Smart homes and smart objects: internet of things for energy-aware monitoring and controlling systems

Abstract

In recent years, the design and implementation of Home Automation Systems followed the spread of Internet of Things and its intent to make every home smart for end-users through Internet and Wireless connectivity. Ambient intelligence is an emerging discipline as well that aims to bring intelligence to environments making them sensitive to people through the use of embedded smart objects. Together, Automation Systems, Internet of Things and Ambient Intelligence make great interaction between people and the environments they live in possible. The enhancing of these interactions was one the main goals of this thesis whose intent was to improve the classic concept of Home Automation System through Internet Of Things philosophy. The first research objective was the design and implementation of a basic Internet of Things architecture that can be used for several Home Automation and Monitoring applications such as lighting, heating, conditioning or energy management. In particular, besides controlling features, the system can optimize energy consumptions by increasing awareness of users that have full control of their house and the possibility to save money and reduce the impact of energetic consumption on the earth, matching the new “green” motto requirements. According to IoT, innovative plug-and-play and ready-to-use smart devices were designed and implemented as part of this reactive automation system that offers a user-friendly web application and allows users to control and interact with different plans of their house in order to make life more comfortable and be aware of their energy consumptions. Control and awareness were two important key points for the first stage of research activity. The next challenge was to enhance IoT with intelligence and awareness by exploring various interactions between human beings and the environment they live in. The system was progressively enhanced evolving from a reactive system to a proactive system where the knowledge of human needs, in addition to the current environment status, constitute a new input for the system whose further objective is to find the right automations that can satisfy human needs in real-time. This advanced proactive system can sense and infer the user’s and the environment’s context and consequently decide autonomously how to affect the environment and actuate smart actions. It was experienced by many researchers that, for several reasons, some users might not appreciate these kinds of proactive actuations so, another challenge was the design of a system which is able to learn from user’s context and feedbacks history and, subsequently, to adapt itself to always up-do-date users’ expectations and keep the rules for triggering smart actuations constantly updated. The system was at a later time transformed into a “Inferactive” system. Another important scope of the research was the in-depth examination of the motivations for energy-efficient communications in wireless systems by highlighting emerging trends and identifying the challenges that need to be addressed to enable novel, scalable and energy-efficient wireless communications. One of the most important issues for researchers that must be addressed in designing communication protocols for wireless networks is how to save devices’ energy while meeting the needs of applications. For this reason, the architecture proposed was also enhanced at a communication level with energy-awareness in order to minimize energy consumption by communication devices, protocols, networks, end-user systems and data centers. To do this, some smart devices have been designed with multiple communication interfaces, such as RF and Wi-Fi, by using open-source technology such as Arduino. They have been analyzed under different working conditions and network topology. Communication parameters, data size and device status have been changed dynamically according to different scenarios and specific quality of service required, such as the speed of response, in order to find the best hardware and software configuration that offers the most benefits in terms of energy cost/quality ratio, lowest energy consumption and extended lifetime for battery-powered devices. The last challenge was to improve energy consumption of battery-powered smart devices provided with Wi-Fi that is commonly considered a very energy-expensive communication interface if compared to Bluetooth or ZigBee. Research focused on social IoT solutions for Home Automation Systems where devices are socially connected to Internet and can communicate through social applications like Facebook, Twitter or Google+ with a community of users that usually interact with that device itself. A fuzzy-based solution was proposed to classify the social community interaction with the system in order to implement an adaptive energy saving mode for social Wi-Fi devices according to users’ current context, behavior, habits and feedbacks. Test and performance evaluation regarding energy consumption and efficiency in real world scenario with real hardware devices were performed to prove the efficiency of the solution in terms of electricity consumption, battery lifetime, CPU utilization and increase of comfort and satisfaction levels for community users. The thesis is organized as follows. Chapters 1,2 and 3 contains the basics for a better understanding of the solutions proposed such as Internet of Things, Ambient Intelligence, Smart Homes and Smart Devices energy level issues. Chapter 4 describes the solution proposed, in particular, the system architecture and how the system evolved from reactive, to proactive and finally to “inferactive”. Chapter 5 examines how to deal with energy-aware communication and how Wi-Fi communication was improved in terms of energy consumption through social IoT awareness and fuzzy logic. In closing, Chapter 6 presents the test and the results achieved.