۱- Introduction

۲- Related works

۳- ICA-BEMS architecture and features

۴- The solution scheduling

۵- ICA-BEMS implementation

۶- Conclusions

References

Abstract

Context-awareness is an important research area. Many energy efficiency applications of ubiquitous computing need to access some related contexts to provide the best and adequate energy saving services at the right time and at the right place. One of the big challenges is the difficulty and the complexity to make systems identify and understand situations in the building business, especially in complex situations to provide adequate energy-saving services for each of which. This issue is divided into two parts: On one hand, the smart building and its environment must be modeled in a way that provides context-awareness. On the other hand is the how to effectively exploit this context-awareness to reduce energy consumption and increase the user comfort. In this paper, we propose an intelligent context-awareness Building Energy Management System (ICA-BEMS). ICA-BEMS uses hybrid energy-saving techniques based on a Smart Context-Awareness Management (Smart-CAM). Smart-CAM uses smart building ontology to organize smart building knowledge and utilizes a new context-awareness mechanism to provide contextual information. The former exploits the contextual information in reasoning to reduce the building energy consumption, promoting users behavioral change and maximizing the user’s comfort to bring about a better energy efficiency policy. To evaluate our system, we have developed a smart building simulator (Open-SBS) which simulates smart building comportments and human behaviors. We have created various scenarios of daily life in the smart building simulator. We have tested our ICA-BEMS effect on energy consumption having a positive result. Energy consumption has been decreased by 40% of total energy consumption.

Introduction

In the ubiquitous computing environment, every day technology produces new devices, services, and systems to make our daily life easier and comfortable. The building is one of the most important places in people’s everyday life. 90% of people spend most of their time in buildings [1]. Smart building is an important research area of ubiquitous computing. Knowing that global primary energy demand will grow by 31% between 2012 and 2035 and energyrelated CO2 emissions increase by 18.1% [2]. The commercial and residential building accounts for about 20% of the world’s total energy consumption [3]. The energy demand in this sector grows faster than other areas throughout some projections [3]. Energy efficiency has significant gains like saving money and good impact on the environment. Therefore several works have been conducted to saving energy [4–۸]. Such as the ones made by the major Information and Communication Technology (ICT) enterprises, as IBM, MONI, Control4, and Samsung who have created their own Building Management System (BMS). In our case, we are interested in BEMS (Building Energy Management System). There are two types of BEMS: Actives and Passives. The passive methods collect environment data, devices information and past energy use in a smart building. This information is used to provide new decisions to make the best saving energy policy in the future. These methods are easy to apply. Moreover, they are faster, cheaper and better for small buildings. Active methods operate at a level of intelligence and automation. BEMS have sensors, meters, and devices to control building in real-time to reduce energy consumption.