Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in their spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT)-enabled low-cost sensor systems have offered a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, 20 sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden (Dresden University of Technology). Furthermore, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration.