7 - Data-Driven Expansion of a City-Wide LoRaWAN Network
St. Galler Stadtwerke (sgsw) operates its own LoRaWAN network within the city of St.Gallen, using dozens of gateways. This network collects data from close to 10'000 LoRa-based modules, primarily used for monitoring water, gas, and district heating systems. Many more modules are expected to be added in the coming years. Despite selective optimizations and the targeted addition of gateways, overall network quality has not significantly improved. Challenging topography and urban density result in areas with poor or unreliable signal coverage, which hinders stable data transmission and efficient operation.
Challenge Owner
Postdate 07.08.2025
Goal & Challenge
We plan a large-scale expansion of the LoRaWAN infrastructure across the 40 km² urban area of St.Gallen. However, this expansion must not be random – it should be strategic and data-driven. We are looking for an approach that helps answer the following questions:
- Where are the current weak points in network coverage?
- Which factors (e.g., topography, building density, infrastructure, module distribution, historical signal strength) most affect network performance?
- How can existing internal and external data be used to develop an intelligent and optimized gateway deployment plan?
- How many additional gateways are needed, and where should they ideally be installed?
Expected Outcomes
- Tools or concepts to analyze and visualize current network coverage
- Suggestions for prioritized gateway placement
- A scalable planning model for smart IoT network expansion
Available Data (examples)
- Location and status of existing gateways and modules
- Signal strength and network coverage data
- Topographical maps and building information
- Urban density and infrastructure layers
Target Audience
Developers and data scientists with interest in IoT, network optimization, GIS, and smart city solutions.