drivers, we can obtain more accurate and dynamic picture of the urban traffic flow. By using such information it would be easier for truck drivers to optimize their delivery routes, reducing delays and fuel costs.
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