AI artificial intelligence algorithm+data analysis platform for fall behavior recognition algorithm

Based on ToF depth data, the AI algorithm expert model data deep learning network can complete the accurate recognition of human postures such as falling, sitting, lying and walking. Intelligent ai behavior recognition monitoring can monitor the abnormal behavior of personnel online, deeply analyze the obtained video information according to the AI behavior detection algorithm, and trigger alarm information immediately when the behavior of personnel does not meet the requirements of the rules. Automatic recognition of employees’ actions and behaviors in relevant work areas can realize fatigue recognition and departure recognition in actual scenes.

Different from wearable monitoring equipment and camera monitoring equipment, the company’s smart pension facilities provide non-touch monitoring for the elderly, which is more convenient to use without the elderly actively cooperating with wearing and charging the facilities regularly. The escalator personnel fall detection algorithm can accurately identify the behaviors of luggage case, trolleys, strollers and their personnel on the escalator, such as falling, queue density, retrograde, etc., and help managers find dangerous situations at the first time. The development of sensors makes objects have touch, smell, vision, taste and hearing similar to human beings, and makes objects come alive, which is an important means for intelligent products to interact with the outside world.

Smart power series algorithms realize intelligent monitoring, real-time analysis and hidden danger alarm for personnel unsafe behaviors, environmental risks, facilities and other parameters, and create an innovative mode of power safety production. Equipped with edge gateway box, embedded with AI Eye-in-the-Eye algorithm, it can also provide early warning information for intelligent and diverse emergencies, such as campus personnel gathering, personnel falling identification, dangerous area intrusion identification, high climbing identification, etc., and protect students’ personal safety in school.

Analyze people’s numerous behaviors and combine them with relevant fixed scenes to obtain user data analysis, such as decomposing the actual operation links of workers, establishing standardized data rules in terms of time and action standards, setting up multi-scene coverage video surveillance system at the entrance and exit of escalators and taking the escalator area, and analyzing the artificial intelligence algorithm with "smart brain". It can quickly and accurately detect violations such as passengers falling down, the escalator on the stroller, the detention at the entrance and exit of the escalator, passengers retrograde, and the body reaching out of the escalator, and prevent them as early as possible by means of voice broadcast and sending early warning information to the management unit, effectively preventing accidents caused by people’s unsafe hidden dangers.

The recognition technology of body movement behavior in artificial intelligence image processing algorithm also plays an important role in intelligent monitoring. In the process of visual tracking, the target tracking is realized according to the correlation algorithm of adjacent frames or through the global correlation algorithm of quality inspection of all frames. Real-time tracking of body movements by video has high efficiency and low cost.

Personal behavior analysis mainly includes human face recognition, staff behavior recognition, range intrusion detection, inspection of items left behind, crowd gathering recognition, intelligent tracking and so on. Relying on the sensor built in the helmet and the field camera, it can automatically identify the behavior of people falling in the construction site, rescue them as early as possible, improve the effect of manual supervision and ensure life safety. Personnel fall to the identification alarm system. The personnel fall detection system reduces the risk of on-site personnel monitoring and improves management efficiency.

The fall detection system effectively remedies the shortcomings of traditional methods and technologies, improves the effect of manual supervision and ensures life safety. Fall into the detection and identification system for humanized care and intelligent operation management, reducing costs, reducing risks and improving management efficiency for the elderly. The identification of AI video content is mainly aimed at the automatic identification, classification and prediction of the behavior of the target characters in the picture. According to the motion information captured by the camera, the human posture and motion trajectory are calculated according to the information data by the algorithm.