Information Extraction and Data Planning of Smart City Based on Internet of Things

Abstract

In order to solve the problem of slow resource scheduling in the process of smart city management, the author proposes a smart city information extraction and data planning system based on the Internet of Things. IoT requires different technologies for analysis for different data types. Managers use different IoT applications to analyze data from different devices and integrate relevant data for possible machine failure or emergency in smart home applications. Situation is predicted. The system includes a cloud platform intelligence center, uses the cloud management module to monitor various hardware devices, constructs the cloud computing resource scheduling objective function, uses the cultural particle swarm algorithm to solve the objective function, and obtains the cloud computing resource scheduling scheme. The experimental results show that the overall utilization rate of the system is the best, close to 100%. Conclusion. The system can realize the effective management of the smart city and monitor the city situation in real time. When implementing resource scheduling, the task completion time is short, the system utilization rate is high, and the resources can be maximized.