Internet of Things - block buildings Unit 2.pptx

Internet of Things - block buildings

1. Unit 2 IoT BUILDING BLOCKS – HARDWARE REQUIREMENTS Building blocks of an IoT system, the Smart Things- smart sensor, smart communicator, smart actuator-Controller, IoT Gateway, layered Architecture, network-cloud services- IoT analytics. Sensor fundamentals- Classification, sensor anatomy, principles of sensors, wireless sensors networks, architecture-types-characteristics-architecture of WSN Communication protocol stack . CO2: Learn and build the IoT blocks.

2. Building blocks of an IoT system.

3. Smart thing conceptual model.

4. Smart thing components Smart Thing Sensor : sensor is a device that translates the received stimulus (a quantity, property, or condition/state of a physical object) into an electrical signal. IoT smart things: temperature sensor, humidity sensor, proximity sensor, motion sensor, gyroscope sensor, rain sensor, gas and smoke sensor, pressure sensor, light sensor, iris motion sensor, alcohol sensor, etc. Smart Thing Communicator : Different types of wireless networks including Wi‐Fi, Bluetooth, ZigBee, Long Range Wide Area Network ( LoRAWAN ), etc. enable the connectivity of smart things to the IP‐based network infrastructure through IoT Gateways. Smart Thing Actuator : Actuators as a complement to sensors are required to take actions, based on sensor readings. Actuators are electronic/mechanical components or devices of an IoT system that perform direct/indirect physical actions on the environment to control a certain mechanism Smart Thing Controller: IoT applications demand more than just adding a sensor to a physical thing, i.e. a Microcontroller (MCU).

5. Microcontroller (MCU) An MCU contains one or more processors, memory, programmable input/output peripherals on a single integrated circuit. MCUs are designed for embedded applications. ● MCUs have a specific amount of RAM. ● MCUs have flash memory to store offline data. ● MCUs have input/output pins (ranging from 1s to 100s) to connect sensors/actuators to MCU. ● MCUs have Ethernet/Wi‐Fi ports for Internet connectivity. ● MCUs are generally available in a number of bits that ultimately affect the speed of computation. ● MCUs have power supply pins to supply power to attached sensors. There are a number of development boards, and MCUs are available from different companies, i.e. Arduino, Raspberry Pi, Samsung, etc. ● Easy availability and compatibility of development board to support sensors of your application. ● Sufficient memory to execute your IoT application. ● Energy‐efficient architecture and cost of development board to implement IoT system. ●

6. ● Sensing and actuating capabilities. ● Processing is the capability. ● Networking capability ● Shielding ability ● Logging ● Self‐awareness capability ● Self‐management capability

7. The IoT Gateway IoT gateway can be a dedicated physical device or software that assists connectivity between devices and Cloud. IoT gateway is responsible for the collection, pre‐processing, filtering, storage, analysis, and secure transmission of data from sensor nodes to IoT Cloud.

8. The IoT Gateway Pre‐processing - large volumes of sensor data -compression of aggregated data to reduce transmission costs. IoT gateway performs the translation of different network protocols to support the interoperability of smart things and connected devices . IoT gateways provide certain levels of security through advanced encryption networks. Therefore, as a middle layer (between devices and Cloud), IoT gateways protect the IoT system from unauthorized access and malicious attacks. IoT gateway technology architecture consists of various hardware components and software modules . H ardware components: MCUs (processors), wireless connectivity modules (i.e. Wi‐Fi, ZigBee, Bluetooth, 2G/3G/4G, etc .). Software modules: Linux and Android OSs can be used, however, RTOS is preferred. Security is implemented in the form of Crypto Authentication chips. IoT gateway is responsible for the collection, pre‐processing, filtering, storage, analysis, and secure transmission of data from sensor nodes to IoT Cloud.

9. IoT cloud architecture Network infrastructure enables the processing and transmission of data from smart things to IoT Cloud through several network devices, i.e. switches, routers, and gateways. IoT Cloud - virtualization technology and consists of different components, i.e. Virtual Resource Pool and three major types of VM‐based configured servers. Virtual Resource Pool consists of two components Hardware resources CPUs , memory, and network connectivity on physical machines. Hypervisor software provide OS environment (known as VMs) and enable dynamic resource allocation. Application Servers in IoT Cloud comprises of both Hypertext Transfer Protocol (HTTP) servers and Message Queuing Telemetry Transport (MQTT) servers. Database servers are optional and depending on the nature of IoT application, the data is stored in relational (SQL) and non‐relational (NoSQL) databases. Load‐balancing Servers are essential and beneficial in IoT Cloud as these: ● process requests in a scheduled way. ● distribute the workload on application/database servers. ● avoid congestion on application/database servers. ● achieve maximum utilization of available resources.

10. IoT Analytics IoT analytics is the process of the formation of useful interpretations for trend forecasting. Predictive analysis of IoT Cloud data can be used for preventive measures as well as for improving products and services . ● Acquiring of IoT data through sensors ● Dealing with heterogeneous as well as real‐time nature of sensed data ● Refinement/elimination of noise through the implication of statistical and probabilistic techniques on sensed heterogeneous data ● Spatiotemporal dependencies of IoT data streams ● Biasedness of IoT data demands pre‐processing (i.e. understanding and scrutiny of training and test datasets) ● Security/privacy requirements necessitate pre‐processing of personal data .

11. IoT Analytics Tools and Techniques

12. IoT Analytics Tools and Techniques

13. IoT Analytics Life Cycle IoT Data Collection Phase: This first phase of the IoT analytics life cycle deals with the collection of IoT data from heterogeneous devices at IoT Cloud. IoT Data Unification Phase: The second phase deals with the validation and refinement of IoT sensed data in terms of integrity, consistency, and accuracy. IoT Data Analysis Phase: This is the third phase of the IoT analytics life cycle and deals with the structuring, storage, and analysis of data through the implications of machine learning and data mining techniques that transform IoT data into actionable knowledge. IoT Operational and Reuse Phase: This fourth phase deals with the actual implementation and operational details of analysis on IoT data. It also supports the visualization and reusability of IoT datasets.

14. Sensor fundamentals T he sensor is a device - to receive and respond to a stimulus (for example, variation in any natural phenomenon, i.e. temperature, pressure, humidity, motion, position, displacement, sound, force, flow, light, chemical presence, etc.). The following is the classification of a few basic types of stimuli: ● Electric Stimuli: Charge, Electric Field, Current, Voltage, etc. ● Magnetic Stimuli: Magnetic Field, Magnetic Flux, Magnetic Flux Density, etc. ● Thermal Stimuli: Temperature, Thermal Conductivity, etc. ● Mechanical Stimuli: Velocity, Position, Acceleration, Force, Density, Pressure, etc. The sensor output is ultimately required to be compatible with electronic circuits. A sensor can be considered as an energy converter, which actually measures the transfer of energy from and into an object under observation. Concerning energy conversion, the sensor must be differentiated from the term transducer, which is merely used to convert one form of energy to any other form of energy.

15. Difference between sensor, actuators, and transducer .

16. Sensor Classification ● Simple (Direct) Sensors Versus Complex Sensors ● Active Sensors Versus Passive Sensors ● Contact Sensors Versus Noncontact Sensors ● Absolute Sensors and Relative Sensors ● Digital Sensors Versus Analog Sensors (based on output) ● Scalar Sensors Versus Vector Sensors (based on data types)

17. Anatomy of Sensors Sensing elements are hardware devices -to measure any physical stimulus (i.e. light, temperature, sound, etc.) in the environment to collect concerned data. The sensor generates a continual analog signal, which is required to be digitized before transmitting it to the controllers for further processing. ADC is required, which performs the conversion of an analog signal to the digital signal. A microcontroller having the processing unit is responsible for the processing of received digitized sensed data and controlling other functions of a sensor node. The most common controller is a microcontroller that is used in sensor nodes because of its low power consumption, low cost, and flexibility to connect other devices. Field Programmable Gate Arrays (FPGAs) and Application‐Specific Integrated Circuits (ASICs) are other alternatives, which can be used as a controller in sensor nodes. The processing unit is generally associated with storage memory. A transceiver is required to connect the sensor nodes to other nodes in the network for the transmission and reception of required data. Mostly, the Industrial, Scientific and Medical (ISM) band is preferred in sensors to use free radio and three common communication schemes, i.e. optical communication (laser), Infrared (IR), and radio frequency (RF ).

18. Physical Principles of Sensing The world around us is full of information, but it's not always in a form we can easily understand. Sensing is the process of detecting and measuring physical quantities like temperature, pressure, light, and sound . These measurements are crucial for countless applications, from everyday devices like smartphones to advanced technologies like self-driving cars. To understand how sensing works, we need to delve into the underlying physical principles . Three key principles: capacitance, electric resistance and resistivity, and the piezoelectric effect .

19. Physical Principles of Sensing The conversion of physical effects into an electrical signal is based on various basic principles of Physics, i.e. capacitance, magnetism, piezoelectric effect. Mechanical sensors, such as pressure sensors and accelerometers, use the movement of a physical object to generate a signal . Optical sensors, such as light detectors and cameras, use light to measure properties. Thermal sensors, such as thermometers, measure temperature by sensing the heat energy of an object .

20. Capacitance Sensors: Sensing Liquid Levels, Proximity, and Pressure Capacitance sensors utilize the principle of capacitance to detect changes in the environment. These sensors work by measuring the capacitance between two electrodes. Changes in the dielectric material between these electrodes, caused by variations in the surrounding medium, affect the capacitance. This change in capacitance is then converted into an electrical signal, providing information about the sensed environment. Liquid Level Sensing Capacitance sensors can be used to measure the level of liquids in tanks and other containers. The change in capacitance due to the presence of the liquid is proportional to the liquid level. Proximity Sensing Capacitance sensors can detect the presence of an object without physical contact. As an object approaches the sensor, the capacitance changes, providing a signal indicating the object's proximity. Pressure Sensing Capacitance sensors can also be used for pressure sensing. The pressure applied to a diaphragm affects the capacitance, which is then measured and converted into a pressure reading.

21. Capacitance Sensors: Advantages and Applications Capacitance sensors offer several advantages over other types of sensors, including their sensitivity, high speed, and non-contact operation. These benefits make them suitable for a wide range of applications, from touch screen technology to industrial automation. Capacitance sensors can detect very small changes in the environment, making them highly sensitive to variations in capacitance. Capacitance sensors can respond quickly to changes in the sensed environment, allowing for rapid measurement and data acquisition Capacitance sensors can operate without physical contact with the measured object, making them suitable for applications where contact is undesirable or impractical. Capacitance sensors find applications in various fields, including touch screen technology, liquid level sensing, proximity detection, and pressure measurement.

22. magnetism & electricity Number of turns in the coil Current variation in coil Movement of the magnetic field source Changing the magnetic source area

23. Magnetism and Induction Magnetism and electricity are associated with each other in such a way that moving charges are able to produce a magnetic field and from the magnetic field it is possible to generate electricity.

24. Magnetic Sensing Examples Eddy current-based proximity sensor . Hall sensor-based fuel detection.

25. Resistive Sensors: Sensing Temperature, Strain, and Light Resistive sensors rely on the change in resistance of a material due to variations in physical parameters. These sensors typically consist of a resistive element, often a wire or a semiconductor, whose resistance changes with the measured quantity. The resistance change is then converted into an electrical signal, providing information about the sensed parameter. Temperature Sensing Thermistors and resistance temperature detectors (RTDs) are common examples of resistive sensors for temperature measurement. Their resistance changes with temperature, allowing for precise temperature readings. Strain Sensing Strain gauges are resistive sensors used to measure strain, which is the deformation of a material under stress. Their resistance changes proportionally to the applied strain, providing a measure of the material's deformation. Light Sensing Photoresistors, also known as light-dependent resistors (LDRs), are resistive sensors whose resistance decreases with increasing light intensity. They are used in light-sensitive circuits, such as those found in automatic streetlights.

26. Electric Resistance and Resistivity Resistance -measure of how much a material resists the flow of electricity . -material's resistivity, length, and cross-sectional area. Higher resistivity means greater resistance. Longer wires offer more resistance. Thicker wires have less resistance . Resistivity Resistivity is a material property It's independent of the material's shape or size. Good conductors like copper have low resistivity. Insulators like rubber have high resistivity. Resistivity can change with temperature . Resistors are used to control current flow in circuits . Resistivity is used to design heating elements and sensors. Understanding resistance and resistivity is essential for designing efficient and reliable electronic systems.

27. Piezoelectric Effect The piezoelectric effect is a fascinating phenomenon that links mechanical stress to electrical charge. Certain materials, like quartz and ceramics , exhibit this unique property. When these materials are subjected to mechanical stress, such as compression or bending, they generate an electric charge across their surface. Conversely , applying an electric field to these materials causes them to deform. This bidirectional relationship between mechanical stress and electrical charge makes piezoelectric materials ideal for various sensing and actuation applications

28. Piezoelectric Sensors: Sensing Pressure, Vibration, and Acceleration Sensor Type Application Pressure Sensors Blood pressure monitoring, tire pressure gauges, industrial process control Vibration Sensors Machine health monitoring, structural integrity assessment, seismic monitoring Acceleration Sensors Airbag deployment systems, motion detectors, inertial navigation systems

29. Piezoelectric Sensors: Advantages and Applications Piezoelectric sensors offer several unique advantages, including their high sensitivity, robustness, and wide operating temperature range. These characteristics make them ideal for a variety of applications, from medical devices to industrial automation and aerospace systems . 1 High Sensitivity Piezoelectric sensors are highly sensitive to mechanical stress, allowing them to detect even subtle changes in pressure, vibration, or acceleration. 2 Robustness Piezoelectric sensors are typically robust and can withstand harsh environments, making them suitable for demanding applications. 3 Wide Operating Temperature Range Piezoelectric materials can operate over a wide range of temperatures, making them suitable for use in various environments. 4 Wide Range of Applications Piezoelectric sensors find applications in fields like medical devices, automotive systems, aerospace systems, and industrial automation.

30. Wireless Sensor Networks (WSN) Wireless sensor networks (WSNs) consist of spatially distributed autonomous devices that monitor physical or environmental conditions. These devices communicate wirelessly with each other and a central base station to collect and transmit data. WSN is defined as an infrastructure‐less and self‐configured network consisting of thousands of tiny low power sensor nodes, which are able to monitor physical conditions and communicate wirelessly to transfer collected data to the required destination

31. Types of WSNs ● Wireless Body Area (Sensor) Networks (WBAN/WBASN): Networks of implanted and on‐ body sensors to monitor vital signs of the human body. ● Terrestrial WSN: A typical WSN in which a number of sensor nodes are capable to transmit data to the sink or base station. ● Multimedia WSNs: These sensor networks are able to monitor real‐time events in the form of multimedia, i.e. images, audio, video, etc. ● Underground WSN: WSN consists of sensor nodes to monitor changes beneath the earth and demands additional above ground sink nodes to transmit acquired data to the destination. ● Underwater WSNs: Sensor networks consist of sensor nodes undersea and dynamic anchor nodes at sea surface to collect gathered data. Underwater WSNs face the challenging environment of underwater communication with long propagation delay and low bandwidth. ● Mobile WSNs: WSN consists of mobile sensor nodes to collect data from the physical environment.

32. WSN Architecture Types Star Topology A central base station collects data from all sensor nodes. This topology is simple to implement but vulnerable to single points of failure. Tree Topology Data is routed through a hierarchical structure. This approach provides better scalability but requires more complex routing protocols. Mesh Topology Nodes communicate with multiple neighbors, creating redundant paths for data transmission. This topology offers robustness and scalability but requires more complex routing protocols.

33. Characteristics of WSNs 1 Scalability WSNs can be scaled up or down to accommodate different application requirements. 2 Energy Efficiency Sensor nodes operate on limited battery power, requiring efficient energy management techniques. 3 Reliability WSNs must operate reliably in harsh environments, with data loss minimized through redundancy and error correction. 4 Security Protecting sensitive data and preventing unauthorized access is crucial in WSNs. Severe power (energy) constraints Limited memory and computing capabilities Narrow communication bandwidth and short communication range Lack of global identifications Limited mobility Heterogeneity/Homogeneity of nodes Self‐organizing and self‐healing (ability to manage node failures) Ability to withstand extreme environmental conditions ● Application dependent ● Distinct (Random as well as Manual) deployment strategies

34. Protocol Stack of WSNs

35. The traditional User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) protocols cannot be directly implemented to the WSN due to the following reasons ● UDP is unreliable. ● TCP connection‐oriented overhead is not suitable to WSNs. ● TCP degrades the throughput in WSNs because it adjusts data rate to the lowest when packet loss occurs. ● TCP is reliable but due to end‐to‐end retransmission mechanism, energy consumption is high. ● TCP reliable mechanism through acknowledgments is not essential in WSNs.

36. Communication Protocol Stack 1 Physical Layer Responsible for transmitting and receiving data signals over the wireless medium. 2 Data Link Layer Provides error detection and correction mechanisms to ensure reliable data transmission. 3 Network Layer Handles routing and addressing of data packets across the network. 4 Transport Layer Ensures reliable data transfer between applications, providing flow control and segmentation. 5 Application Layer Provides services for specific applications, such as data aggregation, processing, and visualization.

37. Physical Layer: Wireless Transmission The physical layer defines how data is encoded into electromagnetic waves and transmitted over the wireless medium. Different modulation schemes and frequency bands are employed based on the application requirements and environmental conditions.

38. Data Link Layer: Reliable Transmission The data link layer ensures the reliable transmission of data between sensor nodes and the base station. This layer incorporates error detection and correction mechanisms, such as checksums or cyclic redundancy checks, to minimize data corruption during transmission.

39. Network Layer: Routing and Addressing Routing Algorithms Determine the optimal path for data packets to travel from sensor nodes to the base station. Addressing Each sensor node has a unique address for identification and communication. Data Aggregation Combining data from multiple sensor nodes to reduce network traffic and energy consumption.

40. Transport Layer: End-to-End Communication TCP Connection-oriented protocol, providing reliable data delivery with flow control and error checking. UDP Connectionless protocol, offering faster data transmission but without guarantees for delivery or order.

41. Application Layer: Data Processing and Visualization Data Aggregation Combining data from multiple sensor nodes to reduce network traffic and energy consumption. Data Analysis Processing and interpreting sensor data to extract meaningful insights and patterns. Event Detection Identifying and responding to events based on predefined thresholds and patterns in sensor data. Visualization Presenting sensor data in an intuitive and informative way to facilitate understanding and decision-making.

42. Applications of Wireless Sensor Networks WSNs are widely used in various applications, including environmental monitoring, healthcare, industrial automation, agriculture, and smart cities. These networks enable real-time data collection and analysis, empowering informed decision-making and improved efficiency in diverse fields.