This study explored the multidiscipline domain of the Wireless Sensor Network (WSN) and Ambient Intelligence (AmI) in addressing the problem of the comfort of a living space. This thesis addresses the potential for embedding an intelligent engine into WSN and the aggregation of multiple comfort factors in a living space. The four most important comfort factors for humans are taken into account. These are thermal comfort, visual comfort, indoor air comfort and acoustical comfort.

This thesis introduces a WSN based embedded intelligent system architecture and a system framework for a living space’s comfort level. Human Comfort Ambient Intelligence System (HCAmI) architecture is presented. The HCAmI key component encompasses a flexible generic distributed fuzzy engine embedded within WSN nodes. The engine serves as a key knowledge component in solving specific human comfort requirements.

With the proliferation of pervasive computing, there is an increasing demand for the inclusion of WSN in wider areas such as buildings, living space, system automation and much more. Focusing on buildings and living space alone, multitudinous studies have been made of environmental comfort for occupants. A smart environment and low energy homes are amongst the driving forces behind this research. Also, WSN research has been progressing well and expanding into various aspects of life such as support of the elderly, environmental senor, security and much more. Unfortunately, separate studies have been conducted in their own discipline focusing on specific issues and challenges. Little attention has been paid to putting it together under one roof. Lack of interdisciplinary research inspired this effort to unite these unconnected research domains. This has acted as the key motivational catalyst. The motivation behind combining these effects brings us to the specific issue of the human comfort realm that prompted this study. Human comfort deals with providing a comfortable and healthy place for people to live. Hence, in a living space, other than good design and construction, it is essential to monitor and maintain the modifiable environment such as temperature, lighting, humidity, noise, air quality and psychological factors. Functional environmental comfort system adaptability and the WSN system determination to solve the problem is a fascinating issue that certainly warranted further investigation.

The HCAmI concept was designed and implemented based on a knowledge based architecture and framework. This approach addressed the component level first, catering for the four key human comfort factors. The system level design was then looked at. Each individual component was subjected to simulated and real sensor data and tested against a corresponding model built using appropriate tools such as the MATLAB Simulink and Sun SPOT Solarium WSN simulator. The HCAmI System was used to collect raw data from 20/04/2010 to 26/08/2010 (four months of data) in the SeNSe Laboratory, School of Engineering. A short snapshot of the collected data (from 08:00am 25/08/2010 to 11:40am 26/08/2010) is presented as a case study.

The main achievement / contribution of this thesis is a distributed fuzzy logic based wireless sensor node in the human comfort realm. The framework, architecture and development of an integrated human comfort concept could be embedded in a wireless sensor network environment. The modular architecture and framework presented here highlights the flexibility and integrated approach of the design. The knowledge component of each comfort area can be changed easily and adding or removing comfort components is catered for as well.

Overall, this thesis adds to the WSN body of knowledge in an embedded distributed generic fuzzy engine, thermal comfort engine, spatial sensing engine, human comfort index engine, application layer communication protocol and specific external sensor driver development and interface for Sun SPOT WSN.