Fine-Grained Location-Based Sensor Mapping: Poster Abstract

Achieving an optimized control schema for building automation systems relies on the accurate collection of environmental modalities and accurate modeling of how the environment reacts to changes. Recent advances in indoor localization coupled with the influx of smart devices have created a unique and efficient method of collecting these modalities in real-time. This allows for quicker adaptation of the control schema by increasing both temporal and spatial information resulting in a reduction of operating costs. Visualizing these environmental modalities with fine grained positional accuracy allows for a better understanding of inter-dependency between modalities and also allows for a comparison between the real-time data across several modalities and pre-defined models.