Nowadays, the development level of the Internet of Things (IoT) and related technologies is getting higher and higher, and the development speed is getting faster and faster, and its data management is becoming more and more important. How to optimize the calculation in its communication data will be a technical problem that needs to be broken through urgently. Artificial intelligence (AI) is a high-tech that has developed rapidly in recent years. It can simulate the human brain to perform some complicated tasks, and can also combine various recognition technologies to identify various items. Using AI can make IoT communication more efficient. Edge computing (EC) is a more efficient algorithm developed on the basis of cloud computing (CC), which can effectively reduce the computing process of the device, thereby reducing the power consumption of the device and improving the computing speed. This paper aims to study the management of IoT data by combining AI and EC technology, so as to further improve the efficiency of personnel communication in communication, improve the speed of logistics, and ensure the safety of logistics. This paper proposes a CNN neural network model, which combines EC to optimize the data management of IoT communication technology, and conducts simulation tests from the aspects of power consumption, queue average and overall performance. The final results show that the overall power consumption of the optimization algorithm in this paper is about 15W lower than that of CC, and about 18W lower than that of traditional EC, and the average queue value is the smallest. And the evolutionary EC proposed in this study has the best optimization effect, and its final objective function value is about 70 lower than CC and about 30 lower than traditional EC. Finally, the algorithm proposed in this study has advantages in queue value and power consumption, and the overall performance is also significantly improved.

Xiaoyu Liu. Evolutionary Algorithm of Optimization Technology in IoT Data Management Communication Based on Artificial Intelligence and Edge Computing. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 4: 75-85. https://doi.org/10.25236/AJCIS.2025.080409.

[1] Mckeithan P. Drying with IoT, cloud-based data management[J]. Food Pacific manufacturing journal, 2019, 19(3):28-30.

[2] Wan S, Lu J, Fan P, et al. Toward Big Data Processing in IoT: Path Planning and Resource Management of UAV Base Stations in Mobile-Edge Computing System[J]. IEEE Internet of Things Journal, 2020, 7(7):5995-6009. 

[3] Sung S H. Key Management for Secure Internet of Things(IoT) Data in Cloud Computing[J]. Journal of the Korea Institute of Information Security and Cryptology, 2017, 27(2):353-360.

[4] Sean, Dessureault. Rethinking Fleet and Personnel Management in the Era of IoT, Big Data, Gamification, and Low-Cost Tablet Technology[J]. Mining, Metallurgy & Exploration, 2019, 36(4):591–596.

[5] Naas M I, Lemarchand L, Raipin P, et al. IoT Data Replication and Consistency Management in Fog Computing[J]. Journal of Grid Computing, 2021, 19(3):1-25.

[6] Al-Ali A R, Zualkernan I A, Rashid M, et al. A smart home energy management system using IoT and big data analytics approach[J]. IEEE Transactions on Consumer Electronics, 2018, 63(4):426-434.

[7] Mckeithan P. Drying with IIOT And Cloud-Based Data Management[J]. Process Heating, 2018, 25(10):27-32.

[8] Sood S K, Sandhu R, Singla K, et al. IoT, big data and HPC based smart flood management framework[J]. Sustainable Computing: Informatics and Systems, 2017, 20(DEC.):102-117.

[9] Diene B, Rodrigues J, Diallo O, et al. Data management techniques for Internet of Things[J]. Mechanical systems and signal processing, 2020, 138(Apr.):106564.1-106564.19.

[10] Terroso-Saenz F, A González-Vidal, AP Ramallo-González, et al. An open IoT platform for the management and analysis of energy data[J]. Future generation computer systems, 2019, 92(MAR.):1066-1079.

[11] A K D, A S S, A E G M P, et al. Modular and generic IoT management on the cloud[J]. Future Generation Computer Systems, 2018, 78(1):369-378.

[12] Jun Hu, Ruan Yuxuan, et al. A Life Cycle Framework of Green IoT-Based Agriculture and Its Finance, Operation, and Management Issues[J]. Communications Magazine, IEEE, 2019, 57(3):90-96. 

[13] Wang G, Zhang X, Gao Y, Yee A L, & Wang X. The Use of an Internet of Things Data Management System Using Data Mining Association Algorithm in an E-Commerce Platform [J]. Journal of Organizational and End User Computing, 2023, 35(3): 1-19.