detection Multimodal data fusion

The Indoor Outdoor (IO) status of mobile devices is fundamental information for various smart city applications. In this paper we present NeuralIO, a neural network based method to deal with the Indoor Outdoor (IO) detection problem for smartphones. Multimodal data from various sensors on a smartphone are fused through neural network models to determine the IO status. A data set consisting of more than 1 million samples is constructed. We test the performance of an early fusion scheme in various settings. NeuralIO achieves above 98% accuracy in 10-fold cross-validation and above 90% accuracy in a real-world test.