The rapid development of Internet technology in the new era has led to the prosperous development of the e-commerce industry, and more and more traditional retail enterprises are transforming into e-commerce enterprises in line with the development of the times to survive. Based on the relevant financial risk management theories, this paper designs an e-commerce investment risk management system for small and medium-sized enterprises based on the 5G intelligent sensor network, identify the financial risks arising from the e-commerce model, and takes appropriate countermeasures to manage the identified risks. For the optimal coverage problem of homogeneous terminals in the subnetwork of a smart sensing network, this paper introduces the concept of area coverage contribution, transforms the problem of selecting the optimal coverage subset in a large area into the problem of selecting the substrate particles, and organically combines the particle swarm algorithm in the bionic algorithm to consider the network survival period, area sensing coverage, and iteration cost for the hierarchical distributed large-scale IoT architecture. A minimum coverage subset dormancy scheduling algorithm based on homogeneous terminals is proposed. The simulation results are compared with the greedy algorithm and the multioptimized target task assignment algorithm, and it is demonstrated that this algorithm can consider multiple optimization objectives such as energy balance, scheduling cycle, timeout rate, network survival cycle, and system reliability and perform well in the case of large-scale deployment. Finally, an appropriate financial risk evaluation model is constructed to objectively evaluate the identified financial risks, and targeted financial risk control measures and suggestions are proposed based on four aspects: financing, investment, operation, and others.
