Hear about Mines students recent successes at Hackathons, straight from the students themselves.

IRMI (Intuitive Remote Manipulation Interface)
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IRMI makes use of the Leap Motion to transmit precise hand movements to
remote areas for humanoid robot applications.

Team: Stephen Agee, Easton Bornemeier, Kristin Farris, Daichi Jameson

Description: IRMI aims to remove humans from life-threatening situations
without sacrificing the intuition that human hand control offers. IRMI
utilized the Leap Motion tracker, long-range data transmission, and a
dexterous robotic hand (simulated within the Unity game engine) to
translate human hand movement to remote locations for applications such
as bomb defusal, remote surgery, and nuclear sites. Custom gesture
recognition was used to interact with the virtual environment and
simulate the potential of the product.

Challenges Entered: Freewave long-range transmission application

Cool encounters: A lot of judges and other students who stopped by our
table were very impressed with what we had done and thought it was a
great application of the hardware. A young girl got to ‘defuse’ our
virtual bomb and was very excited about it. We had a great conversation
with a guy who helps start-ups get the capital they need to start and
was extremely interested in our group furthering our product and seeing
what we could do with it given more time and potentially funding our
efforts to do so.

Alteryx Challenge Team
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We were given an unexplained data set and had to use it to determine
what specific event they were talking about and predict its attendance.

Team: Tyler Quast, Ben Lin (Civil), Alejandro Martinez (a future Mines
student, currently in high school)

Description: We solved the challenge in Python. We had an unexplained
data set of binary values. We changed the binary into ASCII which
returned JSON objects and index values of some sort. After being given
multiple incorrect data sets, which ate up most of the first day, we
were finally given a correct data set from Alteryx which using the index
values, turned the JSON objects into Longitude and Latitude coordinates.
We realized the coordinates were to locations to previous winter
Olympics locations with the final one being Beijing. We then used data
like country population, past attendance for winter Olympics and
attendance based on continent we were able to determine an estimate for
the attendee of the 2022 Beijing winter Olympics. This challenge was
actually very simple, however we spent an incredible amount of time
working with an incorrect data set provided by Alteryx which was very
frustrating as we could not pinpoint the source of the error.

Challenges Entered: Alteryx Challenge

Prizes: We got second place and got a 50$ Amazon card and an Echo dot.
The top three teams all got invited for interviews at the Alteryx
office.

Wii-Track
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Distributed inventory tracking using WiiFit, Rasberry Pi, and Arduino.
Backed by the computing power of AWS Lambda, and the flexibility of the
DynamoDB NoSQL database.

Team: Sumner Evans, David Florness, Jack Garner, Robby Zampino (EE)

Description: Wii-Track is a system for package tracking designed for use
in a variety of scenarios such as warehouses. The name Wii-Track comes
from the fact that we used a WiiFit board as our “scale” for this
prototype. Our overall goal was to make inventory tracking more
cost-effective by utilizing sensors and data analytics to identify
inventory items automatically, without human intervention. For the
hackathon, we utilized two metrics (weight and color) to identify
objects, however, we designed the system to scale to any number of
additional metrics such as image recognition and infrared image data.

Challenges Entered: Dish Network challenge to create a system for asset
tracking which utilized IOT technologies, and Best use of AWS.

Prizes: We won the Best use of AWS challenge, received first place in
the Dish Network Challenge, and won the Judges Favorite award.