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Internet of Things has had a tremendous effect in several fields, including the healthcare sector, to enhance network operation and users' quality of experience. In healthcare applications, people with cognitive, mental, and physical impairment rely on some form of assistive mobility device for their mobility needs and a better quality of life. The traditional wheelchairs are effective for physical impairments but poorly suited for individuals with a combination of physical and cognitive or perceptual impairments. To accommodate users with cognitive impairment, several researchers have used technologies originally developed for mobile robots to create smart mobility devices. With this significant interest, real-time autonomous navigation for the healthcare sector still requires more attention. This paper presents a review of the different existing literature on the internet of things frameworks and multi-sensor fusion techniques for assistive mobility devices (smart wheelchair). An Internet of things framework that takes into consideration scalability and security is proposed. A multi-sensor fusion pipeline for accurate localization and monitoring of assistive mobility devices for navigation purposes is also proposed.

З використанням методу Бокса-Вілсона (МБВ) проведено оптимізацію виходу олії дерева ші, екстра- гованого в реакторі з гладкими стінками, обладнаному імпе- лером, внаслідок зміни часу, температури та швидкості пере- мішування. Для досліджень застосовували гвинтовий імпелер, встановлений на швидкісному змішувачі Tecmix TM 1100. Для розроблення та оптимізації змінних процесу використана програма Minitab 16.1. Встановлено, що температура та швидкість мають значний вплив на вихід з p-значеннями 0,001 і0,002, відповідно. Значення виходу олії відповідно до графіку залишків показують, що прийнята модель є ефективною, оскільки експериментальні та прогнозовані значення виходу дуже близькі. Доведено адекватність моделі. The yield of Shea butter extracted in an unbaffled vessel equipped with an impeller was optimized by varying kneading time, kneading temperature and kneading speed using response surface method (RSM). Helical shaped impeller was mounted on a variable speed Tecmix TM 1100 kneader to knead the Shea paste. Minitab 16.1 software was used for the design and optimization of the process variables. The study indicated that the temperature and speed were highly significant on Shea butter oil yield with p-values of 0.001 and 0.002, respectively. The residual plots of the yield show that the adopted model was efficient because the experimental and the predicted yields for the extraction are very close. It was concluded that the model to be adequate.