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Module 5
5.1 Introduction to Arduino

Arduino is an open-source advancement prototyping platform which depends on simple to utilize equipment
and programming. Arduino can read-inputs – such as detecting the power of light, events triggered by a button
or a twitter message and can respond into a yield, for example, run the engine, on the LED, send data through
online. Instructions to the microcontroller are given by the use of Arduino programming dialect which depends
on wiring and handled through the utilization of Arduino Software (IDE).

5.1.1 Why Arduino

• Inexpensive: Arduino boards are relatively inexpensive compared to other microcontroller platforms.
The least expensive version of the Arduino module can be assembled by hand.
• Cross-platform: The Arduino software runs on Windows, Macintosh OS and Linux operating
systems.
• Simple, clear programming environment: The Arduino programming environment is easy-to-use for
beginners, yet flexible enough for advanced users to take advantage of as well.
• Open source and extensible software: The Arduino software is published as open-source tools,
available for extension by experienced programmers. The language can be expanded through C++
libraries.
• Open source and extensible hardware: The Arduino is based on Atmel's ATMEGA microcontrollers.
Even relatively inexperienced users can build the breadboard version of the module in order to
understand how it works and save money.

5.1.2 Which Arduino

In ten years since Arduino was released, hundreds of “Arduino boards” are available in the market
serving every kind of purpose.
Some of the boards from Arduino family are given below.
• Arduino Mega is a big sister to the UNO with more memory and pins with a different chip the
ATmega2560, useful when your project does’t fits in an UNO.
• Arduino Micro is bit smaller with a chip ATmega 32u4 that can act like a keyboard or mouse
which does its task with native USB. Its slim with downward pins which can be plugged into a
breadboard.
• Arduino MKR1000 is a little like an Arduino Micro but has a more powerful 32-bit ATSAM
ARM chip and built-in Wi-Fi. A great upgrade for when you want to do internet of things
projects.
• Flora is an Arduino compatible from Adafruit which is a round wearable which can be sewed
into clothing.

5.2 Exploring Arduino Uno Learning Boar

• Microcontroller: the ATmega328p is the Arduino brain.

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• Digital pins: Arduino has 14 digital pins, labelled from 0 to 13 that can act as inputs or outputs.
• When set as inputs, these pins can read voltage. They can only read two different states HIGH or LOW.
When seta as outputs, these pins can apply voltage. They can only apply 5V(HIGH) or 0V(LOW).
• PWM pins: these are digital pins marked with a ~ (pins 11,10,9,6,5 and 3). PWM for “pulse width
modulation” and allows to make digital pins output “fake ” varying amounts of voltage.
• TX and RX pins: digital pins 0 and 1. The T stands for “transmit” and R stands for “receiver” . Arduino
uses these pins to communicate with the computer. Avoid these pins, unless you’re running out of pins.
• LED attached to digital pin 13: this is useful for an easy debugging of the Arduino sketches.
• TX and RX pins: these pins blink when there are information being sent between the computer and
Arduino.
• Analog pins: the analog pins are labelled from A0 to A5 and are most often used to read analog sensors.
• Power pins: The Arduino has 3.3V or 5V supply, which is really useful since most components require
3.3V or 5V.
• Reset Button: when you press that button, the program that is currently being run in your Arduino will
start from the beginning.
• Power ON LED: will be on since power is applied to the Arduino.
• USB jack: Connecting a male USB A to male USB B cable is how you upload programs from your
computer to your Arduino board. This also powers your Arduino.
• Power Jack: The power jack is where you connect a component to power up your Arduino. There are
several ways to power up your Arduino: rechargeable batteries, disposable batteries, wall-warts and
solar-panel.

5.2.1 Things that Arduino can do

• The simplest thing you can control with your Arduino is an LED.
• You can also display a message in a display, like LCD display.
• You can also control DC or Servo motors.
• You can also read data from the outside world
• Motion sensor: the motion sensor allow you detect movement.
• Light sensor: this allows you to “measure” the quantity of light in the outside word.
• Humidity and temperature sensor: this is used to measure the humidity and temperature.
• Ultrasonic sensor: this allows to determine the distance to an object through sonar.
• Shields: an extension of the Arduino
• Shields are boards that will expand the functionalities of you Arduino.
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5.3 Installing the Software

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The Toolbar buttons and functions of each button are as shown in Table

Verify Check the code for errors

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Stop Stop the serial monitor, or un-highlight other buttons

New Creates a new blank sketch. Enter a name and a location for you
sketch
Open Shows a list of sketches in your sketchbook
Upload Uploads the current sketch to the Arduino. You need to make sure that
you have the current board and port selected before uploading.
Serial Monitor Display serial data being sent from the Arduino
Compile Button is used to check that your code is correct, before you upload it
to your Arduino.
Stop button Will stop the serial monitor from operating. If you need to obtain a
snapshot of the serial data so far explained.

Breadboard for prototyping Arduino UNO Circuits

A breadboard is a solderless construction base used for developing an electronic circuit and wiring for projects
with microcontroller boards like Arduino. The vertical columns of the breadboard are called terminals, while
the horizontal long rows are called power rails because they are mostly used to connect the power supply to
the breadboard. The positive rails are indicated by red lines, while the negative rails are indicated by black
ones.

Table 7-6 Technical Specifications of Arduino Uno

Microcontroller ATmega328P
Operating Voltage 5V
Input Voltage (recommended) 7-12V
Input Voltage (limit) 6-20V
Digital I/O Pins 14 (of which 6 provide PWM output)
PWM Digital I/O Pins 6
Analog Input Pins 6
DC Current per I/O Pin 20 mA
DC Current for 3.3V Pin 50 mA
Flash Memory 32 KB (ATmega328P) of which 0.5 KB used by bootloader
SRAM 2 KB (ATmega328P)
EEPROM 1 KB (ATmega328P)
Clock Speed 16 MHz
LED_BUILTIN 13
Length 68.6 mm
Width 53.4 mm
Weight 25 g
5.4 Fundamentals of Arduino Programming
• This section in table 7-3 explains the basic structure of Arduino programming with respect to usage
of variables, constants, control flow statement and finally the predefined functions used to read
analog and digital inputs.
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Exploring the Raspberry Pi Learning Board

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Raspberry Pi Model and its GPIO

• Processor: The Broadcom BCM2835 SoC used in the first generation Raspberry Pi is somewhat
equivalent to the chip used in first generation smart phones which includes a 700 MHz ARM
1176JZF-S processor, Video Core IV graphics processing unit (GPU) and RAM.
• Power Source: The recommended and easiest way to power the Raspberry Pi is via Micro USB port
on the side of the unit. The recommended input voltage 5V, and the recommended input current is
2A.
• Ethernet: The Ethernet port of the raspberry pi is the main gateway for communicating with
additional devices. The raspberry pi Ethernet port is used to plug your home router to access the
internet.
• USB Ports: It has 2 USB ports. USB port provide current upto 100mA. For connecting devices that
draw current more than 100mA, an external USB powered hub is required.
• HDMI Output: It supports both audio and video output. Connect raspberry Pi to monitor using
HDMI cable.
• Composite video Output: Raspberry comes with a composite video output with an RCA jack that
supports both PAL and NTSC video output.
• Audio Output: It has 3.5mm audio output jack. This audio jack is used for providing audio output to
old television along with RCA jack for video.
• GPIO Pins: It has a number of general purpose input/output pins. These pins are used to connect
other electronic components. For example, you can connect it to the temperature sensor to transmit
digital data.
• Display Serial Interface (DSI): DSI interface are used to connect an LCD panel to Raspberry PI.
• Cameral Serial Interface(CSI): CSI interface are used to connect a camera module to Raspberry PI.
• Memory: The raspberry pi model A board is designed with 256MB of SDRAM and model B is
designed with 51MB.Raspberry pi is a small size PC compare with other PCs. The normal PCs RAM
memory is available in gigabytes. But in raspberry pi board, the RAM memory is available more than
256MB or 512MB.
• JTAG headers: JTAG is an acronym for Joint Test Action Group’, an association that began back in
mid 1980’s to address test point get to issues on PCB with surface mount gadgets.
• Status LEDs: Raspberry has 5 status LEDs.
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8.1.1 Description of System on Chip(SoC)

A System on a chip (SoC) is an integrated circuit (IC) that coordinates all parts of a PC or other electronic
framework into a solitary chip.
An SoC comprises of:
• A microcontroller, chip or DSP core(s). Some SoCs—called multiprocessor framework on chip
(MPSoC) – incorporate more than one processor centre.
• Memory pieces including a choice of ROM, RAM, EEPROM and streak memory
• Timing sources including oscillators and stage bolted circles
• Peripherals including counter-clocks, ongoing clocks and power-on reset generators.
• Outer interfaces, including industry norms, for example, USB, FireWire, Ethernet, USART, SPI
• Simple interface including SDCs and DACs
• Voltage controllers and power administration circuits.

Accessories
• Camera- the Raspberry Pi camera board contains 5 MPixel sensor, and interfaces through strip link to
the CSI connector on the Raspberry Pi.

Gertboard
• A Raspberry Pi Foundation authorised gadget intended for instructive purposes, and grows the
Raspberry Pi’s GPIO pins to permit interface with control of LEDs switches, simple signs, sensor and
different gadgets.

USB Hub
• In spite of the fact that not an official embellishment, it is an exceptionally suggested extra for the Pi.

8.1.2 Raspberry Pi Interface

Raspberry Pi has serial, SPI and I2C interfaces
• Serial: the serial interface on Raspberry Pi has receive(Rx) and transmit(Tx) pins for communication
with serial peripherals.
• SPI: Serial Peripheral Interfaces(SPI) is a synchronous serial data protocol used for communication
with one or more peripheral devices. There are 5 pins on Raspberry Pi for SPI interface
o MISO(Master In Slave Out): Master line for sending data to the peripherals
o MOSI(Master Out Slave In): Slave line for sending data to the master.
o SCK(Serial Clock): Clock generated by master to synchronize data transmission.
o CE0(Chip Enable 0): To enable or disable devices
o CE0(Chip Enable 1): To enable or disable devices
• I2C: The I2C interface pins on Raspberry Pi allow you to connect hardware modules. I2C interface
allows synchronous

8.3 Raspberry Pi Operating System

• Various operating system can be installed on Raspberry Pi through SD cards. Most use a MicroSD
slot located on the bottom of the board. The Raspberry Pi primarily uses Raspbain, a Debain-based
Linux operating system.
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• Other third party operating systems available via official website include Ubuntu MATE, Snappy
Ubuntu Core, Windows 10 IoT Core, RISC OS and specialised distribution for the Kodi media centre
and classroom management.

8.4 Operating System Setup on Raspberry Pi

• Preinstalled NOOBS operating system is already available in many authorized as well as independent
seller, there are many other operating system for Raspberry Pi in the market like NOOBS, Raspbian
and third party operating system are also available like UBUNTU MATE, OSMC, RISC OS etc. To
setup an operating system we need a SD card with minimum capacity of 8GB.
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8.4.5 Login Information

• The default login for Raspbian is username “pi” with the password “raspberry”. To load the graphical
user interface, type “startx” and press enter.
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Figure 8-3 shows Raspbian pi desktop and Figure 8-4 shows File explore on Raspberry Pi. Figure 8-5 shows
console on Raspberry Pi, Figure 8-6 shows browser on Raspberry Pi to expand root partition to fill SD card,
change password, setting time zone, enable SSH(Secure Shell) server and change root behaviour.
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Digital Temperature Sensors Vs. Analog Temperature Sensors

• Analog temp. sensors contain thermistors and temperature value is obtained from resistance value (due
to change in volt)
• Digital temperature sensors are typically silicon based integrated circuits
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• Unlike analog temperature sensors, calculations are performed by the sensor, and the output is an actual
temperature value

Raspberry Pi and DS18B20 Temperature Sensor

About the DS18B20
• The DS18B20 also has an alarm function that can be configured to output a signal when the temperature
crosses a high or low threshold that’s set by the user.
• A 64 bit ROM stores the device’s unique serial code. This 64 bit address allows a microcontroller to
receive temperature data from many sensors with identity.
• The DS18B20 temperature sensor is perfect for projects like weather stations and home automation
systems
• The size is same as a transistor and use only one wire for the data signal
• Extremely accurate and take measurements quickly

DS18B20 : Technical Specifications

• -55°C to 125°C -: temperature range
• 3.0V to 5.0V :- operating voltage
• 0.5°C (9 bit); 0.25°C (10 bit); 0.125°C (11 bit); 0.0625°C (12 bit) resolution
• 64 bit unique address
• One-Wire communication protocol

DS12B20 Pin Diagram

Figure 5.10 DS12B20 Pin Diagram

Configuring Raspberry Pi
• sudo nano /boot/config.txt
• Add this à “dtoverlay=w1-gpio” at the end of file if doesn’t exist
• sudo reboot
• sudo modprobe w1-gpio
• sudo modprobe w1-therm
• cd /sys/bus/w1/devices
• ls
• a3 01 4b 46 7f ff 0e 10 d8 : crc=d8 YES
• cd 28-xxxx
• cat w1_slave
• a3 01 4b 46 7f ff 0e 10 d8 t=32768

Pi Via SSH (Secure Shell)

• You can access the command line of a Raspberry Pi remotely from another computer or device
• The Raspberry Pi will act as a remote device: you can connect to it using a client on another machine.
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• Set up your local network and wireless connectivity

o Make sure your Raspberry Pi is properly set up and connected
o If you are using wireless networking, this can be enabled via the desktop's user interface, or
using the command line
o You will need to note down the IP address of your Pi in order to connect to it later.
o Using the ifconfig command will display information about the current network status,
including the IP address, or you can use hostname -I to display the IP addresses associated
with the device
• Enable SSH
o Enter sudo raspi-config in a terminal window
o Select Interfacing Options
o Navigate to and select SSH
o Choose Yes
o Select Ok
o Choose Finish
• Alternatively, use systemctl to start the service
o sudo systemctl enable ssh
o sudo systemctl start ssh
• Enable SSH on a headless Raspberry Pi (add file to SD card on another machine)
o For headless setup, SSH can be enabled by placing a file named ssh, without any extension,
onto the boot partition of the SD card from another computer.
o When the Pi boots, it looks for the ssh file. If it is found, SSH is enabled and the file is deleted
• Set up your client
o SSH is built into Linux distributions and Mac OS. For Windows and mobile devices, third-
party SSH clients are available.

Smart and Connected Cities

An IoT Strategy for Smarter Cities
• Managing a city bears some resemblance to managing a corporate enterprise.
• As the need for efficiency increases, new tools help increase operational efficiency.
• For cities, just as for businesses, digitization transforms the perspective on operations.
• New ideas emerge, bringing different approaches to solving management issues.

Vertical IoT Needs for Smarter Cities

• There are many differing approaches and solutions for city management.
• Allthese solutions typically start at the street level, with sensors that capture data on everything from
parking space availability to water purity.
• Data analytics is also used extensively—for example, to reduce crime or improve traffic flows.
• Citizens can use tools to leverage their smart mobile devices, such as to report problems and make
recommendations for improving urban life or locate available parking spaces.
• When enabled through connectivity, these smart solutions can have a transformative impact on
quality of life.
• A recent Cisco study, as illustrated in Figure 5.11, expects IoT to have the following economic
impact over a 10-year period:
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1) Smart buildings: Smart buildings have the potential to save $100 billion by lowering operating costs by
reducing energy consumption through the efficient integration of heating, ventilation, and air-conditioning
(HVAC) and other building infrastructure systems.
• Note that the financial gain applies to city budgets only when a building is city owned.
• However, the reduced emissions benefit the city regardless of who owns the buildings.
2) Gas Monitoring: Monitoring gas could save $69 billion by reducing meter-reading costs and increasing the
accuracy of readings for citizens and municipal utility agencies.
• The financial benefit is obvious for users and utility companies when the utility is managed by the
city.
• There are also very important advantages in terms of safety, regardless of who operates the utility.
• In cases of sudden consumption increase, a timely alert could lead to emergency response teams
being dispatched sooner, thus increasing the safety of the urban environment.
3) Smart Parking: : Smart parking could create $41 billion by providing realtime visibility into parking space
availability across a city
• Residents can identify and reserve the closest available space, traffic wardens can identify
noncompliant usage, and municipalities can introduce demand based pricing.

4) Water management: Smart water management could save $39 billion connecting household water meters
over an IP network to provide remote usage and status information.

• The benefit is obvious, with features such as real-time consumption visibility and leak detection.
• A gate or a pump can be opened and closed remotely and automatically in real time, based on a
variety of flow input and output analytics data.
• Vibrations can be measured to detect and predict potential equipment failures.
• Repair teams can be dispatched proactively before equipment failure occurs.
• Road pricing: Cities could create $18 billion in new revenues by implementing automatic payments
as vehicles enter busy city zones while improving overall traffic conditions.
• Real-time traffic condition data is very valuable and actionable information that can also be used to
proactively reroute public transportation services or private users

Global vs. Siloed Strategies

• The main obstacle in implementing smart solutions in today’s traditional infrastructure is the
complexity of how cities are operated, financed, regulated and planned.
• Cities attempting to upgrade their infrastructure to match the growing needs of the citizenpopulation
often invest in one problem at a time, and they do it independently.
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• Even cities using IoT technology break up city assets and service management into silos
that are typically unable to communicate or rely on each other.
The independent investment model results in the following problems:
• Isolation of infrastructure and IT resources
• No sharing of intelligence and information, such as video feeds and data
from sensors.
• Waste and duplication in investment and effort
• Difficulty scaling infrastructure management
• All these requirements pose technological challenges, including the following:
• How do you collect the data? What are the various sources of data, including
hardware endpoints and software?
• How do you make sure that any data collection devices, such as sensors, can be
maintained without high costs?
• Where do you analyze the data? What data do you carry back to the cloud, and what
data do you analyze locally?
• What kind of network connectivity is best suited for each type of data to collect?
• What kind of power availability and other infrastructure, such as storage, is required?
• How do you aggregate data from different sources to create a unified view?
• How do you publish the data and make it available for applications to consume?
• How do you make the end analysis available to specialized smart city personnel, such
as traffic operators, parking enforcement officers, street lighting operators, and so on at
their logical decision points?
• How do you present the long-term analysis to city planners?
 5.10) Smart City IoT Architecture
• A smart city IoT infrastructure is a four-layered architecture, as shown in Figure 5-12.
• Data flows from devices at the street layer to the city network layer and connect to the
data center layer, where the data is aggregated, normalized, and virtualized.
• The data center layer provides information to the services layer, which consists of the
applications that provide services to the city.

Figure 5.12 Smart Cities Layered Architecture

1) Street Layer
• on
Theinstructions
street layerfrom
is composed of solution,
the overall devices and sensors
as well that
as the collect data
networking and take action
components neededbased
to
aggregate and collect data.
• A sensor is a data source that generates data required to understand the physical world.
Sensor devices are able to detect and measure events in the physical world.
• ICT (information and communication technology ) connectivity solutions rely on sensors
to collect the data from the world around them so that it can be analyzed and used to
operationalize use cases for cities.
• A variety of sensors are used at the street layer for a variety of smart city use cases
• A magnetic sensor can detect a parking event by analyzing changes in the
surrounding magnetic field when a heavy metal object, such as a car or a truck,
comes close to it (or on top of it).
• A lighting controller can dim and brighten a light based on a combination of time-
based and ambient conditions.
 • Video cameras combined with video analytics can detect vehicles, faces,
and traffic conditions for various traffic and security use cases.
• An air quality sensor can detect and measure gas and particulate matter
concentrations to give a hyper-localized perspective on pollution in a given area.
• Device counters give an estimate of the number of devices in the area, which
provides a rough idea of the number of vehicles moving or parked in a street or a
public parking area, of pedestrians on a sidewalk, or even of birds in public parks
or on public monuments—for cities where bird control has become an issue.
2) City Layer
• At the city layer, which is above the street layer, network routers and switches must be
deployed to match the size of city data that needs to be transported.
• This layer aggregates all data collected by sensors and the end-node network into a single
transport network.
• The city layer may appear to be a simple transport layer between the edge devices and the
data center or the Internet.
• However, one key consideration of the city layer is that it needs to transport multiple
types of protocols, for multiple types of IoT applications.
• Some applications are delay- and jitter-sensitive, and some other applications require a
deterministic approach to frame delivery.
• As a result, the city layer must be built around resiliency, to ensure that a packet coming
from a sensor or a gateway will always be forwarded successfully to the headend station.
Figure 5.13 shows a common way of achieving this goal.

Figure 5.13 Street Layer Resiliency

3) Data Center Layer
• Ultimately, data collected from the sensors is sent to a data center, where it can be
processed and correlated.
• Based on this processing of data, meaningful information and trends can be derived, and
information can be provided back.
• For example, an application in a data center can provide a global view of the city traffic
and help authorities decide on the need for more or less common transport vehicles.
• At the same time, an automated response can be generated.
• For example, the same traffic information can be processed to automatically regulate and
coordinate the street light durations at the scale of the entire city to limit traffic congestion.
• The key technology in creating any comprehensive smart solution with services is the
cloud.
• With a cloud infrastructure, data is not stored in a data center owned directly or indirectly
by city authorities.
• Instead, data is stored in rented logical containers accessed through the Internet.
• Because the containers can be extended or reduced based on needs, the storage size and
computing power are flexible and can adapt to changing requirements or budget conditions.
• In addition, multiple contractors can store and process data at the same time, without the
complexity of exclusively owned space.
• This proximity and flexibility also facilitate the exchange of information between smart
systems and allow for the deployment of new applications that can leverage information
from several IoT systems.
• Figure 5.14 shows the vision of utilizing the cloud in smart solutions for cities.
• The cloud provides a scalable, secure, and reliable data processing engine that can handle
the immense amount of data passing through it.
• Smart city issues require not just efficient use of infrastructure, which the cloud helps
enable, they also require new data processing and management models.
• For example, cloud services allow for Software as a Service (SaaS) models that create
cyclical returns on investment.
 Figure 5.14 The Role of the Cloud for Smart City Applications

• With the cloud approach shown in Figure 5.14 , smart cities can also take advantage of
operating expense–based consumption models to overcome any financial hurdles in
adopting solutions to their most critical issues.
• Critical data, such as air condition (humidity, temperature, pollution) levels monitoring,
can be processed initially.
• Then, as the efficiency of IoT is scaled up, richer data processing can be enabled in the
cloud applications.
lights. In times when city budgets are strained, data processing can be scaled down to
essential services.
4) Services Layer
• Ultimately, the true value of ICT connectivity comes from the services that the measured
data can provide to different users operating within a city.
• Smart city applications can provide value to and visibility for a variety of user types,
including city operators, citizens, and law enforcement.
• The collected data should be visualized according to the specific needs of each consumer
of that data and the particular user experience requirements and individual use cases.
• For example, parking data indicating which spots are and aren’t currently occupied can
drive a citizen parking app with a map of available spots, as well as an enforcement officer’s
understanding of the state (utilization and payment) of the public parking space,
 while at the same time helping the city operator’s perspective on parking problem areas in
the city at any given time.
• With different levels of granularity and scale, the same data performs three different
functions for three different users.
• Along the same lines, traffic information can be used by individual car drivers to find
the least congested route.
• A variation of the same information can be made available to public transportation users
to estimate travel times.
• Public transportation systems, such as buses, can be rerouted around known congestion
points.
• The number of subway trains can be increased dynamically to respond to an increase in
traffic congestion, anticipating the decisions of thousands or even millions of commuters
to take public transportation instead of cars on days when roads are very congested.
• Here again, the same type of data is utilized by different types of users in different ways
based on their specific use cases.
On-Premises vs. Cloud
• Different cities and regions have different data hosting requirements based on security or
legal policies. A key consideration in developing ICT connectivity solutions is whether a
city has requirements about where data should be hosted.
• Data can be hosted on-premises or in the cloud. Fog architectures provide an intermediate
layer.
• The data resulting from fog processing can be sent to the cloud or to a data center operated
locally (on-premises).
• On-premises encompasses traditional networks, and all their limitations, whereas cloud
hosting encompasses a whole host of security risks if the proper measures are not taken to
secure citizen data.
• When data is sent to the cloud, data sovereignty (supremacy) laws may restrict the physical
location where this data is actually stored.
• Ideally, a smart city utilizing ICT connectivity would use the cloud in its architecture, but
if this is impossible, the city would need to invest far more in the city layer’s networking
components (for example, switches, routers) and still may not be able to drive the same
cross-domain value propositions and scalability in its design.
5.11) Smart City Security Architecture
• A serious concern of most smart cities and their citizens is data security.
• Vast quantities of sensitive information are being shared at all times in a layered, realtime
architecture, and cities have a duty to protect their citizens’ data from unauthorized access,
collection, and tampering.
• In general, citizens feel better about data security when the city itself, and not a private
entity, owns public or city-relevant data.
• It is up to the city and the officials who run it to determine how to utilize this data.
• When a private entity owns city-relevant data, the scope of the ownership may initially be
very clear.
• However, later considerations or changes in the private entity strategy may shift the way
the data is used.
• It may then be more difficult for city authorities or the citizens to oppose this new direction,
simply because they do not have any stake in the decision-making process ofthe private
entity.
• For example, suppose that a private contractor is in charge of collecting and managing
parking sensor data.
• One possible way to increase the profitability of such data is to sell it to insurance
companies looking to charge an additional premium to car owners parking in the street (vs.
in a covered and secured garage).
• Such deviations from the original mandate are less likely to happen when cities own the
data and when citizens have a way to vote against such usages.
• A security architecture for smart cities must utilize security protocols to fortify each layer
of the architecture and protect city data.
• Figure 5.15 shows a reference architecture, with specific security elements highlighted.
Security protocols should authenticate the various components and protect data transport
throughout.
• For example, hijacking traffic sensors to send false traffic data to the system regulating
the street lights may result in dramatic congestion issues.
• The benefit for the offender may be the ability to get “all greens” while traveling, but the
overall result would typically be dangerous and detrimental to the city.
• The security architecture should be able to evolve with the latest technology and
incorporate regional guidelines (for example, city by-laws, county or regional security
regulations).
• Network partners may also have their own compliance standards, security policies, and
governance requirements that need to be added to the local city requirements.

Figure 5.15 Key Smart and Connected Cities Reference Architecture

The following are common industry elements for security on the network layer:
• Firewall: A firewall is located at the edge, and it should be IPsec- and VPN-ready,
and include user- and role-based access control.
• It should also be integrated with the architecture to give city operators remote access
to the city data center.
• VLAN: A VLAN provides end-to-end segmentation of data transmission, further
protecting data from rogue intervention. Each service/domain has a dedicated VLAN
for data transmission.
• Encryption: Protecting the traffic from the sensor to the application is a common
requirement to avoid data tampering and eavesdropping.
• In most cases, encryption starts at the sensor level. In some cases, the sensor-to gateway
link uses one type of encryption, and the gateway-to-application connection uses
another encryption (for example, a VPN).
5.17) Smart City Use-Case Examples
• There are multiple ways a smart city can improve its efficiency and the lives of its
citizens.
• The following sections examine some of the applications commonly used as starting
 points to implement IoT in smart cities: connected street lighting, smart parking, smart
traffic control, and connected environment.
Connected Street Lighting
• Of all urban utilities, street lighting comprises one of the largest expenses in a
municipality’s utility bill, accounting for up to 40% of the total, according to the New York
State Department of Environmental Conservation.
• Maintenance of street lights is an operational challenge, given the large number of lights
and their vast geographic distribution.
Connected Street Lighting Solution
• Cities commonly look for solutions to help reduce lighting expenses and at the same time
improve operating efficiencies while minimizing upfront investment.
• The installation of a smart street lighting solution can provide significant energy savings
and can also be leveraged to provide additional services.
• In this regard, light-emitting diode (LED) technology leads the transition from traditional
street lighting to smart street lighting:
• LEDs require less energy to produce more light than legacy lights, and they have a much
longer life span and a longer maintenance cycle.
• A leading lighting company estimates that a complete switch to LED technology can
reduce individual light bills by up to 70%.
• LEDs are well suited to smart solution use cases.
• For example, LED color or light intensity can be adapted to site requirements (forexample,
warmer color and lower intensity in city centers, sun-like clarity on highways, time- and
weather-adaptive intensity and color).
• Figure 5.16 shows how electricity prices rise, while LED prices decrease and their unit
sales rise.

Figure 5.16 Electricity Cost vs. LED Cost and Sales

Street Lighting Architecture
• Connected lighting uses a light management application to manage street lights remotely
by connecting to the smart city’s infrastructure.
• This application attaches to LED lights, monitors their management and maintenance, and
allows you to view the operational status of each light.
• In most cases, a sensor gateway acts as an intermediate system between the application
and the lights (light control nodes).
• The gateway relays instructions from the application to the lights and stores the local
lights’ events for the application’s consumption.
• The controller and LED lights use the cloud to connect to the smart city’s infrastructure,
as shown in Figure 5.17.

Figure 5.17 Connected Lighting Architecture

• A human or automated operator can use a cloud application to perform automated
scheduling for lights and even get light sensors to perform automated dimming or
brightening, as needed.
• The schedule can also impact the light intensity level and possibly the color, depending on
environmental conditions, weather, time of year, time of day, location within the city, and
so on.
• Lighting nodes vary widely in the industry, especially with respect to elements such as what
communication protocol they use (for example, Wi-Fi, cellular, ZigBee, 802.15.4g [Wi-
SUN], LoRaWAN).
• These features are optimized for different circumstances and conditions; no single lighting
node can support all environments ideally.
• Many solutions leverage wired connectivity, either by using the existing city cable
infrastructure or by adding a cable adjacent to the power cable.
• In cases where cabling is not practical, wireless technologies may bring interesting
capabilities.
• For example, 802.15.4g controllers can be used to form a mesh and extend the network.
This extension is used not only to connect other light poles but also to connect smart meters
from neighboring houses.
• In all cases, the built-in versatility offered by the four-layer architecture shown in Figure
5.17 ensures that all the different types of technologies optimized to fit any city topology
can be flexibly incorporated into the solution.
Smart Parking Use Cases
• Added traffic congestion is one consequence of drivers looking for parking space, and it
has several consequences:
• Contributes to pollution: Tons of extra carbon emissions are released into the city’s
environment due to cars driving around searching for parking spots when they could be
parked.
• Causes motorist frustration: In most cities, parking spot scarcity causes drivers to lose
patience and waste time, leading to road rage, inattention, and other stress factors.
• Increases traffic incidents: Drivers searching for parking spots cause increased
congestion in the streets and that, in turn, causes increased accidents and other traffic
incidents.
• Revenue loss is another consequence of drivers looking unsuccessfully for parking space,
and it also has various negative side effects:
• Cities often lose revenue: As a result of inadequate parking meter enforcement and no-
parking, no-standing, and loading-zone violations, cities lose revenue.
• Parking administration employee productivity suffers: Employees waste time roaming
the streets, attempting to detect parking rules offenders.
• Parking availability affects income: Local shops and businesses lose customers because
of the decreased accessibility caused by parking space shortages.
Smart Parking Architecture
• A variety of parking sensors are available on the market, and they take different approaches
to sensing occupancy for parking spots.
• Examples include in-ground magnetic sensors, which use embedded sensors to create a
magnetic detection field in a parking spot; video-based sensors, which detect events based
on video computing (vehicle movements or presence); and radar sensors that sense the
presence of vehicles (volumetric detection).
• Most sensors installed in the ground must rely on battery power, since running a power
line is typically too expensive.
• In larger (for example, outdoor) environments, a longer-range Low Power Wide Area
(LPWA) protocol is common, as shown in Figure 5.18.

Figure 5.18 Connected Parking Architecture

• Parking sensors are typically event-driven objects.
• A sensor detects an event and identifies it based on time or analysis.
• The event is transmitted through the device’s communication protocol to an access point
or gateway, which forwards the event data through the city layer.
• The gateway sends it to the cloud or a fog application, where it is normalized.
• An application shows the parking event on operator dashboards, or personal smart
phones, where an action can be taken.
• For example, a driver can book a nearby parking spot, or a parking operator can remove it
from the list of available parking spaces in target locations.
• This action triggers data to be sent back to the parking sensor to modify its availability
status based on the received instructions.
• smart parking has three users that applications must support through aggregated data: city
operators, parking enforcement personnel, and citizens.
• The true value of data normalization is that all parking data, regardless of technology or
vendor, would be visible in these applications for the different users to support their
particular experiences.
• The following are some potential user experiences for these three user types.
1) City operators: These users might want a high-level map of parking in the city to maintain
perspective on the city’s ongoing parking situation.
• They would also need information on historical parking data patterns to understand
congestion and pain points in order to be able to effectively influence urban planning.
2) Parking enforcement officers: These users might require real-time updates on parking
changes in a certain area to be able to take immediate action on enforcement activities,
such as issuing tickets or sending warnings to citizens whose time is nearing expiration.
• Their focus is driving revenue creation for the city and minimizing wasted time by
performing parking monitoring and enforcement at scale
3) Citizens: These users might want an application with a map (such as a built-in parking app
in their car) showing available parking spots, reservation capabilities, and online payment.
• Their focus would be on minimizing the time to get a parking spot and avoiding parking
tickets.
• The application could warn when parking duration limits approach, allowing the driver to
move the vehicle before the timer expires or pay a parking timer extension fee without
having to go back to the vehicle.
Smart Traffic Control
• Traffic is one the most well-understood pain points for any city.
• It is the leading cause of accidental death globally, causes immense frustration, and heavily
contributes to pollution around the globe.
• A smart city traffic solution would combine crowd counts, transit information, vehicle
counts, and so on and send events regarding incidents on the road so that other controllers
on the street could take action.
Smart Traffic Control Architecture
• In the architecture shown in Figure 5.19, a video analytics sensor computes traffic events
based on a video feed and only pushes events (the car count, or metadata, not theindividual
images) through the network.
• These events go through the architectural layers and reach the applications that can drive
traffic services.
• These services include traffic light coordination and also license plate identification for toll
roads.
• Some sensors can also recognize abnormal patterns, such as vehicles moving in the wrong
direction or a reserved lane. In that case, the video feed itself may be uploaded to traffic
enforcement agencies.

Figure 5.19 Smart City Traffic Architecture

• Other types of sensors that are part of traffic control solutions include Bluetooth vehicle
counters, real-time speed and vehicle counters, and lighting control systems.
• These sensors provide a real-time perspective while also offering data collection services
for historical data trending and correlation purposes.
Smart Traffic Applications
• Traffic applications can be enabled to take immediate action with other sensors to manage
traffic and to reduce pain points. Historical data can be used to develop more efficient urban
planning to reduce the amount of traffic a city experiences.
• A common traffic pain point is stop-and-go, where traffic flow suddenly comes to a halt
and then flows again.
• This wavelike traffic pattern is a natural result of the unpredictability of the traffic speed
ahead and has long been studied by public and private organizations.
• A well-known remedy for stop-and-go traffic is to regulate the standard flow speed based
on car density.
• As density increases, car speed is forced down to avoid the wave effect.
• An application that measures traffic density in real time can take action by regulating the
street light cycle duration to control the number of cars added to the flow of the main routes,
thus limiting or suppressing the wave effect.
• From the driver’s standpoint, there is a wait time before being able to get on the highway
or main street, and traffic on the main route is slow but steady.
• The impression is that traffic is slow but moving, and the overall result is a better commute
experience, with lowered and less stressful commute time, as well as a reduced number of
accidents.
Connected Environment
• As of 2017, 50% of the world’s population has settled on less than 2% of the earth’s surface
area.
• Such densely populated closed spaces can see spikes in dangerous gas molecules at any
given moment.
• More than 90% of the world’s urban population breathes in air with pollutant levels that
are much higher than the recommended thresholds, and one out of every eight deaths
worldwide is a result of polluted air.
The Need for a Connected Environment
• Most large cities monitor their air quality.
• Data is often derived from enormous air quality monitoring stations that are expensive
and have been around for decades.
• These stations are highly accurate in their measurements but also highly limited in their
range, and a city is likely to have many blind spots in coverage.
• Given the price and size of air quality monitoring stations, cities cannot afford to purchase
the number of stations required to give accurate reports on a localized level and follow the
pollution flows as they move through the city over time.
• To fully address the air quality issues in the short term and the long term, a smart city would
need to understand air quality on a hyper-localized, real-time, distributed basis at any given
moment. To get those measurements, smart cities need to invest in the following:
• Open-data platforms that provide current air quality measurements from existing
air quality monitoring stations
 • Sensors that provide similar accuracy to the air quality stations but are available at
much lower prices
• Actionable insights and triggers to improve air quality through cross domain
actions
• Visualization of environmental data for consumers and maintenance of historical
air quality data records to track emissions over time.
Connected Environment Architecture
• Figure 5.20 shows an architecture in which all connected environment elements overlay
on the generalized four-layer smart city IoT architecture.

Figure 5.20 Connected Environment Architecture

• As shown in Figure 5.20 , at the street layer there are a variety of multivendor sensor

offerings, using a variety of communication protocols.

• Connected environment sensors might measure different gases, depending on a city’s
particular air quality issues, and may include weather and noise sensors.
• These sensors may be located in a variety of urban fixtures, such as in street lights, as
explained earlier.
• They may also be embedded in the ground or in other structures or smart city
infrastructure.
• Even mobile sources of information can be included through connected wearables that
citizens might choose to purchase and carry with them to understand the air quality around
them at any given moment.
• Crowd sourcing may make this information available to the global system.
• Communication technologies depend on the location of the sensors.
• Wearables typically communicate via a short-range technology (such as Bluetooth) with a
nearby collecting device (such as a phone).
• That device, in turn, forwards the collected data to the infrastructure (for example,through
cellular data).
• Sensors that are installed in urban fixtures also use a variety of communication
technologies.
• Sensors included in street lighting systems may utilize the same communication
infrastructure as the street light control application.
• In addition to all the air quality sensor and wearable data, the data center layer orapplication
layer represented on the left side of Figure 5.20 also receives the open data from existing
weather stations as an additional data input.
• All these data inputs come together to provide a highly accurate sense of the air quality in
the city at any given moment.
Model Questions
QE1) Compare digital and analog temperature sensor
QE2) What is thermistor? What is its role in temperature sensor?
1) What are the things Arduino can do?
2) Explain Arduino UNO Board.
or
Explain Arduino UNO microcontroller with neat sketch
3) Explain how arduino software package is downloading and installation (write steps)
4) List Technical Specification of Arduino UNO
5) Explain the Data types , operators and constants in Arduino programming.
6) Explain Flow control statements in Arduino programming.
7) Explain Digital and Analog input output pins and their usage with respect to Arduino
8) Compare Raspberry Pi model A+, Model B, Model B+ and Model 3.
9) Draw a neat diagram for Raspberry Pi GPIO pins .
10) Explain Raspberry Pi learning Board.
11) Explain configuring RaspberryPi microcontroller.
12) Explain different categories of Raspberry operating system.
13) Write a python program to check for Armstrong number
14) Describe DS18B20 Temperature Sensor.
15) Give technical specifications of DS18B20 Temperature Sensor along with PIN
Diagram
16) Explain Pi via SSH.
[Type here] [Type here] [Type here]

17) Write a program to access temperature from DS18B20 sensor.

or

Write a python code to read temperature value in centigrade (Celsius) and

Fahrenheit formfrom DS18B20 sensor connected to Raspberry pi
microcontroller.

18) Explain Smart City IoT Architecture with a neat diagram.

19) Explain Smart City Security Architecture with a neat diagram.

[Type here] [Type here] [Type here]