Chapter 9 - Integration and study of map matching algorithms in healthcare services for cognitive impaired person

Abstract

The use of different intelligent Internet of Things (IoTs) future innovations for machine learning has become fairly important in most practical applications these days owing to their high performance and low cost for various devices. Wearable cameras, actuators, the IoTs, and automation technologies are now developing the foundations for modern healthcare technologies such as pattern analysis and prognostic modeling. In the near future, smart assistive devices can allow cognitive impaired person, that is, elderly and disabled participants to interact in everyday activities, participate in friendly events, entertain, and socialize themselves while preserving their health and well-being. The involvement of health-related practices, which necessitates the use of communication and collaboration technology, complements those smart environments. Sophisticated networks and IoT systems are often used in these approaches to improve health and well-being. Intellectual disabilities are a category of conditions marked by reduced cognitive and adaptive functioning. They are also known as mental retardation or general intellectual disability. Mild (approximately 80%), moderate (14%), severe (approximately 4%), and extreme (approximately 2%) developmental disorders are the most prominent. The bulk of cases are associated with mild to moderate form of disorder. For individuals with mild to severe conditions in the early stages with intellectual disabilities, SCCA module is a form of orientation facility. In an advanced, serious, or drastic phase of life, the person is unable to use a mobile screen making orientation inevitable. The main characteristics of this type of LBS are that it is a continuous process. In LBS, augmented reality user interfaces were used to guide cognitively challenged individuals. It diminishes the amount of mental activity needed to comprehend the way to approach. A screen may appear to alert the user to wait as the system decides the best travel direction. The moving path must be fed into the speculative computational module to predict user errors and ensure proper travel direction. The trajectory data mining approach was applied and tested with the goal of completing the travel path as per the user preferences. The trajectory of a person with cognitive impairments is denoted as T from their log L. It is a set of GPS points with a fixed distance between them that does not exceed a certain threshold Th. The trajectory is written as T:p1→p2→···→pm, where, with pi∈P⊂L, (m>i≥1), and Th>pi+t·t>0. The term (|T|=m), and t are known as the number of samplings and the interval of the sampling point, respectively. The point structure P=p1, p2· · ·, pm are known as a GPS log, in which, each point pi ∈ P includes pi lng, pi lat, pi.t as longitude, latitude, and timestamp, respectively. Path W [W: e1→e2→···→en] is a connected street segment arrangement that begins at the vertex Vi and ends at the vertex Vj, where, 1≤k≤n, e1 start=Vi, en end=Vj, and ek end=ek+1 start.