Behavior identification model training method and device based on mobile terminal multi-sensor

Abstract

The invention provides a behavior identification model training method and device based on mobile terminal multi-sensor. The method comprises the following steps: step one, collecting original data ofmultiple sensors on a mobile terminal according to the preset sampling frequency, and classifying all original data according to behavior modes of the collected objects, thereby obtaining sampling data sets of different behavior modes; step two, comparing the original data of each sensor at the adjacent sampling moment for the sampling data set of each behavior mode, and determining multiple groups of feature vectors of each behavior mode; and step three, performing probability statistics on multiple groups of feature vectors of each behavior mode by adopting improved Markov chain assumptionor Naive Bayes classifier, and taking the feature vector with the highest probability in each behavior mode as the behavior identification vector of the behavior mode. The utilization efficiency of the data is improved, the complex degree of the identification process is reduced, the identified behavior content is more specific and close to the life, the frequency of occurrence is high, and the application significance is strong.

Description

technical field [0001] The invention relates to the technical field of data analysis, in particular to a method and device for training a behavior recognition model based on multiple sensors of a mobile terminal. Background technique [0002] In earlier studies, researchers placed special motion sensors on different body parts of the participants, such as waists and wrists, to store behavioral information data and convert them for analysis and identification. Great impact, unable to carry out normal work and life. Therefore, the above research methods cannot provide a long-term effective solution for activity monitoring or prediction. Subsequently, the continuous development of cameras has made video recording an important means in this field. Researchers use cameras to record the behavior of the observed person, and can record detailed parts of the behavior data according to the needs. This method is similar to obtaining data from sensors attached to the body. Compared wi...

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Problems solved by technology

[0004] However, in the current research on behavior recognition using mobile phone sensor data, most of the research uses a small number of sensors, a single data type, and the identifiable behavior content is simple and the algorithm is difficult to implement. The feasibility needs to be improved.

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