In-vehicle environment monitoring early warning method based on cloud service and depth neural network

Abstract

The invention belongs to the technical field of information processing, and discloses an in-vehicle environment monitoring and early warning method based on cloud service and a depth neural network. When an individual enters a vehicle, information is detected by a human body infrared detection module. The detected real-time data is transmitted to an intelligent interconnected cloud platform through a 5G wireless network, a database server of the intelligent cloud performs cloud storage and backup operations, and a content management server performs cloud computing and big data cluster analysisdata mining operations. According to the method, the intelligent cloud is utilized to monitor the indoor air of the automobile in real time, and a proposed alarm information level classification algorithm based on a logic regression optimization model is utilized at a cloud end to accurately classify the danger level of the automobile owner, and a decision is made by using a designed system self-adaptive deep reinforcement learning algorithm; at the cloud, a proposed Pyechars-Based visualization algorithm is used for statistical analysis of mass data and independent and safe visualization services are provided for all vehicle owner users.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to an in-vehicle environment monitoring and early warning method based on a cloud service and a deep neural network. Background technique [0002] At present, the commonly used prior art in the industry is as follows: In addition to traffic accidents, there is also a major cause of death in the car-the environment in the car room-air (carbon monoxide gas exceeds the standard, formaldehyde Exceeding the standard), temperature (the temperature exceeds the limit of the human body: the most vulnerable groups: the elderly and infants). Facing the dangerous factors in the car interior, design and implement a car interior environment detection and alarm method and system based on the Internet of Things and deep reinforcement learning algorithm to accurately detect carbon monoxide gas, formaldehyde concentration, and temperature and humidity inside the car, and mo...

AI Technical Summary

Problems solved by technology

[0005] (1) At present, the existing in-vehicle air safety detection system in the society cannot intelligently detect and accurately store and analyze data and provide intelligent remote alarms

[0006] (2) The current assisted driving system used to prevent automobile fatigue driving is complex in technology, relies on real-time monitoring of high-definition cameras, and has high cost. Convolutional neural network is used for deep learning, and the number of samples of human body poses for training is limited. In the initial research and development stage, it is not suitable for rapid promotion in the society

[0008] Significance of solving the above-mentione...

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