Many institutions started research and development using AI technology to prevent child abuse in kindergartens
Recently, child abuse incidents in kindergartens have occurred frequently, but video surveillance, which should have played a role in shock, prevention, and evidence collection, has repeatedly caused problems. Not only has it failed to make the child abusers feel discouraged, but also data loss and other failures occurred during investigation and evidence collection. Making child abuse costs cheaper and cheaper. So, how should the camera be no longer a display? The answer is to let it judge whether there is child abuse behavior, that is, the introduction of AI technology.
A research team at Guizhou Nationalities University has been studying this topic and is preparing to launch an artificial intelligence system to capture child abuse behavior in kindergartens in real time. According to Rao Yan, the project's chief scientist, her team started the research in 2013. They found that although most kindergartens in China installed surveillance cameras in key locations such as classrooms, they did not play an effective role for a long time. There are several reasons for this. For example, some kindergartens only turn on the camera when there is an inspection in order to save costs. There are still some lucky feelings. Even if the parents look at the surveillance video, they will not find the problem because the amount of data is too large.
The artificial intelligence algorithm researched by Rao Yan team can analyze the real-time video stream to track the movements of each student and teacher. When abnormal behaviors are found, such as beatings, the system will send the clipped video to the management of the kindergarten. Personnel, government regulators or parents will also issue an alert.
The research team said that some of the current AI+ security surveillance systems are designed for adults, so there are a lot of problems when applying them to kindergartens to monitor the behavior of teachers and children, because children are very different from adults in their size and behavioral patterns. . Rao's team used a large number of surveillance videos collected by kindergartens and preschools as training samples to develop new machine learning algorithms. It did not pre-set the correctness of behaviors and was completely judged by the system.
After continuous training and data updates, the system learned to properly assess the monitoring content, and the entire project does not require human intervention. At present, many research institutions have shifted the focus and resources of research to solving the problem of preventing child abuse, but machine learning needs a lot of data support to improve the accuracy of its identification, which will be one of the problems faced by researchers. . But with more challenges, we also need a system that can protect children 24 hours a day, 7 days a year, AI is the best choice.
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