RoomCanvas: A Visualization System for Spatiotemporal Temperature Data in Smart Homes

Abstract

Spatiotemporal measurements such as power consumption, temperature, humidity, movement, noise, brightness, etc., will become ubiquitously available in both old and modern homes to capture and analyze behavioral patterns. The data is fed into analytics platforms and tapped by services but is generally not readily available to consumers for exploration due in part to its inherent complexity and volume. We present an interactive visualization system that uses a simplified 3D representation of building interiors as a canvas for a unified sensor data display. The system's underlying visualization supports spatial as well as temporal accumulation of data, e.g., temperature and humidity values. It introduces a volumetric data interpolation approach which takes 3D room boundaries such as walls, doors, and windows into account. We showcase an interactive, web-based prototype that allows for the exploration of historical as well as real-time data of multiple temperature and humidity sensors. Finally, we sketch an integrated pipeline from sensor data acquisition to visualization, discuss the creation of semantic geometry and subsequent preprocessing, and provide insights into our real-time rendering implementation.