SensorUp worked with partners as well as the Open Geospatial Consortium (OGC) and the US Department of Homeland Security to construct an incident management information sharing system.
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Common Operating Picture

Combining disparate data and communicating only critical information

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Mapping & Analytics

Easy-to-use portal featuring built-in mapping and analytics capabilities.

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Permissions Control

Communicate the right information to the right role.

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Maximize Efficiency

Reduced administrative overhead time and costs.

Common Operating Picture

SensorUp’s Platform was used to support on-the-fly connection of disparate sensors in near real time (less than one second delay). The platform supported a set of rules dictating what information should be presented on screen to a given role, at a given point in time.

Display and visualization were used to communicate the relative importance of information. SensorUp’s COP dashboard presented information in a map-based portal with analytics accessible in the same screen.

SensorUp API Platform

SensorUp’s Platform acts as the bridge allowing devices to interact with each other and with 3rd-party web applications.

In this case, devices are in-situ, fixed, mobile, and wearable. In situation management, devices measure disparate phenomena, are sourced from numerous manufacturers, and belong to different organizations. SensorUp’s platform combined this variety into a single portal.

SensorUp provided cloud, server, and connection services.Check out SensorUp's IoT Platform »

A High-Stakes Portal

Emergency and disaster management is a high-stakes environment. The situation changes rapidly and decisions can be a matter of life or death. Information streams in from multiple sources including police, fire, hazmat, military, private response personnel, and individual citizens. Situation Commanders need to make informed decisions on the fly and need to see the important data while filtering the noise. By intelligently coordinating and aggregating real-time information SensorThings Cloud helps situation commanders by providing more signal and less noise reducing cognitive load.

How it Works

To create a working common operating picture (COP), disparate Datastreams must be brought together in real-time. To prevent information overload we apply, analytics, rules, machine learning, and notification systems that enable the right information to reach the decisions makes at the right time. When each operative is outfitted with biometric sensors the SensorThings platform learns normal ranges and notifies team leaders if vital signs become abnormal. Then through our industry-leading geospatial capabilities, SensorThings broadcasts an alert notification to all nearby personnel to assist.

Robust geospatial capacity is key to emergency management. In emergency situations, it is vital to know where events are occurring, where responders are along with a continuous spatial-temporal view of the evolving hazards. Spatial context matters when hazards are carried on the wind or when evacuations can be obstructed by artificial and natural barriers such as dead-ends or waterways. When dispatching personnel, it is vital to know who optimally positioned to respond.

Robust geospatial capacity is also necessary to support emergency management. The situation happens in physical space, and effects propagate through it. Hazards can be carried on the wind or downstream, evacuations can be obstructed by artificial and natural barriers such as dead-ends or waterways. When dispatching personnel, it is important to know who is actually closest, rather than who is closest as the crow flies. In our earlier example, in which the nearest operative is being sent to help a fellow responder in a critical state, this is particularly important. If the closest able body is behind a wall, and must navigate a complex network such as a circuitous route through a darkened building, the fastest response may actually be achieved by sending someone who appears farther, but can reach the situation sooner via a more direct route. To know this, the system must understand network location rather than just point locations.

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