Cloud for Smart Healthcare
With the widespread use of smartphones and
the explosion of sensors and connected devices, users are collecting an
unprecedented amount of data on their health. In addition, program sponsors
today can share aggregate program data with an ecosystem of partners that can
set goals, monitor, advise and influence the programs for better outcome. Cloud
based systems allow the statistical evaluation of user data obtained by health
monitoring sensors (e.g., wearable monitors such as FitBit devices or blood
pressure, temperature, pulse, weight, or activity monitors) which is vital for providing
many value added smart healthcare services. However, privacy remains a major
concern. US20150286800 illustrates a system that establishes trust by providing
the user full control over his data by specifying what parts of the data, how,
when and for how long is shared with a particular program sponsor or an
ecosystem partner that can improve the outcomes of the program.
US20150088538 illustrates another cloud based
smart health care system that provides various devices for tracking and
monitoring health statistics and behaviors including oral health, fitness,
heart health, bone health, salivary diagnostics and diabetes. Health statistics
and behaviors are tracked and monitored by various devices including toothbrush,
connected surface with sensors, salivary diagnostic system and breath analysis
system.
Cloud for Smart Home
Various methods of monitoring states of smart
home appliances and controlling functions or operations of the smart home appliances
have been suggested. A user can monitor states of home appliances or control
the home appliances through a network formed among the home appliances in smart
home environments. The user can also remotely monitor the states of the home
appliances or control the home appliances using a smartphone of the user. Such
monitoring and controlling may be preformed based on data, associated with
states and/or functions of the home appliances, generated by the home
appliances. However, a conventional home appliance management system may not
efficiently store, analyze, and process a large amount of data, associated with
the states and/or the functions of the home appliances, generated at every unit
time.
US20150134727 illustrates a cloud based system
for managing home appliances that may efficiently manage a large amount of data
generated by the home appliances. Data generated by the home appliances (metadata)
includes an identifier, a make, a model, a time, a location, a status and an event.
The cloud based home appliance management system determines the particular
interpretation instructions (define particular control rules for the home
appliances) that are associated with the particular ontology recognition of the
data.
Cloud for Connected Car
Smartphones along with the cloud computing
service can assist drivers with respect to improving driver safety. For
example, the cloud-based assistive technology can warn drivers upon lane
departures, impending collisions, and/or vehicles in blind-spots. US20150262486
(Microsoft) illustrates a technology by which driver safety technology such as
collision detection is implemented via smartphone sensors and the cloud service
that processes data received from vehicles associated with the smartphone. The
cloud service receives the trajectory-related data. The trajectory-related data
is used to predict collisions between vehicles and/or lane departures of
vehicles. To operate the service in real-time with low latency, driving areas are
divided into grids, e.g., based upon traffic density, having parallel grid
servers each responsible for only vehicles in or approaching its own grid, and
other parallel/distributed mechanisms of the cloud service. The grid servers
associated with the grids determine whether vehicles that are known to the grid
server to be in or approaching the associated individual grid are at risk of
collision based on information received at the cloud service from smartphones
related to the vehicles, and to output alert-related data for communication to the
vehicles that is at risk of collision.
©2015 TechIPm, LLC All Rights Reserved http://www.techipm.com/
No comments:
Post a Comment