A benchmarking model for sensors in smart environments
In smart environments, developers can choose from a large variety of sensors supporting their use case that have specific advantages or disadvantages. In this work we present a benchmarking model that allows estimating the utility of a sensor technology for a use case by calculating a single score, based on a weighting factor for applications and a set of sensor features. This set takes into account the complexity of smart environment systems that are comprised of multiple subsystems and applied in non-static environments. We show how the model can be used to find a suitable sensor for a use case and the inverse option to find suitable use cases for a given set of sensors. Additionally, extensions are presented that normalize differently rated systems and compensate for central tendency bias. The model is verified by estimating technology popularity using a frequency analysis of associated search terms in two scientific databases.