New Mexico Supercomputing Challenge

Stopping Blindness-Induced Collisions

Team: 39

School: Las Cruces High

Area of Science: Disability Management


Interim: Problem Definition: 
Human blindness costs more than 20 Billion EUR [1] annually in economic damages. This issue also represents approximately 350000 years of productivity lost annually. Current methodologies to combat limitations caused by human blindness all have similar disadvantages, notably high affordability costs, durability, and inconsistent performance. In solving the above issue, simplicity, ease-of-use, and affordability all must be taken into account. The group is utilizing simple programming language techniques with simplified user interface, cheap, widespread, commercially available materials, and accurate measurements for solving the problem.
An ultrasound sonic sensor maps out the environment in front of it; this information is then sent to a processor which corresponds distance of objects to beeps produces. Beep intensity corresponds to distance, with proximity of objects being represented with more rapid beeping.

Measurements: For experimental purposes, rather than beeping, number values will be recorded for object proximity for quantitative measurements. Various environments will be tested to explore device performance. 

Progress to Date: 
Presently, a prototype of our model has been created. This prototype uses an ultrasonic sensor in order to measure the distance of objects that lie directly ahead of it. The sensor beeps according to the sensed distance. The further away the sensed object is the lower the beep with the furthest measurement of 255 cm. As an object becomes closer the beep becomes higher. For experimental purposes the distance is sent back to the battery pack and shown on the display panel.

Expected Results: 
After completion of device and its testing, the proposed device shall with 90% accuracy or higher be able to monitor the environment 255 cm in front of it. The device will be cheap and simple to use.
Team Members: Grace Cowie, Molly Hurd, Vladislav Sevostianov
Sponsoring Teacher: Albert Simon


Team Members:

  Mollyanne Hurd
  Vladislav Sevostianov
  Grace Cowie

Sponsoring Teacher: Elisa Cundiff

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