# Intelligent Monitoring of Data Center Physical Infrastructure
## 4 Discussion  
The experimental results of the proposed RCM provide more precise information about the node which is the main cause of the events. From a large number of nodes, the number was minimized by identifying the main cause of the event. Another advantage of the method lies in obtaining accurate information about the operation of an individual device by monitoring all the data center's technical devices. Rapid identification of data center failure is essential to ensuring high-quality service in terms of high availability. The disadvantage of the RCM is that most of the work needs to be done at the design stage in order to achieve a high degree of availability and reduce the data center's power consumption. The proposed method allows for the addition, removal, and replacement of power supplies, which should be conceived at the data center infrastructure design phase. The design of the software and the sensor system requires critical activities relating to the RCM, where it is necessary to identify all nodes for monitoring and all the parameters that are important for the efficient operation of the data center. With the RCM, most information about the condition of all devices and indirect information on how to reduce the energy consumption in data centers is gathered from the basic layer (power supplies, cooling systems, etc.). For example, if we look at servers, even when they are in sleep mode, they consume a lot of energy. Great savings can be achieved by changing these servers to standby mode when there is no need for their operation. If we use these and other measures, such as consolidation of the total workload to reduce the consumption of electricity in data centers, availability may be reduced. Therefore, a complex balance is needed between energy savings and high availability of the data center. Electricity consumption and heat valuation metrics play an important role in describing the reduction of electrical and thermal loads on the environment. A well-known metric is the power usage efficiency (PUE) measure, which shows the total energy consumption in the data center per unit of energy consumed by the IT system. In addition to the PUE measurement, other information is vital, such as the carbon utilization efficiency (CUE), the green energy coefficient (GEC), the energy reuse factor (ERF), and renewable energy or the recycling of waste heat in data centers [32; 50; 51]. Measurements of general energy efficiency were carried out where small data center efficiency in terms of energy and cooling was evaluated using 25 parameters over a period of six weeks during real-time operation. The measured data were then compared with the supply heat index (SHI), rack heat index (RHI), rack cooling index (RCI), rack temperature index (RTI), and PUE. The results of these comparisons demonstrated that server ceilings were over-cooled by more than 25% if the SHI and RHI were 16% and 74%, respectively [33; 51]. As a measure of improvement, there was a reduction in the cooling load. The next suggestion was that the data center heat load and the level of server cabinets should be evaluated at the same time, in order to more accurately analyze the overall operation of the cooling system. It is also important to ensure that the data center maintains an appropriate climate environment (humidity and temperature) to avoid compromising the reliability of computer equipment. In high humidity, water vapor condensation occurs on the computer equipment, and low humidity results in electrostatic discharges. The thermal management of the data center is also important in order to maintain lower temperatures where the data center equipment is located, as required by the standard specifying the lowest energy consumption. In general, the RCM improves the monitoring of data center operations and the effectiveness of the available data. The method allows objectivity by weighing evidence of alarm events that have already been reported in the past, regardless of the user's personal reactions.