In the age of rapid technological advancement, many telecommunication applications are being integrated into our lives, including smart phones and Internet of Things (IoT). Smart buildings (and houses) use these technologies to reduce energy consumption and increase safety. The need for these buildings is growing as urbanization continues and resources dwindle. According to a report by the United Nations, by 2050 66% of the world’s population will live in cities. This will cause the size and number of megacities to expand drastically in the near future. Complex communication networks, controls and other services will allow us to build smart cities to manage and improve the public’s quality of life. The necessity of smart buildings and, eventually, cities, has stimulated growth of sensor networks for these purposes. This thesis discusses the research on creating a smart transducer network architecture concept that uses Power over Ethernet (PoE) as a method for transferring data and power over a single medium, together with principles of decentralized and remote computing for data processing. The concept prototype had its power supplied by a Cisco Catalyst 4507R+E switch and utilized cloud computing to provide an easily scalable and adaptable architecture, able to easily adapt to a wide array of applications and fit the demands of new trends or integration into other systems. The set-up was tested on RaspberryPi and BeagleBone microcontroller boards as sensor hubs, and used DigitalOcean as the cloud computing service of choice. The server in this implementation acts as user interface, front end, and as the console unit back end. The architecture has demonstrated the feasibility of the concept of uniting PoE and IoT to create a flexible architecture. The system has also demonstrated fast communication times, below 200ms, in a cross-continental setting and the ability to provide fast processing times of under 1s. This shows particular promise for the use of the architecture within the context of green and smart housing equipped with a low-cost sensor network, where local power is partially provided via renewable energy harvesting, and the majority of short-range power transmission is DC-centered. ; Applied Science, Faculty of ; Electrical and Computer Engineering, Department of ; Graduate