LOOMO GEO: Robot Upgrades for GIS-enabled Data Collection


LOOMO is a personal segway robot with multi-terrain mobility and advanced computer vision, allowing it to follow users autonomously, avoid objects, and shoot stabilized video, while traveling up to 22 miles per charge and offering voice & gesture control. As a personal assistant, LOOMO can be further upgraded to help journalists more efficiently investigate and develop their stories.

Problem & How it’s Solved

Credible journalists rely on credible data, but collecting statistical, location-based data can be time-consuming, tedious and even impossible for individual humans. LOOMO GEO can streamline GIS enabled data collection to help journalists generate data visualization insights and develop compelling, data-driven stories.

LOOMO can be upgraded to utilize GPS navigation and follow a pre-programed geographic path set by journalists. It will rely on its object avoidance for a safe journey. Along the path, image recognition software will allow LOOMO GEO to scan the designated area for specific occurrences, take an image tagged with geo-location, and populate a GIS database. This will allow the journalist to generate an easy to understand visual data map.


1. GIS Enabled

LOOMO GEO can be programmed to follow a path set for it by its operator. The GIS path can be selected in-app.

2. Environmental Scanning with Target Recognition

LOOMO GEO can be programmed to recognize specific features in its environment. In order to count cigarette butts, for instance, a sample cigarette can be 3D scanned and loaded in as the new project’s target. LOOMO GEO will scan the path set for it and each match to the sample will be documented by photo and location.

3. Data Visualization

After collecting the GIS data, LOOMO GEO’s companion app will generate an interactive map for data visualization. The heat map will display clusters, indicating the prevalence of the project target, i.e. cigarette butts.


LOOMO GEO helps journalists and researchers gather data more quickly and reliably. This saves time and boosts credibility.


SARA, Spatially Aware Robotic Assistant: developed to survey areas in greater detail, i.e. interior spaces. However, SARA is not programmed to recognize and document the statistical prevalence of target objects.

LOOMO GEO App Sample

Note: This 2 pager proposal on how to upgrade the class robot to help journalists was prepared for Steven King’s MEJO 588 Emerging Technologies class in UNC’s School of Media and Journalism. The sample app images were made quickly in Adobe XD, which lets you design mobile app user interfaces 🙂

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