IoT Unit 1 pptx ( introduction to Iot )

ppt

1. Introduction to Internet of Things UNIT-1 Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

2. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Contents: Introduction Application areas of IoT Characteristics Things in IoT IoT stack Enabling Technologies IoT Challenges IoT Levels

3. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

4. Introduction to IoT Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I IoT refers to the “interconnection” via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.

5. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I The Internet of things ( IoT ) is the inter-networking of physical devices, vehicles (also referred to as “connected devices” and “smart devices”), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data. “Internet of Things” is a technology, which is used to communicate between human and machine or a machine to machine with the help of “internet”.

6. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I IoT can be defined as the analysis of data to generate a meaningful action, triggered subsequently after the interchange of data. Data is everything, everywhere. Scope is beyond , exchange of meaningful information from 1 device to other to acquire purposeful result.

7. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I IoT is not owned by any one engineering branch. IoT is reality, when multiple domains come together IoT is not a single technology.

8. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Growth of internet from “No where” to “Now Here” IoT enables the objects to be sensed when controlling them remotely, which facilitates better interaction with physical world and computers. This improves efficiency and accuracy with minimal human intervention. Soon one’s life would be governed entirely by IoT in near future.

9. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I These design goals have to be fulfilled while building an Application. Design Goals

10. IoT Growth Prediction

11. Application areas of IoT Smart Home : The cost of owning a house is the biggest expense in a homeowner’s life. Smart homes are promised to save the time, money and energy. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

12. Smart cities : It includes smart surveillance, environment monitoring, automated transformation, urban security, smart traffic management, water distribution, smart healthcare etc. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

13. Wearables: Wearable's are devices that have sensors and software installed which can collect data about the user which can be later used to get the insights about the user. They must be energy efficient and small sized. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

14. Connected cars : A connected car is able to optimize its own operation, maintenance as well as passenger’s comfort using sensors and internet connectivity. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

15. Smart retail : Retailers can enhance the in-store experience of the customers using IoT . The shopkeeper can also know which items are frequently bought together using IoT devices.

16. Smart healthcare : People can wear the IoT devices which will collect data about user's health. This will help users to analyze themselves and follow tailor-made techniques to combat illness. The doctor also doesn't have to visit the patients in order to treat them.

17. Characteristics of IoT Connectivity : Things in I.O.T. should be connected to the infrastructure. Anyone,Anywhere,Anytime connectivity should be guaranteed. Without connection nothing makes sense. Intelligence : Extraction of knowledge from the generated data is important. Like, sensor generate data, and this data should be interpreted properly. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

18. Scalability : The no. of things getting connected to the I.O.T. infrastructure is increased day by day. Hence, an IOT setup shall be able to handle the massive expansion. The data generated is also enormous,and to be hanled . Unique Identity : Each IOT device has an I.P. address. This identity is helpful in tracking the equipment and at times to query its status. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

19. Dynamic and Self-Adapting : The IOT device must dynamically adopt itself to the changing context. Assume a camera meant for surveillance, it may have to work in different conditions and at different light situations. Architecture (Heterogeneity): IoT Architecture cannot be homogeneous in nature. The devices in the IoT are heterogeneous as based on different hardware platforms and networks. They can interact with other devices different networks.

20. Safety : Having got all the things connected with the Internet possess a major threat, as our personal data. Data security It can be tampered with, if proper safety measures are not taken. Equipment safety

21. Things in IoT Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

22. Things in IoT Things refer to a variety of devices. To qualify as a thing::it requires identity of its existence. The thing in a network can monitor/measure. Things are capable of exchanging data with other connected devices in the system. The data could be stored in a centralized server (or cloud),processed there and a control action could be initiated. The devices involved in getting this accomplished are known as things. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

23. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I ‘Things’ refers to these machines or physical objects so it becomes important to understand what kind of objects can be connected via Internet. Objects with intelligence or  Smart Objects . Objects without intelligence or  Non-Smart Objects

24. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I   Smart Objects: Smart objects are those physical and digital objects which can be identified, have sensing/actuating capabilities, processing and calculating powers, also storing, and networking capabilities. smartphones ,smart fridge, Smart TV, Alexa voice assistant, micro-controllers like Arduino can be easily seen.

25. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I   Non- Smart Objects: Non-smart objects are generally those objects which do not have intelligence and processing capabilities. Sensors and actuators are non-smart devices.

26. Things in IoT Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I “Things”= Hardware + Software + Service

27. Example of IoT -based home automation Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

28. Home automation components The major components can be broken into: IoT Sensors IoT Gateways IoT Protocols IoT Firmware IoT Cloud and Databases IoT Middleware (if required) Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

29. An IoT gateway is a centralized hub that connects IoT devices and sensors to cloud-based computing and data processing. Modern IoT gateways often allow bidirectional data flow between the cloud and IoT devices. IoT devices communicate with each other over the network, so certain standards and rules need to be set to determine how data is exchanged. These rules are called IoT Network Protocols.

30. Short Range Communication, Low Data Rate, Low Power Bluetooth Zigbee 6LoWPAN PAN stands for Personal Area Network, and 6LoWPAN refers to IPV6 Low Power PAN Short Range Communication, High Data Rate WirelessLAN - Wi-Fi Long Range Communication, High Data Rate, Low power LoRaWAN LTE-M stands for Long Term Evolution for Machines. Long Range, Low Data Rate, Low Power Consumption Sigfox is used when wide area coverage is required with minimum power consumption. It aims at connecting billions of IoT devices. Long Range, Low Data Rate, High Power Consumption Cellular,This is also known as a mobile network.

31. Firmware is a microcode or program that is embedded into the memory of hardware devices to help them operate. It enables hardware like cameras, mobile phones, network cards, optical drives, printers, routers, scanners, and television remotes to function smoothly. Middleware is software that different applications use to communicate with each other. It provides functionality to connect applications intelligently and efficiently so that you can innovate faster.

32. Major IoT platform as a service provider: AWS IoT Azure IoT Thingworx Ubidots Thingspeak Carriots Konekt TempoIQ Xively IBM Bluemix Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

33. Home Automation Sensors We will break down IoT sensors for home automation by their sensing capabilities: Temperature sensors Lux sensors Water level sensors Air composition sensors Video cameras for surveillance Voice/Sound sensors Pressure sensors Humidity sensors Accelerometers Infrared sensors Vibrations sensors Ultrasonic sensors Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

34. Home Assistant for smart home development Supports RaspberryPi , uses Python with OS as Hassbian . Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I

35. IoT Stack Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I This digital technology also has defined layers like OSI model with 7 layers. Each layer has the protocols defined clearly with appropriate hardware/software working for it.

36. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 1(physical/Sensor Layer): This layer is concerned about the physical components. Sensors are the core components. Actuators in industrial automation. This layer is responsible for data collection(i.e., sensing). Choose appropriate sensor(temperature sensors,Humidity sensors,Pressure sensors etc )

37. A PLC (Programmable Logic Controller) is used to automate industrial processes by controlling actuators, which can include pneumatic devices, to execute specific actions based on programmed logic.

38. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 2(Processing and control action Layer): This layer has core components for IoT . Microcontrollers or processors are found this layer. To determine if data is meaningful, a microcontroller is required. Data from sensors are received by microcontrollers development kits like: Aurdino NodeMCU PIC(Peripheral Interface Controller) ARM(Advanced RISC Machines) Operating Systems play major role: Android,IOS,Linux

39. A microcontroller is  a compact integrated circuit designed to govern a specific operation in an embedded system . A typical microcontroller includes a processor, memory and input/output (I/O) peripherals on a single chip.

40. Different types of microcontrollers and development platforms. Arduino: Arduino is an open-source electronics platform based on easy-to-use hardware and software. It consists of microcontroller boards with various capabilities and a user-friendly development environment. Arduino boards are designed for beginners and hobbyists to create projects and prototypes. Arduino boards typically use Atmel AVR microcontrollers, and they come with various digital and analog I/O pins for connecting sensors, actuators, and other devices. The Arduino IDE provides a simple programming environment for writing and uploading code to the boards. NodeMCU : NodeMCU is an open-source IoT (Internet of Things) platform based on the ESP8266 WiFi module. It provides a firmware and development environment that allows developers to build WiFi -enabled projects and applications. NodeMCU is based on the Lua scripting language and provides built-in WiFi connectivity, making it suitable for creating IoT projects that require wireless communication. It's often used for home automation, sensor networks, and other connected applications. PIC (Peripheral Interface Controller): PIC is a family of microcontrollers developed by Microchip Technology (formerly Microchip Technology Inc.). PIC microcontrollers are widely used in various applications due to their low power consumption and versatility. PIC microcontrollers come in a range of models with different features and capabilities. They are used in a variety of industries, including automotive, industrial, consumer electronics, and more. Development tools and software libraries are available to facilitate programming and development for PIC microcontrollers.

41. ARM (Advanced RISC Machines) is a family of microprocessor architectures that are widely used in various embedded systems, mobile devices, and more. ARM processors are known for their energy efficiency and performance. Features: ARM-based microcontrollers and microprocessors are used in a wide range of applications, from small embedded systems to high-performance computing. ARM-based development boards and platforms are available for various use cases, and they can be programmed using different programming languages and development environments. Each of these platforms has its own strengths and use cases. The choice between them depends on factors such as project requirements, familiarity with the platform, available resources (libraries, tools, documentation), and the level of complexity desired for your projects.

42. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 3(Hardware Interface Layer): This layer include components or interfaces used for communication such as RS232, RS485, SPI, I2C, CAN, SCI etc. Connection and communication. These interfaces are used for serial or parallel communication at various baud rates in synchronous/asynchronous modes. All theses components ensure flawless communication.

43. SPI (Serial Peripheral Interface), CAN (Controller Area Network), and I2C (Inter-Integrated Circuit). These are all widely used communication protocols for connecting and communicating between electronic devices.

44. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 4(Radio Frequency Layer): This radio frequency layer houses RF technologies based on short range or long range and data rate desired by the application of use. The common indoor RF/wireless technologies include Wifi , Bluetooth, Zigbee, Zwave , NFC, RFID etc. The common outdoor RF cellular technologies include GSM/GPRS, CDMA, LTE-M, NB-IoT, 5G etc. RF layer does communication of data using radio frequency based EM waves. There is another technology which uses light waves for data communication. This light based data communication is referred as LiFi .

45. WiFi : A wireless communication technology that enables devices to connect to the internet and local networks using radio waves. Bluetooth: A short-range wireless technology for connecting devices and transferring data over short distances. Zigbee: A low-power wireless communication protocol designed for connecting and controlling devices in home automation and industrial applications. Z-Wave: A wireless technology used for home automation and smart devices, focused on creating a mesh network of low-power devices. NFC (Near Field Communication): A short-range wireless technology allowing two devices to exchange data when brought close together. RFID (Radio-Frequency Identification): A technology using radio waves to identify and track objects or people by attaching small tags to them. Wi-Fi: Wireless Fidelity. Bluetooth: Named after the 10th century Danish king Harald "Bluetooth" Gormsson . Zigbee: Derived from the waggle dance of honeybees. Z-Wave: Developed by Zensys , representing a "wave" of RF communication. NFC: Near Field Communication. RFID: Radio Frequency Identification.

46. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 5(Session/Message Layer): This layer deals with various messaging protocols such as MQTT, CoAP, HTTP, FTP (or Secured FTP), SSH etc. It defines how messages are broadcasted to the cloud.

47. MQTT (Message Queuing Telemetry Transport): MQTT is a lightweight publish-subscribe messaging protocol often used for efficient communication between devices in IoT applications, allowing devices to publish data and subscribe to topics of interest. CoAP (Constrained Application Protocol): CoAP is a specialized protocol designed for resource-constrained devices in IoT environments, offering lightweight communication for querying and controlling resources. HTTP (Hypertext Transfer Protocol): HTTP (Hypertext Transfer Protocol) is  the set of rules for transferring files -- such as text, images, sound, video and other multimedia files -- over the web . FTP (File Transfer Protocol) / SFTP (Secure File Transfer Protocol): FTP is the traditional file transfer protocol. It's a basic way of using the Internet to share files.  SFTP (or Secure File Transfer Protocol) is an alternative to FTP that also allows you to transfer files, but adds a layer of security to the process . SSH is a network protocol used for secure remote access and control of devices over an unsecured network, providing encrypted communication and authentication. Each of these protocols serves specific purposes and is suitable for different types of applications and scenarios, ranging from IoT communication and resource-constrained devices (MQTT, CoAP) to web communication (HTTP), secure file transfer (FTP/SFTP), and secure remote access (SSH).

48. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 6(User Experience Layer): This layer deals with providing best experience to the end users of IoT products. To fulfill this, this layer takes care of rich UI designs with lots of features. Various languages and tools are developed for the design of GUI interface softwares . These include objected oriented and procedure oriented technologies as well database languages (DBMS, SQL) in addition to analytics tools.

49. Department of CSE – Data Science, School of Engineering IoT Analytics UNIT-I Layer 7(Application Layer): This layer utilizes rest of the six layers in order to develop desired application. The typical case studies or applications of IoT are as follows.

50. GSM/GPRS (Global System for Mobile Communications / General Packet Radio Service): GSM is a widely used standard for cellular networks, providing voice and basic data services. GPRS is an extension of GSM that enables packet-switched data transmission for activities like internet browsing and email. CDMA (Code Division Multiple Access): CDMA is a digital cellular technology that uses spread-spectrum techniques for communication. It allows multiple users to share the same frequency band by assigning unique codes to each user. LTE-M (Long-Term Evolution for Machines): LTE-M is a low-power, wide-area network technology designed for the Internet of Things (IoT). It provides a balance between coverage, data rate, and power consumption, making it suitable for IoT devices. NB-IoT (Narrowband Internet of Things): NB-IoT is another low-power, wide-area network technology optimized for IoT. It operates in narrow frequency bands and offers extended coverage and improved power efficiency for IoT devices. 5G (Fifth Generation): 5G is the latest generation of cellular network technology, promising faster data speeds, lower latency, and support for a massive number of connected devices. It aims to enable new applications like remote surgery, autonomous vehicles, and smart cities.

51. Smart vegetable quality tracking system using IoT It starts with sensor layer, where temperature, humidity are measured. Then data goes to the microcontroller; from there to cloud; from here messaging protocols take effect. RF protocols are used for transport and communication. User experience is taken care with the Android application designed.

52. Enabling Technologies Sensors Cloud Computing Big Data Analytics Embedded Computing Boards Communication Protocols User Interfaces

53. Enabling Technologies IoT is collection/group of technologies/devices. Enabling Technologies fall under any of the following categories: Technologies that help in acquiring/sensing data Technologies that help in analyzing/processing data Technologies that help in taking control action. Technologies that help in enhancing security/privacy.

54. 1.SENSORS Sensors are the heart of any IoT application. They're the pieces of an IoT ecosystem that bridge the digital world to the physical world. Sensors could be analog/digital IoT sensors are pieces of hardware that sense and detect changes in an environment and collect data.

55. Some examples: Camera used in home security systems. Weather tracking system uses temperature/humidity/moisture sensors. Vehicle health monitoring sensors keep track of speed,tyre pressure,etc. Water quality is monitored through sensors that measure PH,turbidity,chloride level etc. PIR sensor is used in pedestrian signal operation with human presence detection.

56. 2. Cloud Computing Data storage plays a major role in IoT. Cloud has grown more popular, as it serves as an affordable, effective, efficient medium for data storage. Majority of applications use Adafruit

57. Adafruit.io is needed to display the IOT project's data online in real-time. It is a cloud server that can be used to connect to IoT devices through Wi-Fi and to control these devices through a dashboard. It can be used as a free service and it has got a simple easy-to-use interface to design dashboards.

58. Cloud services are categorized as: IaaS(Infrastructure as a service) Form of cloud computing that provides virtualized computing resources(H/W) over the internet. Ex:AWS EC2, Rackspace ,Google Compute Engine (GCE), Digital Ocean, Microsoft Azure etc. PaaS(Platform as a service) Cloud service provider delivers hardware and software tools needed for App Dev to users over internet. Ex:Google App Engine, OpenShift, Apache Stratos. SaaS(Software as a service) A complete software application is provided to the user. Ex:Google Workspace,Dropbox,ZenDesk etc.

59. IaaS Paas SaaS It provides a virtual data center to store information and create platforms for app development, testing, and deployment. It provides virtual platforms and tools to create, test, and deploy apps. It provides web software and apps to complete business tasks. It provides access to resources such as virtual machines, virtual storage, etc. It provides runtime environments and deployment tools for applications. It provides software as a service to the end-users. It is used by network architects. It is used by developers. It is used by end users. IaaS provides only Infrastructure. PaaS provides Infrastructure+Platform . SaaS provides Infrastructure+Platform +Software.

60. A SaaS model provides cloud-based tools and applications to consumers and businesses, whereas a PaaS model allows them to host, manage, and secure their own applications and IaaS allows organizations to manage their business resources like network, server, and data storage. SaaS helps you to eliminate the need to have IT staff download and install applications on each computer, while PaaS provides freedom to build the software without the need to worry about software updates. IaaS delivers cloud computing infrastructure through virtualization technology. The SaaS model is used by end users, while developers use PAAS, and network architects use the IaaS model.

61. 3. Big Data Analytics Data is everywhere, and from every function or operation,we get more data. Biggest challenge with Big Data is its V’s: Volume Variety Velocity Veracity Biggest challenge with Big Data is its V’s: Volume Variety Velocity Veracity

62. Who is generating all this data?

63. Sensors from security systems, weather monitoring systems, car/navigation systems, wearables, industrial equipment, social media etc Data analytics is one of the enabling technologies for building a complete and comprehensive IoT applications.

64. 4. Embedded Computing Boards An Embedded Computing Board is a very important component to bring IoT design to reality. An  Embedded Computer  is a small-sized, compact, powerful and easy-to-operate electronic module, based on microcontroller/microprocessor and act as a bridge between electronics hardware and computer software. Some of the Boards: Raspberry Pi Arduino NodeMCU Intel Edison etc

65. Raspberry Pi

66. Arduino

67. NodeMCU Intel Edison All these boards are small,yet smart. Minimum cost < 100$

68. 5. Communication Protocols Data exchange happens through these protocols, which takes care of: Addressing Format of the messages. Message security. Routing Flow control Error monitoring Sequencing Retransmission guidelines Segmentation of data packets Protocols are the pillars for good Iot infrastructure.

69. 6. User Interfaces All devices must have an intuitive user interface. IoT services should be designed in such a way that accessing and handling the services are easier and comfortable for the end user. Like providing mobile/web Applications which are consistent and not clumpsy .

70. IoT Challenges Technical and Non-Technical challenges: Security/Personnel safety Data and personnel Privacy Permissions Data extraction with consistency from complex environments . 24 /7 Internet Connectivity Wired and wireless Power requirements Green power sources Complexity involved Due to integration of different domains. Lack of Expertise Storage Need , Cost, Identify Service Provider, Type of cloud

71. IoT Levels Based on architectural approach, there are 5 levels

72. Level 1 It is of minimal complexity and the easiest to build. The data sensed is stored locally and the data analysis is done locally. Monitoring /control is done through an application(. apk or webapp ). Data generated in this level application is not huge(i.e., no big data). All the control happens through internet.

73. Level 2 Slightly more complex than previous level. Here data is voluminous, so cloud is required. Sensing frequency is faster, and no. of times sensing done is much more than previous level. Local analysis and triggers action through mobile/web Storage only

74. Level 3 Difference is, data analysis is carried out on cloud. Based on data analysis, control action can be triggered through mobile/web app. Ex: agricultural applications, room freshening solutions based on odour data analysis

75. Level 4 With every passing level, the volume of data increases and sensing rate also increases . At this level, multiple and independent nodes are present, which uploads data to cloud, where storage and analysis is carried out. Based on data analysis, control action can be triggered through mobile/web app. storage and analysis

76. Level 5 Amount of data is extensive, sensing frequency is much faster. At this level, multiple and independent nodes are present . Data sensing and storage is same as previous level. Based on data analysis, control action can be triggered through mobile/web app. When an application is completely cloud oriented, it is computationally intensive in real time.