Forklift real-time monitoring and early warning system and method based on embedded development and deep learning

Abstract

The invention discloses a forklift real-time monitoring and early warning system and method based on embedded development and deep learning. The system comprises a monitoring camera shooting terminal,an embedded development platform, a mobile user terminal and a webpage user terminal, wherein the monitoring camera shooting terminal is in wired connection with the embedded development platform; the embedded development platform is in wireless connection with the mobile user terminal; the embedded development platform is in wired connection with the webpage user terminal; a deep learning network is built in the embedded development platform; a forklift, pedestrians and the like are detected in real time; an early warning type is judged; early warning information is stored in a database server and is sent to the mobile terminal in real time through short messages and mails; and the webpage user terminal can check, retrieve and count the early warning information in real time. The systemcan automatically adjust a frame extraction interval and a deep learning network type used for detection, self-supervise mAP values and self-learn and update weights of the forklift, the pedestrians and the like. The system is flexible and convenient to use, low in labor input, and intelligent and reliable.

Description

technical field [0001] The invention relates to the field of industrial operation safety, in particular to a forklift real-time monitoring and early warning system and method based on embedded development and deep learning. Background technique [0002] Forklifts, also known as industrial handling vehicles, are widely used in production and life because they can move goods in a short distance and in large quantities. In my country alone, there are 2.9 million to 3.5 million forklifts moving goods in various workplaces. However, in the process of actually driving a forklift, there are blind spots, fatigue, and speeding that lead to collisions, rolls, etc., and then serious accidents occur, resulting in injuries and deaths, huge compensation, and leadership accountability. At present, the development of deep learning is mature, and the network structure is relatively easy to implement and train, and can be easily applied to other fields such as target detection. Therefore, b...

AI Technical Summary

Problems solved by technology

However, in the process of actually driving a forklift, there are blind spots, fatigue, and speeding that lead to collisions, rolling, etc., and then serious accidents occur, resulting in injuries and deaths, huge compensation, and accountability by leaders.

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