Monitoramento e análise contínuos de variáveis diversas usando redes de sensores e recursos de business intelligence como suporte para green data centers

Abstract

Continuous monitoring and analysis of several variables using sensor networks and business intelligence as a support for green data centers ABSTRACT Data Centers are large energy consumers in the areas of Information and Communications Technology, where it is estimated that the equivalent of one-third of the energy consumption of the servers is spent on cooling systems to control the temperature of the equipment. In addition, airconditioning systems are essential to maintain proper thermal conditions, avoiding significant losses, besides keeping an homogeneous air distribution with energy efficiency. In order to evaluate their performance, it becomes demanding to continuously monitor certain variables, generating a historical basis that provides data analysis, identifying the environmental quality, the efficiency and the system operation pattern. Aiming this solution, here is proposed the development of an environmental and power consumption data analysis module in Data Centers, using Business Intelligence features, providing support to managers in the definition of strategies for sustainable operation of airconditioning systems. This module should be integrated into the system for secure and remote monitoring of the indoor environmental quality, operating since 2009 at Engineering School of University of São Paulo. It continuously monitors temperature, relative humidity, energy quality and consumption of the fan coils and chiller, in two airconditioned classrooms. This information is stored on a web server, generating history data and enabling remote access of users through an interface containing numerous features. The existing database will be used in the testing and validation of the proposed module that, integrated into the monitoring system, will bring benefit through reports and analytic charts. Data Center managers will be able to perform a quality control of the indoor environment with greater accuracy, adopting strategies of sustainable operation, facilitating risk identification and decreasing the possibility of accidents and maintenance costs. This solution will be fully aligned to the concept of Green Data Centers.