As we have understood for many
years & still by many people often think about Internet of Things (IoT) and
robotics technology as separate fields, these two niches seem to be growing
simultaneously as we find new ways to engineer each one. The IoT and robotics communities are coming
together to create The Internet of Robotic Things (IoRT). Yes this is the term
used by many in research field now a days, the IoRT is a concept in which
intelligent devices can monitor the events happening around them, fuse their
sensor data, make use of local and distributed intelligence to decide on
courses of action and then behave to manipulate or control objects in the
physical world. This is even more
impressive if we know that the Internet of Robotic Things, although being very
real, is still in its early days.
Similarities and Differences
Connected Devices: As most common
is the requirements of Data to be in and out at all times for all such devices
normally. The improvements are based on the data already collected & next
steps are programmed & evolved on these learnings.
Sensing capabilities: Both IoT
devices and robots depend on sensors to understand the environment around them,
quickly process data and determine how to respond. Robots are able to handle
anticipated situations, while most IoT applications can only handle
well-defined tasks.
Real Action: The main difference
between the IoT and the robotics community is that robots take real action and
are in the physical world. They do something. Focus has been shifting from the
cyber component of IoT to the physical aspect, and that’s where the efforts are
combining.
Now, let’s take a closer look at
the Internet of Robotic Things. The main difference with the Internet of Things
as we know it, is that the devices, the robots, take real action (and are) in
the physical world. In other words: your intelligent device “does” something.
Concept : The Internet of Robotic
Things (IoRT), where intelligent devices can monitor events, fuse sensor data
from a variety of sources, use local and distributed intelligence to determine
a best course of action, and then act to control or manipulate objects the
physical world, and in some cases while physically moving through that world.
Intelligence: The device (robot) is intelligent in the sense
that it has embedded monitoring (and sensing) capabilities and at the same time
can get sensor data from other sources which are fused for the ‘acting’ purpose
of the device.
A second ‘intelligent’ part is
that the device can leverage local and distributed “intelligence”. In other
words it can analyze the data from the events it monitors (which by definition
means a presence of edge computing or fog computing in many circumstance) and
has access to (analyzed) data.
Next steps / evolution : Finally, both prior components
serve the third one which consists of (autonomously) determining what action to
take and take that action, whereby an action can be the control or manipulation
of a physical object in the physical world. And, if its purpose is to do so and
it has been designed to be able to, the device or robot can also move in that
physical world. In this stage and looking at the cases we can also include
‘notifying’ or ‘alerting’, based upon the analysis of a ‘physical event’ to the
actions.
Let’s understand the connection
again, IoT and Robotics Tech Are Evolving Together So far, the robotics and IoT
communities have been driven by varying yet highly related objectives. IoT
focuses on supporting services for pervasive sensing, monitoring and tracking,
while the robotic communities focus on production action, interaction and
autonomous behavior. A strong value would be added by combining the two and
creating an Internet of Robotic Things.
The concept where sensor data
coming from a range of sources are fused, processed with local and distributed
intelligence and used to control and manipulate objects in the physical world
is how the term “Internet of Robotic Things” was created. A wider situational
awareness is given to robots from the IoT sensor and data analytics
technologies, which leads to better task execution.
3 way intelligence built in
- The robot can sense that it has embedded monitoring capabilities and can get sensor data from other sources.
- It can analyze data from the event it monitors, which means there’s edge computing involved. Edge computing is where data is processed and analyzed locally instead of in the cloud, and it eliminates the need to transmit a wealth of data to the cloud.
- because of the first two components, the robot can determine which action to take and then take that action. As a result, the robot can control or manipulate a physical object, and if it was designed to, it can move in the physical world. The bigger idea for now is collaborations between machine / machine and between man / machine. These interactions could move toward predictive maintenance and entirely new services.
Work Force Impact: Integrating
artificial intelligence into the workforce isn’t a brand new thing, but with
the rise in labor prices, manufacturers are trying to reduce costs without
cutting production. They can do so by putting robots in settings to work
closely with humans, which can either boost productivity with the same number
of workers or replace workers altogether.
Now, IoT applications have the
ability for stationary and mobile applications. Some stick to their program
while others learn and evolve. Collaborative robots have more sensors than
their counterparts on the assembly line and offer more capabilities for
companies.
With the rise of robotics
technology and industry spending, it’s a great opportunity for those who are
interested in artificial intelligence and robotics. A career in robotics
technology offers a wide variety of options, and a number of jobs fall under
this category.
This type of field can offer jobs
like service and repair as well as designing and creating the interfaces and
systems. It’s a multi-disciplinary field with growing opportunity as the
industry expands. Many perceive benefits of this type of work to be in the
distant future but are unaware of how much robots already play a role in
society and how fast they’re evolving.
One of the main technology
components in the manufacturing industry concerns robotics. In fact, 60% of
G2000 manufacturers will be working beside automated assistance technologies
like robotics, 3D printing and artificial intelligence. According to the
International Federation of Robots and Loup Ventures’ new report, robotic
spending will climb to $13 billion in 2025.
Market Growth: Industry data predicting that the
IoRT market will be worth approximately $21.44 billion by 2022. The compound
annual growth rate for the IoRT market would be 29.7% until 2022. These changes
are disrupting businesses, governments and consumers and transforming how they
interact with the world. In the next five years, companies will spend almost $5
trillion on the IoT, showing that we can all expect a rise in the combination
of these technologies and the resulting capabilities in a number of industries.
The IoT is a network of things
that are connected to the internet, including IoT devices and IoT-enabled
physical assets ranging from consumer devices to sensor-equipped connected
technology. These items are an essential driver for customer-facing innovation,
data-driven optimization, new applications, digital transformation, business
models and revenue streams across all sectors.
IoT devices are usually designed to handle specific tasks, while robots
need to react to unexpected conditions. Artificial intelligence and machine
learning help these robots deal with unexpected conditions that arise.
Applications and developments of
the Internet of Robotic Things: Doesn’t this look a bit like the autonomous
robots as we know them, even if it’s just from movies? Well, yes and no. Thinking about that
cyber-physical IoT promise, it does emphasize the “physical” aspect more than
is the case in most IoT projects today where the main focus is on “cyber”
component, as ABI Research puts it.
First of all let’s remind it’s
still early days but, more importantly let’s look at use cases and what exactly
is mean with control or manipulation of a physical object and you’ll see we are
very far from those movie robots. Before doing so let’s also remind
that we are speaking about robotics in the broader sense, so not just
industrial robots, even if that’s where we see some actual projects. However,
according to the earlier mentioned research, the growth of the IoRT market will
be driven by, among others applications in e-commerce (e.g. at Amazon, more
below). But also think robots in healthcare, domestic appliances (personal
robots) and vehicles.
Examples
In the Industrial Internet or
Industry 4.0 space, FANUC, a well-known Japanese and globally active
manufacturer of industrial and intelligent robots ad expert in factory
automation, joined forces with Rockwell Automation, Preferred Networks and
Cisco for the development of a system called ‘FIELD‘ (FANUC Intelligent Edge
Link and Drive). It uses sensors, middleware, deep learning, edge computing and
more to enable industrial robotics devices that coordinate and collaborate
(read: act). Industrial collaborative robots are one of the main areas in IoRT.
A robotic device that could check in a
corporate parking lot if a car is authorized to use that lot and, if not, alert
about it. He also cites the example of
Amazon Robotics‘ warehouse automation fulfillment center (here is our
e-commerce) where mobile robots move bins and pallets and can coordinate their
movements (to avoid accidents).
Obviously these are all still
relatively early initiatives. You can imagine applications in the personal
robot space, as said also a growing phenomenon, whereby robots can take real
physical action by learning and combining sensor data, whether it’s in garden
maintenance, support of the elderly or cleaning. An often mentioned example in
this regard is iRobot (cleaning appliances).
In many of these areas
initiatives are already taken and, when Research and Markets announced its IoRT
forecasts it cited a growing need for personal robots in the mentioned examples
of domestic cleaning and elderly assistance. And let’s not forget healthcare.
There are more examples in the article we’ve mentioned. And even these are only
the start.
Finally, note that, for instance
in a manufacturing context, IoRT and robots that can take decisions and
collaborate don’t mean the human element is entirely gone. As mentioned in our
overview of digital transformation in the manufacturing industry, for instance,
we cited findings from IDC’s ‘10 Predictions for the Manufacturing Industry‘
FutureScape (released end November 2016).
This is my thoughts and collected figures & images are respected tread marks, can be contacted my at ravindrapande@gmail.com skyppe : RavindraRPande also my organization for corporate training http://www.indiatrainingservices.in/
