Crane Gesture Detector

Published: 2 July 2019| Version 1 | DOI: 10.17632/fpmk9zmjmm.1
Contributor:
juan Zuluaga

Description

Project Objectives In the field of construction there are some operators called crane helpers which indicate to the crane operator through some hand signals what he has to do and of course there are some other operators that work on other activities But they have to be aware about the crane activities so they constantly must see the signals performed by the crane helpers. And all these activities represent an imminent risk and not only for the crane operator but also for the people close to him The main point of our project is create an application based on activity recognition through smartphone sensors to detect the signal performed by a human operator or a crane helper through a machine learning algorithm. Sensors used: Two cell phones are used, of which the accelerometer and the gyroscope are used. Location of the sensors: The sensors are located in the hands and one at the height of the bicep Collection mechanism: For the collection of the data, five series were made, in each of the series 6 signals were made defined for the experiment, for the exercise 5 people were used.

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