A smart university platform for building energy monitoring and savings

Abstract

This paper presents a novel, integrated platform for energy monitoring, management and savings in the context of a Smart University Building. Namely, the proposed Smart International Hellenic University (IHU) platform integrates an intelligent, rule-based agent that enforces savings, while a variety of applications offers user interaction with the system and the means for monitoring and management. The application layer is built over a common Web Service middleware, incorporating semantic interoperability. Monitoring applications visualize raw and aggregated sensor readings, such as building energy disaggregation, environmental measurements and data center efficiency. Extensive monitoring capabilities allow users to take immediate action and devise policies towards energy-savings. Such policies are, then, autonomously enforced by the intelligent, hybrid agent, which is capable of both deliberative (long-term) and reactive (immediate) actions. The agent is also integrated with the Open-ADR standard for receiving provider instructions in future Smart Grids. A pilot deployment of the agent with expert-formulated policies at the IHU premises, has managed to reduce the total daily consumption of a typical university office by approximately 16%.

Energy Consumption Model for Green Computing

“…The metric that models the efficiency of telecommunications equipment (M T and M T , IT) is presented in the following equation [2,7]:…”

“…In the equation, k is the number of routers in the GNS and bi is the total number of bits that leave the same router during the evaluation window [2,7]. E IN is the total energy consumed by the GNS system during the evaluation window.…”

Artificial intelligence and ambient intelligence

“…In this work, the authors present an automatic approach to coping with conflicts in the OWL ontologies that represent the agents' knowledge base. A different work by Stavropoulos et al [63] focuses on monitoring and saving energy in the context of a smart university building. Rule-based agents are integrated into the middleware that monitors the use of energy in the International Hellenic University.…”

Indoor air quality prediction systems for smart environments: A systematic review

“…The concept of smart homes, smart factories, smart cities and smart health systems are gaining immense popularity around the world. Moreover, smart environments are mainly influenced by the combination of AI and IoT [43,110,123]. On the one hand, traditional threshold-triggered solutions can provide instant updates about critical IAQ levels.…”

“…The research communities from the past years are exploring the potential of AI to design intelligent environments where building occupants get automatic, real-time updates about changing environmental conditions [24,95,135]. This vision has taken them to the concept of ambient intelligence that further contribute to the development of smart environments for healthy living [30,110,111]. Several researchers in the past have proposed efficient prediction systems for IAQ to improve public health and well-being [70,109,115,139,140].…”