Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.

Abstract: Devices, methods and systems for disinfecting dry goods are described herein. In an aspect, dry goods such as dry foods can be sprayed within a disinfection device by a gas and liquid mixture. The gas and liquid mixture may include a mild acid and an ozone gas fluidized using a fluidization element of the device. As a result, spraying the dry goods with the gas and liquid mixture, the microbial activity on the dry goods are reduced and disinfection is achieved. Furthermore, organic dry goods such as corn, garlic, onions, and other such food items can maintain its organic status using the described disinfection devices, methods, and systems.