Collaborative Hotspot Data Collection with Drones and 5G Edge Computing in Smart City

Abstract

The construction and governance of smart cities require the collaboration of different systems and different regions. How to realize the monitoring of abnormal hot spots through the collaboration of subsystems with limited resources is related to the stability and efficiency of the city. This work constructs a hot data processing framework for drones and 5G edge computing infrastructure, as well as an Ensemble Multi-Objective Cooperative Learning (EMOCL) method to process three different types of hot data. The data collection phase combines set operations with the 0-1 multi-knapsack model, and the cooperative learning phase realizes the degree of cooperation control while retaining the ability of independent optimization of the subsystem. Finally, the advantages of the framework are verified by hot data coverage and collaborative processing efficiency, resource use cost and balance.