Abstract: Disclosed herein is a method for an accurate edge classification using artificial intelligence. The system includes a network and a plurality of terminal devices communicably coupled via the network. The plurality of terminal devices are configured to capture data. The system further includes microcontrollers communicably coupled to the plurality of terminal devices. The microcontrollers are configured to send data from the plurality of terminal devices to the microcontrollers via the network. The microcontrollers are further configured to classify the received data and predict the classified data via the microcontrollers using Artificial Intelligence (AI) algorithms.

Abstract: A system for recognizing unattended humans who require supervision is disclosed. The system includes monitoring content from one or more cameras. The system includes processing an artificial intelligence (AI) algorithm, wherein the AI algorithm is configured to detect unattended humans. The system includes processing one or more images, received from the one or more cameras, based on one or more AI algorithm rules. The system includes detecting an unattended human based on the processing of the one or more images, wherein the unattended human is in close proximity to a hazard. The system includes alerting one or more authorized individuals, with one or more notifications of the unattended human's close proximity to the hazard.

Abstract: A system for recognizing unattended humans who require supervision is disclosed. The system includes monitoring content from one or more cameras. The system includes processing an artificial intelligence (AI) algorithm, wherein the AI algorithm is configured to detect unattended humans. The system includes processing one or more images, received from the one or more cameras, based on one or more AI algorithm rules. The system includes detecting an unattended human based on the processing of the one or more images, wherein the unattended human is in close proximity to a hazard. The system includes alerting one or more authorized individuals, with one or more notifications of the unattended human's close proximity to the hazard.

Abstract: In one embodiment, the present invention is a mobile application that, after being installed and activated on a mobile device, detects whether there are network signals. After the invention detects network signals, the mobile application asks the user whether or not there is an occupant in the vehicle. If the user responds that there are one or more occupants in the vehicle, the invention starts checking for interruption of the network signals. When the network signals are no longer available, the invention sends a notification to the user requesting him/her to respond to the notification. If the user does not respond to the notification, the invention sends alerts to a preprogrammed list of several people and/or emergency services. The alerts may include the location information of the vehicle.

Abstract: In one embodiment, the present invention is a mobile application that, after being installed and activated on a mobile device, detects whether there are network signals. After the invention detects network signals, the mobile application asks the user whether or not there is an occupant in the vehicle. If the user responds that there are one or more occupants in the vehicle, the invention starts checking for interruption of the network signals. When the network signals are no longer available, the invention sends a notification to the user requesting him/her to respond to the notification. If the user does not respond to the notification, the invention sends alerts to a preprogrammed list of several people and/or emergency services. The alerts may include the location information of the vehicle.