Exploring Precise Services and Social Integration for Floating Population in the Digital Government Environment Driven by Intelligent Policing

Abstract

Based on the rapid development of digital government and intelligent policing technology, the management issue of floating population has become a key challenge in the city planning and the public service system. Based on intelligent policing and data-driven, combined with the existing digital governance structure, this study proposes the social integration model and adopts novel algorithms for precise service and resource allocation. Truly, the model uses clustering behavior analysis to real-time track floating population activity trajectory, and uses the prediction algorithm long short-term memory network LSTM to make predictions future behavior. This system based on decision tree analysis can meet the needs of the floating population, contribute to the public service supply of medical care, education and housing, and provide personalized and accurate services. Experimental results indicate demonstrates that the proposed model has a significant improvement compared with the traditional model in terms of social integration and optimization of floating population public service.