Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research

An ARTMAP-incorporated Multi-Agent System for Building Intelligent Heat Management

This paper presents an ARTMAP-incorporated multi-agent system (MAS) for building heat management, which aims to maintain the desired space temperature defined by the building occupants (thermal comfort management) and improve energy efficiency by intelligently controlling the energy flow and usage in the building (building energy control). Existing MAS typically uses rule-based approaches to describe the behaviours and the processes of its agents, and the rules are fixed. The incorporation of artificial neural network (ANN) techniques to the agents can provide for the required online learning and adaptation capabilities. A three-layer MAS is proposed for building heat management and ARTMAP is incorporated into the agents so as to facilitate online learning and adaptation capabilities. Simulation results demonstrate that ARTMAP incorporated MAS provides better (automated) energy control and thermal comfort management for a building environment in comparison to its existing rule-based MAS approach

Control of HVAC system comfort by sampling

The sampling of the users comfort, allows observing and predicting the level of comfort on the HVAC (heating, ventilation, and air conditioning) systems. The development of online sampling systems assists in the recognition of the behavior patterns that occur in the offices. This paper presents a user-friendly tool designed and developed in order to make easier knowledge extraction and representation to make possible decisions about which demand that must prevail, the user comfort or saving into a central system. This decision may depend on the occupation and feeling of comfort of its occupants. Some studies have put neutral thermal conditions outside the ranges of comfort of the ASHRAE standard. The actual rules of the HVAC systems are based on studies carried out on specific populations in a specific space, which are not valid in certain situations. This is a dynamic idea of the comfort based in real data. The methodology used provides important and useful information to be able to select the comfort set-point of the rooms of a central heating system without the need to use fixed values based on programmed time schedules or any other methodology. The response to comfort in an area of a building throughout the day can be seen in this study. The users were assessed using a standard set of key questions in order to measure the level of satisfaction with environmental factors, thanks to a questionnaire of imprecise answers. We seek an improvement in the building users, regardless of their particularities

Multi-agent collaboration for decision support in shared zones of intelligent buildings

In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented

Intelligent system for lighting control in smart cities

This paper presents an adaptive architecture that centralizes the control of public lighting and intelligent management to economize lighting and maintain maximum visual comfort in illuminated areas. To carry out this management, the architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA, and a Service Oriented Approach (SOA). It achieves optimization in terms of both energy consumption and cost by using a modular architecture, and is fully adaptable to current lighting systems. The architecture was successfully tested and validated and continues to be in development

Predicting episodes of non-conformant mobility in indoor environments

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ