RETRACTED ARTICLE: A complementary automation control for Internet of Things-based smart home assistance for elder adults

With the recent development and applications of the Internet of Things (IoT) paradigm, smart home concepts are prominent in providing reliable monitoring of people through remote access. The information and communication technologies are harmonized for providing comfortable assistance for elderly and home-cared peoples. The reliability of such smart home-based IoT networks is defaced due to multiple concurrencies in automation control systems. This concurrency issue is resolved by designing a novel pivotal complementary automation control model (PCACM) using a machine learning paradigm. This model first observes the changes and requirements in the smart home environment. The decision tree-based learning paradigm constructs non-congruent solutions for providing different levels of concurrency. By identifying the fixed and varying control routines, the tree is constructed with the possible decisions. If the control requirement exceeds the available solutions, then complementary actions are assimilated, and the tree is modified. Such a decision-making process can confront older adults’ ad hoc requirements, regardless of time and benchmarked assistance. The proposed model’s performance is verified using the metrics assistance attainment, delay, control failures and overhead.