数据中心（DC）正变得越来越重要。因此，对DCs的高效、可靠运行和管理提出了更高的要求。传统的DCs分别运行信息和通信技术（ICT）和设施管理（FM）系统，这可能导致管理效率低下。如今，DCs一直专注于数据中心基础设施管理（DCIM）系统，在该系统中，ICT设备、电力设备以及其他供暖、通风和空调（HVAC）设备可以以集成方式进行管理。在本文中，我们提出了一种设计机架和ICT布局的方法，作为使用DCIM和机器学习（ML）实现适当温度管理和节能效果的一个示例。 在此基础上，利用机器学习方法建立了环境变化后的温度能量预测模型，并给出了验证结果和验证室的有效性。引用:2019年冬季会议，佐治亚州亚特兰大，会议论文

Data centers (DCs) are becoming increasingly important. Accordingly, highly efficient and reliable operation and management of DCs have been required. Conventional DCs operate information and communication technology (ICT) and facility management (FM) systems separately, which could lead to inefficient management. Nowadays, DCs have been focusing on the data center infrastructure management (DCIM) system, in which ICT equipment, power equipment, and other heating, ventilation, and air conditioning (HVAC) devices can be managed in an integrated manner. In this paper, we propose a method of designing rack and ICT placement as an example of initiatives that realize proper temperature management and energy saving effects using DCIM and machine learning (ML). Then models for predicting the temperature energy after enviroment chages by using machine learning are developed, and the results of verification and effectiveness in the verification room are reported.