In the present scenario, healthcare has made significant progress with the
assistance of smart devices involving effective sensors and Internet of Things devices.
In context to this, the combination of IoT and cloud architectures are rigorously
exploited in order to process the large amount of data that would be generated by the
wearable sensor networks in near real-time applications by making use of Artificial
Intelligence supporting smart healthcare systems. In the current scenario of
globalization, in addition to the increased facilities, a wide variety of other challenges
are worked upon for providing quality and efficient healthcare benefits and facilities by
making use of cost-effective instruments and world class technologies.
An important factor for the physical and mental health of a human being, the
performance throughout the day as well as safety is the sleep quality. Effective quality
of sleep can help avoid the risk of mental depression and chronic diseases. Sleep
promotes the brain to actively get associated with the activity that is being performed
and helps in preventing various accidents that might be caused due to falling asleep.
For the analysis of the sleep quality, a continuous monitoring system is necessary
which generates effective results. With the aid of rapid improvisation of mobile and
sensor technology as well as the emerging trends of Internet of things technology, there
is a good opportunity of development of a reliable and effective sleep quality
monitoring system. This chapter effectively describes the background and applicability
of Internet of things for such systems involved in sleep monitoring. The study begins
with the review of the quality of sleep, the importance related to the monitoring of
sleep quality, the employability of Internet of things in this and its relevant field, as
well as the open issues and challenges in this and its related fields.
The IoT technology supports the preamble which would promote a cost effective and
consistent system in order to monitor the quality of sleep-in individuals. There are
several existing systems for the same purpose which involves a large amount of cost
and are cumbersome to implement. To overcome the same issue, the chapter narrates
an inventive system for monitoring and analyzing sleep patterns by making use of effective parameters. In this domain, a combination of clinical medicine, bioengineering,
neuroscience, epidemiology, mHealth, Computer Science, as well as Human Computer
interactio,n in order to approach the challenge of digitization of sleep from a
multidisciplinary perspective. This chapter describes the state of art technologies
involved in sleep monitoring and discusses the challenges and opportunities involved
from the initial step of acquiring the data to the applicability of the acquired data based
on the consumer level and clinical settings.
Keywords: Sleeping disorder, IoT in healthcare, Sensor technology, AI in healthcare, etc.
