Smart home devices are rapidly growing in popularity, and it’s easy to understand why. In our busy lives, convenience is paramount. And smart home environments provide a vast array of functionality that makes life easier on a daily basis. From devices that allow users to control lighting and thermostats from their smartphone to products that significantly improve home security, and even cooking machines that can be managed remotely, smart homes offer a multitude of ways to save money and increase convenience. As the development of smart home devices advances, it becomes necessary to find methods for the technology to adapt to users and the context in which they exist. The Internet of Things is based on human-computer interactions. By adhering to this fundamental IoT principle, smart home devices can evolve to process and learn from the data produced by appliances, sensors, and the human users of this technology. In other words, a smart home environment must adapt to the specific desires and routines of its inhabitants, allowing the technology to be personalized over time in response to a person’s actions. In many ways, the challenges associated with bringing these concepts to fruition is similar to the ongoing developments in smart cities, smart grids, and personalized wearables. This work requires the melding of many disciplines, including human-computer interaction, psychology, social sciences, and context awareness. Context data in a smart home can be derived from several sources, such as sensors in the house and its vicinity, power and water consumption meters, and smart city sensors that provide additional data, like outside temperature, the overall electrical power usage of the community, and pollution levels. Of course, accomplishing this task is a highly complex undertaking. The technology must be designed to be capable of adapting to a wide range of users and contextual situations. Furthermore, it’s very challenging to separate the valuable data from the rest to tailor smart home devices effectively. However, by using machine learning approaches to extract useful information, the intricacies of creating user adaptive and context-aware smart home environments can be accomplished. And, without question, we all stand to benefit massively from these developments, with increased convenience, better security, and more money left in our pockets. Written by Igor Ilunin, head of IoT at DataArt .
