Abstract
Recent advancements in metal oxide semiconductor sensors enable system integrators to make sensor devices without the traditional complications of operating barebone sensor components. Anyone, so it seems, can put together multi-sensor-systems by combining an integrated sensor subsystem with a small piece of digital infrastructure, resulting in low-cost sensor systems or sensor networks for all kinds of applications. With low energy consumption, the deployment of close meshed sensor networks is becoming a reality, promising high density data for big data models. However, data quality is not necessarily a feature of such devices, since the device output signals are heavily processed and the insight into the actual operating technique is black-boxed by the respective sensor manufacturer. High volume production of a sensor model requires widely applicable output information, yet this mainstreaming negatively impacts quality control efforts on the system level as well as niche applications that require specialized operation modes. This article exemplarily examines the measurement chain of typical metal oxide semiconductor sensor applications and deduces requirements for a technically sound advancement of the subject for research and commercial purposes. Equivalent considerations can be made for any low-cost sensor principle and their respective challenges. The conclusion urges all stakeholders participating in the development and marketing of sensor devices to advance a scientifically valid state of knowledge and to educate their customers and even the general public accordingly.
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