Two months ago, we purchased a robot called the temi 3 (available here). This robot features a large touch screen, LIDAR for obstacle avoidance, and text-to-speech/natural language processing/automatic speech recognition included without the need for setting up or training. The tablet attached to the top of the robot runs on Android and controls all functions of the robot (through an open-source SDK). Temi demos and videos are available on the Robot Temi YouTube channel.

After learning about all the functionality that is baked in to this robot and the vast documentation of its SDK, we were confident that we can use this to develop applications in our environment. There are two projects that we are interested in working on.Both projects involve the smell inspector device described in this post to classify smells.

Analyzing Smells in Hospital Rooms

First, we want to detect if urine or stool was present in a patients hospital room. This is in early development and testing of this is taking place within our own office. Temi comes with “patrol” mode, which visits all predefined waypoints on a floor map. To allow temi to roam freely, the robot needed to be lead around our floor to get a map of the area and to add waypoints (e.g. Cody’s office, Snack Room, Conference Room). Once this was complete, we can programmatically start a patrol using the SDK.

After mapping and patrolling was set up, we needed a way to mount the smell inspector sensor to the robot. Dmitry Strakovsky (UK College of Fine Arts) designed a mount that attaches to the back tray of temi. This is just a proof-of-concept mount and will change before the final product, but it does the job well.

Once the smell sensor is mounted and connected via USB to the temi, we can interface with it through our custom Android app. The data from this sensor is then sent to a server, which predicts a smell and returns a classification. At this time, we have collected ambient air data around the office, but still need to chose one (or more) other smells to detect (likely coffee).

Results from this experiment will be posted here.

Monitoring Humidity and Temperature of a Floor

Second, monitoring the temperature and humidity of an area. The smell inspector also collects temperature and humidity data along with each measurement. This is useful paired again with the patrol mode. Hospitals highly monitor temperature and humidity of a floor as they must keep these metrics in acceptable ranges. Using this robot to patrol a floor while collecting these measurements allows us to present real-time data (or heatmaps) to the appropriate parties. This is in contrast to mounting sensors throughout a floor and which may get costly and difficult to maintain. This will use the same physical and app set up as described in the above. This project has not been started yet, but we invision this temperature and humidity data will be sent a website for viewing and a server to send alerts if either metric is out-of-range.

Results from this experiment will be posted here.