# Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network
## 2 Materials and Methods
### Data Acquisition  
Consists of measuring or capturing the relevant information for the research work [27]. According to the proposal presented, images of people with and without helmets will be collected, since deep learning methods can work with audio data, images, etc. and automatically learn the necessary representations to perform detection or classification tasks [28]. This phase will be divided into two sections, planning and execution.  
In the planning, a motorcycle brand Vento 2021 model \"Rocketman\" was selected, which is the second best-selling motorcycle brand in Mexico since it is the geographical area where the research study was conducted [29]. Next, a GoPro HEROS Session 10 MP 4 K Ultra HD Wifi-Sports Camera (4 K Ultra HD, 3840 \(\times\) 2160 Pixels, 120 fps, 1280 \(\times\) 720, 1920 \(\times\) 1080, 2560 \(\times\) 1440, 3840 \(\times\) 2160 Pixels, 720 p, 960 p, 1080 p, 1440 P, NTSC, PAL) was chosen as the device to record the drivers, because it has different capture modes and video settings, as well as the feature of incorporating a micro SD memory for storing the files generated and its ease of mounting on motorcycles. Table 1 presents the video configurations used in the experimentation. Then, the study subjects who participated in the tests were selected, where 13 were students of the Autonomous University of Zacatecas, with ages between 21 and 30 years old and 3 other drivers were residents of the state of Zacatecas, Mexico with ages between 30 and 41 years old. In this experiment, a total of 16 participants were used, of which 7 are women and 9 are men as a first approximation for a new approach to safety, based on the fact that the number of male drivers in LMIC is usually greater than 90%, as can be seen in the data presented by Datos Mexico [30]. Finally, it was determined that the helmets to be used would be certified full-face and modular  
Figure 1: Proposed methodology for the generation of an intelligent model for helmet detection in motorcyclists.  
helmets, for the following reasons: they are the safest helmets for motorcycle riders [31] and finally for being in line with objective 7 planned by the World Health Organization [11].  
In the execution part, and given that this proposal is intended to serve as the basis for the development of an intelligent system for monitoring the use of the helmet which is part of the motorcycle itself, the acquisition of the videos must be carried out from a position that meets two points, one, where don't obstruct the user's visual field and two, where don't compromise the visualization of data presented on the motorcycle's dashboard. That said, and as shown in Figure 2, the camera will be installed on the handlebars of the motorcycle on the side of the dashboard at a height where it does not significantly affect the user's field of vision.  
Once the position of the camera is selected, the videos will be recorded. Before starting the capture, the participants will receive instructions to try to start the motorcycle while carrying out the activity, simulating that the helmet use monitoring system was already installed, so that the images collected are useful for work.  
In this part, in order for the model to be robust, that is, that it can correctly classify the use of the helmet, it will be sought to have to a certain extent variety in terms of the use of personal items such as caps, face masks and sunglasses by the participants.