Enhancing Location Intelligence with Vertical Positioning

Vertical positioning is critical for location intelligence and emergency response in large, dense urban areas. Longitude and latitude alone are not enough to identify a subject’s position in a multi-story skyscraper, underground parking garage, or subway station, for example. Nevertheless, the automatic push of emergency caller location data to Public Safety Answering Point operators today generally uses 2D maps (X- and Y-axis only).

Using a combination of device and mobile networks data, vertical, or 3D, location adds Z-axis information to 2D models to place a caller on a specific floor of a building or subterranean structure. The US Federal Communications Commission (FCC) has led the way in improving emergency services by developing new standards for 3D location, generally requiring vertical accuracy to within 3 meters above or below the handset. In alignment with these requirements, Lawful intelligence and location-based solutions need to be engineered to incorporate a variety of methodologies for achieving 3D positioning accuracy and require active industry collaborations to advance these capabilities.

The 3D Location Intelligence Imperative

When first responders arrive at an urban site without accurate vertical location information, they may be unable to find emergency callers. The resulting delay can put lives at risk, wasting valuable seconds that could be spent treating critical injuries or diffusing a hostile situation.

A variety of techniques can be used to calculate z-axis position based on information from both handsets and mobile networks. However, solutions must be highly reliable and cover the highest possible portion of the population. They must be widely applicable across the full spectrum of devices, from older feature phones to modern smartphones. They must also be interoperable with all mobile network generations, from 2G to 5G. Because of these mandates, a combination of 3D positioning methodologies is often best.

Handset-Based Techniques: Potential and Limitations

While none are fully effective or reliable on their own, and some are not yet technologically mature, the following are the most commonly used handset-based approaches to establishing vertical location:

• Global Navigation Satellite System (GNSS): GNSS is highly accurate, but the need for a satellite in a specific overhead location and the device’s inability to transmit a signal through building walls makes it unreliable for calculating vertical position.
• Barometric pressure: A growing proportion of new smartphones can determine barometric pressure for vertical positioning, however the data can be affected by weather and building features such as elevator shafts. In addition, older generation devices do not have this capability.
• Wi-Fi networks: Individual Wi-Fi networks visible by a device can provide vertical position information, albeit with lower reliability than mobile network mast position due to a dependency on open-source databases of Wi-Fi network locations.
• Bluetooth and other RF Beacons: Dedicated beacons can be deployed to provide indoor vertical location information, but the technology requires significantly more widespread adoption to meet the needs of law enforcement and emergency services.
• Mobile networks: can provide signal angle of arrival and angle of departure information to the network, which can locate devices on the vertical axis, but as with beacons, this technology is not yet pervasive among handsets and networks.

Network-Based Techniques: Potential and Limitations

There is some overlap in handset- and network- based vertical location techniques, and like the handset-orientated approaches above, any single network approach is insufficient on its own:

• Mobile networks: Signal strength is highly dependent on penetration into the building and the relative location of the mast, yet this set of techniques will become more valuable with beamforming in 5G networks.
• Bluetooth or other RF Beacons: These can be deployed in large buildings to provide height location but can be costly and must be widespread to provide value.
• Wi-Fi networks are prevalent in large buildings, but to be reliable for vertical location a more rigorous process for comprehensive, accurate network information must be established.

To realize the full benefit of all the above techniques, the ecosystem must collaborate for further research and adoption.

The Path Forward

The breadth of technologies available offers potential for novel data fusion techniques to contribute vertical position information to location intelligence. AI and machine learning are revealing new approaches to assessing the accuracy and reliability of position data from multiple approaches for better overall outcomes. All relevant parties need to work together to advance these solutions, including location intelligence technology vendors, PSAP operators, device/OS providers, and network vendors.

Looking ahead, government mandates may play a role in providing common, reliable approaches. Given the significant costs of deploying these solutions, government funding may also be needed. For the sake of accurate vertical location information for emergency response, technological innovation and stakeholder support must combine to replace the 2D techniques and maps prevalent today with vertical, 3D positioning.

The opinions expressed are those of the author and do not necessarily represent the views of EENA. Articles do not represent an endorsement by EENA of any organisation.

Michael Gebretsadik and Stuart Walsh

Location Product Manager and Field Product Director at SS8 Networks | + posts

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