Enel Computer Vision Project

Here are a few use cases for this project:

1. Workplace safety compliance: Enel could be used in industrial and construction environments to ensure that workers are following safety regulations by wearing helmets (capacetes) and uniforms (fardas). The model can detect those without helmets (sem-capacete) or not in uniform (não farda) and alert supervisors for quick action.

2. Crowd monitoring and management: At large public events or gatherings, Enel can be employed to analyze crowd demographics, including the number or percentage of people in uniforms (farda), without helmets (sem-capacete), or those in civilian clothes (civil). This information can help event organizers optimize crowd control measures and ensure proper safety protocols are in place.

3. Surveillance and security: Enel can be used in surveillance systems, such as CCTV networks, to identify and flag individuals without helmets (sem-capacete) or not in uniform (não farda) in restricted areas, helping security personnel quickly respond to potential breaches or safety violations.

4. Insurance claim investigations: Insurers can use the Enel model to evaluate accident scenes and determine if proper safety gear, such as helmets (capacetes), was used by claimants. This allows insurance companies to verify claims and assess if proper safety precautions were taken.

5. Training and education: Enel's computer vision model can be utilized in educational videos and training simulations, enabling trainees to work on identifying and reinforcing the practice of wearing correct safety gear like helmets (capacetes) and uniforms (fardas), as well as learning to distinguish workers who are out of compliance (sem-capacete or não farda).