HAUAR: Home Automation Using Action Recognition
This addresses home automation for users by removing human intervention, but it is incremental as it applies existing action recognition methods to a specific domain.
The paper tackled the problem of human-controlled home automation by proposing a system that uses action recognition to automate appliances based on detecting sitting, standing, lying, and empty rooms, achieving 90% accuracy in real-life tests.
Today, many of the home automation systems deployed are mostly controlled by humans. This control by humans restricts the automation of home appliances to an extent. Also, most of the deployed home automation systems use the Internet of Things technology to control the appliances. In this paper, we propose a system developed using action recognition to fully automate the home appliances. We recognize the three actions of a person (sitting, standing and lying) along with the recognition of an empty room. The accuracy of the system was 90% in the real-life test experiments. With this system, we remove the human intervention in home automation systems for controlling the home appliances and at the same time we ensure the data privacy and reduce the energy consumption by efficiently and optimally using home appliances.