Intelligent Management Systems for Energy Efficiency in Buildings

Abstract

In recent years, reduction of energy consumption in buildings has increasingly gained interest among researchers mainly due to practical reasons, such as economic advantages and long-term environmental sustainability. Many solutions have been proposed in the literature to address this important issue from complementary perspectives, which are often hard to capture in a comprehensive manner. This survey article aims at providing a structured and unifying treatment of the existing literature on intelligent energy management systems in buildings, with a distinct focus on available architectures and methodology supporting a vision transcending the well-established smart home vision, in favor of the novel Ambient Intelligence paradigm. Our exposition will cover the main architectural components of such systems, beginning with the basic sensory infrastructure, moving on to the data processing engine where energy-saving strategies may be enacted, to the user interaction interface subsystem, and finally to the actuation infrastructure necessary to transfer the planned modifications to the environment. For each component, we will analyze different solutions, and we will provide qualitative comparisons, also highlighting the impact that a single design choice can have on the rest of the system.

Human Activity Recognition Process Using 3-D Posture Data

“…The activity recognition technique discussed here was developed as part of an AmI system [32] designed to perform timely and ubiquitous monitoring of a complex of buildings to optimize energy consumption [33]. From a logical point of view, the reference model of the AmI system is composed of three layers: the sensing layer, responsible for monitoring and controlling the environment by means of heterogeneous sensors and actuators [34]; the middleware layer, which provides a standard interface between physical sensors and AmI algorithms; the intelligent layer, which implements the AmI functionalities and produces the necessary actions to adapt the environment to the user requirements [35].…”

“…The office is equipped with wireless and wired sensor nodes, which monitor the environment conditions and the status of the actuators, respectively [32]. For example, RFID readers are installed close to each office door providing information about the presence of a particular user, while software sensors are installed to detect the users' activities on their workstations.…”

Programming distributed applications with symbolic reasoning on WSNs

“…Fuzzy rules to evaluate the agreement with the user are described in Table II. defuzzified to obtain a crisp output representing the agreement with the user. The process is based on the mechanism of implicit feedbacks, as described in [12] and is shown in Fig. 6.…”

EPDL: Supporting Context-Based Energy Control Policy Design in IoT-Enabled Smart Buildings: Programing the Physical World with EPDL

“…Substantial works have been done for improving energy efficiency in buildings [10]. Most of these solutions focused on designing controllers for an individual device or a sub-system such as HVAC and lighting systems.…”