Accuracy

Depending on the signal standard, we can promise different levels of accuracy.

Underlying this is the assumption that we have enough data about the area. Without enough data, Ichnaea will fall back to less accurate data sources depending on the configuration.

Bluetooth is the most accurate, followed by WiFi, and than cell based estimation using single cells, multiple cells, or cell location areas. GeoIP serves as a general fallback.

Bluetooth / WiFi

Bluetooth and WiFi networks have a fairly limited range. Bluetooth low-energy beacons typically reach just a couple meters and WiFi networks reach up to 100 meters. With obstacles like walls and people in the way, these distances get even lower.

However, this data can be skewed when the device in question is moving. It takes some time to do a network scan and devices tend to cache this information heavily. There can be a time delta of tens of seconds between when a network was actually seen and when it is reported to the application layer. With a fast moving device this can lead to inaccuracies of a couple kilometers. WiFi networks tend to show up in scans long after they are out of reach, especially if the the device was actually connected to these networks.

This means position estimates based on WiFi networks are usually accurate to 100 meters. If a lot of networks are available in the area, accuracy tends to increase to about 10 or 20 meters. Bluetooth networks tend to be accurate to about 10 meters.

One difficult challenge with Bluetooth and WiFi networks are the constantly moving networks. For example, WiFi networks installed on buses or trains or in the form of hotspot-enabled mobile phones or tablets. Detecting movement and inconsistencies between observed data and the database world view are important.

GSM Cells

In GSM networks, one typically only has access to the unique cell id of the serving cell. In GSM networks, the phone does not know the full cell ids of any neighboring cells unless it associates with the new cell as part of a hand-over and forgets the cell id of the old cell.

So we’re limited to a basic Cell-ID approach where we assume that the user is at the center of the current GSM cell area and we use the cell radius as the accuracy.

GSM cells are restricted to a maximum range of 35km, but there are rare exceptions using the GSM extended range of 120km.

In more populated places the cell sizes are typically much smaller, but accuracy will be in the range of tens of kilometers.

WCDMA Cells

In WCDMA networks, neighboring cell information can be available. However, limitations in chipset drivers, the radio interface layer, and the operating systems often hide this data from application code or only partially expose the cell identifiers. For example, they might only expose the carrier and primary scrambling code of the neighboring cells.

In most cases we are limited to the same approach as for GSM cells. In urban areas, the typical sizes of WCDMA cells are much smaller than GSM cells. This leads to improved accuracy in the range of 1 to 10 kilometers. However in rural areas, WCDMA cells can be larger than GSM cells, sometimes as large as 60 to 70 kilometers.

LTE Cells

LTE networks are similar to WCDMA networks and the same restrictions on neighboring cells applies. Instead of a primary scrambling code, LTE uses a physical cell id which for our purposes has similar characteristics.

LTE cells are often smaller than WCDMA cells which leads to better accuracies.

LTE networks also expose a time-based distance metric in the form of the timing advance. While we currently don’t use this information, it has the potential to significantly improve position estimates based on multiple cells.

GeoIP

The accuracy of GeoIP depends on the region the user is in. In the US, GeoIP can be fairly accurate and often places the user in the right city or metropolitan area. In many other parts of the world, GeoIP is only accurate to the region level.

Typical GeoIP accuracies are either in the 25 km range for city based estimates or multiple hundred kilometers for region based estimates.

IPv6 has the chance to improve this situation, as the need for private carrier networks and network address translation decreases. So far this hasn’t made any measurable impact and most traffic is still restricted to IPv4.