Design And Implementation Of A Smart Community Based On The Internet Of Things

With the construction of urbanization,residents are demanding more and more safety,convenience and efficiency of community living.Therefore,the construction of intelligent communities has gradually gained attention and importance in recent years,and intelligent monitoring and intelligent parking are two important elements in the construction of intelligent communities.In this paper,an in-depth study of the monitoring system and underground parking path planning is presented in the context of the Wanjin Lingxiu project in Hohhot.The main content of the monitoring system research includes the optimization of surveillance camera arrangement,network topology optimization and the design of cell abnormal behavior warning system.First,in order to save cost and reduce the overlap of monitoring range,the optimization of monitoring camera arrangement method is achieved by the exhaustive method under the condition of satisfying the full coverage of cell monitoring with monitoring cost as the target function.Second,to address the problem that the traditional network topology is prone to video lag and system breakdown,we propose to optimize the traditional network topology with a decentralized unitary network topology.In order to improve the security of the community,the method of using HOG and LS-SVM in the monitoring system is proposed to warn the abnormal behavior of the community.The test results show that the intelligent monitoring system has high reliability and real-time performance,and can meet the needs of community intelligent monitoring system.In order to solve the problem of difficult parking in the community dedicated commercial parking spaces,to achieve the optimal path planning and guidance for commercial vehicle parking.This paper proposes a hybrid optimization algorithm combining ant colony optimization algorithm and particle optimization swarm algorithm based on raster graph method for modeling to apply to community underground parking lots to plan parking paths and guide car owners to park their cars quickly.The simulation results verify the superiority of the hybrid optimization algorithm in parking path planning through the simulation and algorithm comparison of different scenarios.