Ideas

Investigation: Mobile Mapping

Mobile Mapping is a workflow that creates maps representing the human experience of spaces by visualizing unseen qualities like temperature, humidity, and biometric data. This series of post-occupancy evaluations assesses factors such as air quality and sound to enhance understanding of occupant experiences. Data is gathered using mobile phone cameras and off-the-shelf sensors, then mapped with Grasshopper. This automated approach increases data precision and volume, ultimately influencing and improving the design process.

April 16, 2025 | Posted by Adam Heisserer

INDOOR AIR QUALITY MAPPING

The atrium of Lake Flato’s Austin Central Library was tested for indoor air quality. Positioning was done through a pair of GoPro Session 5 cameras. A combination of sensors on the Arduino microcontroller and other off-the-shelf data logging air quality sensors were used to collect temperature, humidity, carbon dioxide, PM2.5, PM10, VOC’s, illuminance, sound, and the heart rate of the surveyor. These air quality data points can be mapped onto the nearest point on the point cloud and colored with a gradient to visualize the properties of the space.

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POSITIONING OPTIONS

  • GPS is the simplest and most easily available option. Early tests were completed with GPS as the positioning system, which works well when covering large areas outdoors. A margin of error of a few meters is reasonable for mapping at an urban scale, but GPS is not accurate enough for an indoor application.Indoor positioning with a WiFi signal is feasible, but it requires the placement of beacons within a space befor
  • SLAM is an acronym for Simultaneous Localization and Mapping. It’s a method used in robotics and autonomous vehicles in which a moving object uses sensors such as cameras, radar, or lidar (like radar, but with lasers) to map its surroundings in the form of a 3D point cloud, and then compute how it is moving relative to those surroundings.
  • Lidar requires more impressive hardware, with less work to process the data, and vice versa. Lidar is more expensive and not as universally available as video on a mobile phone, making vision based SLAM more ideal, if not as easy.