Nowadays, various devices for open-loop monitoring in vehicles can be found. These devices consist of multiple video recording cameras; some even include audio recording systems. Due to the complexity of real-time monitoring of individuals, their interactions, moods, fatigue estimates, etc. The tracking of vehicle operation variables has been overlooked, and all responsibility has been transferred to the users (drivers and passengers).

Advanced Driver Assistance Systems (ADAS) minimize driver interaction by automating the main processes involved in vehicle operation with high precision. However, these systems do not consider variables associated with driver-vehicle interactions and potential safety failures related to authorized individuals who are allowed to drive. This opens up possibilities for accidents involving minors and individuals attempting to drive under the influence of alcohol or in the presence of potential health emergencies. Consequently, compact computational systems enable the utilization of abstract data processing devices, sensor data, and environmental variables extracted from features embedded in image data, audio recording systems, Global Positioning System (GPS), and various detection systems for displacement variables and driving behaviors. A wealth of information can be collected during vehicle operation periods.

Our technology, DriveGuard MTools, aims to automate the monitoring system for environmental variables inside vehicles, specifically detecting variables related to driver and occupant behavior. This is achieved through the utilization of various deep machine learning algorithms that identify authorized drivers and a wide range of emotions based on different events occurring within the vehicle's environment. Furthermore, our artificial intelligence algorithm incorporates multiple image processing algorithms to identify and characterize events within the vehicle in real-time, enabling the early identification of potential heart attack stages with great precision. Additionally, our AI system is configured with a vehicle shutdown timer in case an unauthorized person is driving or when a threat to the driver or any of the occupants is detected. In such cases, the system notifies the authorities of the events (providing images, videos, audio, and GPS location) and generates a record on our platform for user review.

Users can access their vehicle's activity history, driving trends (such as speed, acceleration, geographic locations, etc.), and multimedia event records through the mobile application. Users can also configure the following system parameters:

• Authorized facial recognition for individuals allowed to drive the vehicle
• Automatic engine shutdown programming in case of theft

Remote engine shutdown

• Alert programming in case of emergencies such as accidents, intoxication, fatigue, or other variables that hinder optimal driving conditions
• Emergency contacts or authorities who will receive alerts
• Customized triggers for each alarm case.