In the current phase of Geolocation, the accuracy might vary from time to time due to KPN’s continuous improvements. In short, when using the Geolocation functionality, you can expect the following:
Static devices will have a higher accuracy than moving devices
Slow-moving devices will have a higher accuracy than fast-moving devices
Rural areas should provide higher accuracy than suburban areas
Suburban areas should provide higher accuracy than dense urban areas
In urban areas, high rise buildings will negatively influence the accuracy
When a static device is turned on, the accuracy will improve during the first subsequent messages
The accuracy will be less near the borders of the Netherlands (since less gateways will be available).
Another influence on the accuracy of Geolocation is reflection of the radio signal. Due to the reflection, you might see larger and more unstable deviations than average. This is especially relevant in areas with a lot of water, in densely-built environments and in areas with a lot of machinery or metal constructions.
KPN has done multiple tests and the following is an indication of the performance of Geolocation with different settings and in different environments. The results of these test are provided in the table below. As KPN works on improving this service continuously, the parameters are subject to change. For the results below, the number of different messages used to calculate the position lies between 3 and 8.
90% on average
60 meter on average
LoRa Geolocation is designed for outdoor applications. Please note that LoRa Geolocation is not designed to be used at indoor locations or for indoor use cases. While localization will quite frequently work for indoor use cases, KPN will only support he Geolocation functionality for outdoor usage. The main influence for indoor usage is the building material, which may prevent the LoRa message from being received by the minimum of 3 required gateways.
As stated earlier, several factors impact the accuracy of the Geolocation service. In general, the graph in the figure below is representative of the average accuracy in the Netherlands (all locations and all environments for a Static device profile). Depending on your location and environment, you can experience better or worse performance:
95% of the measurements are under 100m
50% of the measurements are under 60m
To give an example of the impact of different environments, KPN has executed specific testing in a environment with tall buildings (more than 6 floors) in the Hague and Rotterdam with Static devices. The 95-percent interval could increase up to 250 meters in case of reflections (Figure 9). The main influence is the reflection of the uplinks. KPN expects to improve this specific case in the near future.
KPN has already performed tests with slow-moving devices. We believe that the majority of use cases should use the Static Device Profile. The main focus of our improvements is the stability and accuracy of Geolocation for static devices. To give an indication, Figure 11 shows the average performance for end devices on slow-moving device profiles.
The relevance of the number of uplinks that can be used by the locsolver is shown in Figure 10. While the accuracy with three messages is around 200 meters, it improves by 30% to around 130 meters after 15 messages. This information is relevant for the design of your solution.