SENSORS, ACTUATORS, AND SMART OBJECTS IOT

Module 2
Smart Objects: The “Things” in IoT

 Sensors are fundamental building blocks of IoT networks
 Sensors are the foundational elements found in smart
objects—the “things” in the Internet of Things
 Smart objects are any physical objects that contain
embedded technology to sense and/or interact with
their environment in a meaningful way by being
interconnected and enabling communication
among themselves or an external agent.

SENSORS, ACTUATORS, AND SMART OBJECTS
 A sensor: It senses
 More specifically, a sensor measures some physical
quantity and converts that measurement reading into a
digital representation.
 That digital representation is typically passed to another
device for transformation into useful data that can be
consumed by intelligent devices or humans
 Sensors are not limited to human-like sensory data.
 They are able to provide an extremely wide spectrum of rich
and diverse measurement data with far greater precision than
human senses

Categories
 Active or passive:
 Sensors can be categorized based on whether they produce an
energy output and typically require an external power
supply (active) or
 Whether they simply receive energy and typically require no
external power supply (passive).
 Invasive or non-invasive:
 Sensors can be categorized based on whether a sensor is part
of the environment it is measuring (invasive) or
 External to it (non-invasive).

 Contact or no-contact:
 Sensors can be categorized based on whether they require
physical contact with what they are measuring
(contact) or not (no-contact).
 Absolute or relative:
 Sensors can be categorized based on whether they
measure on an absolute scale (absolute) or based on a
difference with a fixed or variable reference value
(relative).

 Area of application:
 Sensors can be categorized based on the specific industry
or vertical where they are being used.
 How sensors measure:
 Sensors can be categorized based on the physical
mechanism used to measure sensory input (for
example, thermoelectric,electrochemical,piezoresistive,optic,electric,
fluid mechanic,photoelastic).

 What sensors measure:
 Sensors can be categorized based on their applications
or what physical variables they measure.
 Note that this is by no means an exhaustive list, and there are
many other classification and taxonomic schemes for sensors,
including those based on material, cost, design, and other
factors

Categorization based on what physical phenomenon a
sensor is measuring

Precision agriculture (smart farming)
 which uses a variety of technical advances to improve the efficiency,
sustainability, and profitability of traditional farming practices.
 This includes the use of GPS and satellite aerial imagery for determining field
viability; robots for high-precision planting, harvesting, irrigation, and so on; and
real-time analytics and artificial intelligence to predict optimal crop yield, weather
impacts,and soil quality.
 Among the most significant impacts of precision agriculture are those dealing
with sensor measurement of a variety of soil characteristics. These
include real- time measurement of soil quality, pH levels, salinity, toxicity levels,
moisture levels for irrigation planning, nutrient levels for fertilization planning, and
so on.
 All this detailed sensor data can be analyzed to provide highly valuable and
actionable insight to boost productivity and crop yield.

IoT Use Case: Area of precision agriculture
(smart farming)
 biodegradable, passive microsensors to measure soil and crop and
conditions
.
 These sensors, developed at North Dakota State University
(NDSU), can be planted directly in the soil and left in the ground
to biodegrade without any harm to soil quality.

Figure 3-1 Biodegradable Sensors Developed by NDSU for Smart Farming

Figure 3-3 Growth and Predictions in the Number of Sensors

Actuators
 Actuators are natural complements to sensors
 Sensors are designed to sense and measure practically any
measurable variable in the physical world.
 They convert their measurements (typically analog) into
electric signals or digital representations that can be
consumed by an intelligent agent (a device or a human).
 Actuators, on the others hand, receive some type of
control signal (commonly an electric signal or
digital command) that triggers a physical effect,
usually some type of motion, force, and so on.
 Sensors provide the information,actuators provide the
action

 Actuators also vary greatly in function, size, design, and so on.
 Some common ways that they can be classified include the
following:
 Type of motion: Actuators can be classified based on the type of
motion they produce (for example, linear, rotary, one/two/three-
axes).
 Power: Actuators can be classified based on their power output
(for example, high power, low power, micro power)
 Binary or continuous:Actuators can be classified based on the
number of stable-state outputs.
 Area of application:Actuators can be classified based on the
specific industry or vertical where they are used.
 Type of energy:Actuators can be classified based on their
energy type.

Classification based on energy type

Micro-Electro-Mechanical Systems (MEMS)
 Interesting advances in sensor and actuator technologies is in how
they are packaged and deployed.
 Micro-electro-mechanical systems (MEMS), sometimes simply
referred to as micro-machines, can integrate and combine electric and
mechanical elements, such as sensors and actuators, on a very small
(millimeter or less) scale.
 One of the keys to this technology is a microfabrication
technique that is similar to what is used for microelectronic
integrated circuits.
 This approach allows mass production at very low costs

 The combination of tiny size, low cost, and the ability to mass
produce makes MEMS an attractive option for a huge number of
IoT applications.
 MEMS devices have already been widely used in a variety of
different applications and can be found in very familiar
everyday devices.
 For example, inkjet printers use micropump MEMS.
 Smart phones also use MEMS technologies for things
like accelerometers and gyroscopes.
 In fact, automobiles were among the first to commercially
introduce MEMS into the mass market, with airbag
accelerometers.

Figure 3-6 Torsional Ratcheting Actuator (TRA) MEMS (Courtesy Sandia National
Laboratories, SUMMiT™ Technologies, www.sandia.gov/mstc.)

Smart Objects
 Smart objects are, quite simply, the building blocks of IoT.
 They are what transform everyday objects into a
network of intelligent objects that are able to learn
from and interact with their environment in a
meaningful way
 The real power of smart objects in IoT comes from being
networked together rather than being isolated as standalone
objects

 If a sensor is a standalone device that simply measures the
humidity of the soil, it is interesting and useful, but it isn’t
revolutionary
 If that same sensor is connected as part of an intelligent
network that is able to coordinate intelligently with
actuators to trigger irrigation systems as needed based on
those sensor readings, we have something far more powerful
 Extending that even further, imagine that the coordinated
sensor/actuator set is intelligently interconnected with
other sensor/actuator sets to further coordinate
fertilization,pest control,and so on—and even communicate
with an intelligent backend to calculate crop yield potential

 A smart object, is a device that has, at a minimum, the
following four defining characteristics

 Processing unit:
 Some type of processing unit for
 Acquiring data,
 Processing and analyzing sensing information
received by the sensor(s),
 Coordinating control signals to any actuators, and
 Controlling a variety of functions on the smart
object, including the communication and power systems
 The most common is a microcontroller because of its
small form factor, flexibility, programming simplicity,
ubiquity, low power consumption, and low cost

 Sensor(s) and/or actuator(s):
 A smart object is capable of interacting with the physical
world through sensors and actuators
 Communication device:
 The communication unit is responsible for connecting a
smart object with other smart objects and the
outside world (via the network).
 Communication devices for smart objects can be either
wired or wireless

 Power source:
 Smart objects have components that need to be powered.
 The most significant power consumption usually comes from
the communication unit of a smart object

Trends in Smart Objects
 Size is decreasing
 Power consumption is decreasing
 Processing power is increasing
 Communication capabilities are improving
 Communication is being increasingly standardized

SENSOR NETWORKS
 A sensor/actuator network (SANET), is a network of sensors
that sense and measure their environment and/or
actuators that act on their environment
 The sensors and/or actuators in a SANET are capable of
communicating and cooperating
 Effective and well-coordinated communication and
cooperation is a prominent challenge, primarily because the
sensors and actuators in SANETs are diverse, heterogeneous, and
resource-constrained

 SANETs offer highly coordinated sensing and actuation
capabilities.
 Smart homes are a type of SANET that display this
coordination between distributed sensors and actuators
 For example, smart homes can have temperature sensors
that are strategically networked with heating, ventilation, and
air-conditioning (HVAC) actuators.
 When a sensor detects a specified temperature, this can
trigger an actuator to take action and heat or cool the home
as needed.

 Advantages and disadvantages that a wireless-based solution
offers:
Advantages:
 Greater deployment flexibility (especially in extreme
environments or hard-to-reach places)
 Simpler scaling to a large number of nodes
 Lower implementation costs
 Easier long-term maintenance
 Effortless introduction of new sensor/actuator nodes
 Better equipped to handle dynamic/rapid topology changes
Disadvantages:
 Potentially less secure (for example, hijacked access points)
 Typically lower transmission speeds
 Greater level of impact/influence by environment

Wireless Sensor Networks (WSNs)
 Wireless sensor networks are made up of wirelessly
connected smart objects, which are sometimes referred to
as motes.
 The fact that there is no infrastructure to consider
withWSNs is surely a powerful advantage for flexible
deployments, but there are a variety of design constraints
to consider with these wirelessly connected smart objects

 The following are some of the most significant limitations of
the smart objects inWSNs:
 Limited processing power
 Limited memory
 Lossy communication
 Limited transmission speeds
 Limited power
 Note
 Smart objects with limited processing, memory, power, and
so on are often referred to as constrained nodes.

 These limitations greatly influence howWSNs are designed,
deployed, and utilized.
 The fact that individual sensor nodes are typically so limited
is a reason that they are often deployed in very large
numbers.
 As the cost of sensor nodes continues to decline, the ability
to deploy highly redundant sensors becomes increasingly
feasible.
 Because many sensors are very inexpensive and
correspondingly inaccurate, the ability to deploy smart
objects redundantly allows for increased accuracy

 Such large numbers of sensors permit the introduction
of hierarchies of smart objects.
 Such a hierarchy provides, among other organizational
advantages, the ability to aggregate similar sensor
readings from sensor nodes that are in close
proximity to each other

 . Figure 3-9 shows an example of such a data aggregation function in a
WSN where temperature readings from a logical grouping of
temperature sensors are aggregated as an average temperature
reading.
Figure 3-9 Data Aggregation in Wireless Sensor Networks

 These data aggregation techniques are helpful in reducing the
amount of overall traffic (and energy) inWSNs with very large
numbers of deployed smart objects.
 This data aggregation at the network edges is where fog and
mist computing are critical IoT architectural elements needed to
deliver the scale and performance required by so many IoT use
cases

 Wirelessly connected smart objects generally have one of the
following two communication patterns:
 Event-driven:
 Transmission of sensory information is triggered only when a smart object
detects a particular event or predetermined threshold.
 Periodic:
 Transmission of sensory information occurs only at periodic intervals.
 The decision of which of these communication schemes is used depends
greatly on the specific application
 For example:medical use cases

 For example, in some medical use cases, sensors
periodically send postoperative vitals, such as
temperature or blood pressure readings. In other
medical use cases, the same blood pressure or
temperature readings are triggered to be sent only
when certain critically low or high readings are
measured.

Communication Protocols for Wireless
Sensor Networks
 There are literally thousands of different types of sensors and actuators.
 WSNs are becoming increasingly heterogeneous, with more sophisticated
interactions.
 Any communication protocol must be able to scale to a large
number of nodes.
 Likewise, when selecting a communication protocol, you must
carefully take into account the requirements of the specific
application and consider any trade-offs the communication
protocol offers between power consumption, maximum
transmission speed, range, tolerance for packet loss, topology
optimization,security,and so on

 They must also enable, as needed, the overlay of autonomous
techniques (for example, self-organization, self-healing, self-
configuration)
 Wireless sensor networks interact with their environment. Sensors often
produce large amounts of sensing and measurement data that needs to
be processed. This data can be processed locally by the nodes of
aWSN or across zero or more hierarchical levels in IoT networks.
 Communication protocols need to facilitate routing and
message handling for this data flow between sensor
nodes as well as from sensor nodes to optional gateways, edge
compute,or centralized cloud compute

 standardization of communication protocols is a
complicated task.
 While there isn’t a single protocol solution, there is
beginning to be some clear market convergence around
several key communication protocols.

SENSORS, ACTUATORS, AND SMART OBJECTS IOT

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