Internet of Things I - Lecture 2

Internet of Things I - Lecture 2

• IoT General Enablers are the foundational components enabling IoT systems
• Ubiquitous computing involves real-life objects that sense, communicate, analyze, and act based on the situation.
• Key general enablers include miniaturization, portability, ubiquitous connectivity, integration of diverse devices, and pervasive digital ecosystems (like the cloud).
• The five stages of IoT functional view/information value loop are data creation, communication, aggregation, analysis, and action. These stages are crucial for achieving set goals.

IoT Enabling Technologies

• Identification and Sensing Technologies: Develop devices (sensors) converting physical stimuli into electronic signals.
• Wireless Communication and Networking: Enable electronic signal communication between devices. This includes specific technologies like RFID (with components tag, interrogator, and controller). Different communication types (like Radio Frequency Identification) are important to understanding data transmission.
• Aggregation Standardizations: Enable efficient data processing and interoperability of aggregated data sets.
• Augmented Intelligence: Analytical tools improve the ability to describe and predict relationships among sensed data.
• Augmented Behavior: Technologies and techniques improve compliance with prescribed actions.

IoT Identification and Sensing Technologies

• Identification methods provide unique object identities within a network, typically through public IP addressing.
• Sensing in IoT involves originating data from interconnected smart things using sensors and actuators.
• Sensors produce electrical, optical, or digital data from the physical environment for interpreting information for intelligent devices or people.
• Actuators convert electronic signals to non-electronic energy to complete a feedback loop.

Wireless Communication and Networking

• Wireless communication and networking are pivotal for IoT functioning.
• Wireless Identification and Sensing Technologies (WIST) is an important term for RFID based sensors and WSNs.
• A typical RFID system consists of an RFID tag (Transponder or Smart Label), an interrogator (Reader), and a controller (Host).
• Active RFID tags have an on-board power source, offering advantages like range and high data transmission.
• Passive RFID tags rely on external power sources, they are more affordable but less versatile.
• RFID, sensors, and RFID sensors connect to the internet through heterogeneous network devices (like Bluetooth, Access Points, Wi-Fi routers, Gateways, etc).
• A unique IP address is needed for each smart thing.
• IoT strongly relies on continuous connectivity.

Aggregation Standardization

• Aggregation brings together sensed data for easier handling, processing, and storage. This makes it possible to derive meaningful conclusions for future decision making.
• Standardization is crucial for IoT to ensure interoperability, reusability, scalability, relevant data semantics, and security.
• Standards include network protocols, communication protocols, and data-aggregation protocols within the context of IoT. Regulatory standards deal with ownership, use, and sale of data.

Augmented Intelligence

• Analysis of data demands augmented cognitive technologies.
• Augmented intelligence automates systems to perform descriptive, predictive, and prescriptive analyses.
• Computer vision, natural language processing, and speech recognition play crucial roles in predictive and prescriptive analytics.

Augmented Behavior

• Augmented behavior involves actions considering all phases of the information value loop, from sensing to data analysis.
• Actions in the context of people and organizational processes are supportive of manifesting actions.
• Machine-to-machine (M2M) and machine-to-human (M2H) technologies are important here.
• The transition from data science to behavioral sciences takes place at this phase. This leads to cognitive and action abilities in machines for environmental understanding.

IoT Architectures

• IoT systems connect diverse hardware devices across multiple applications.
• The heterogeneity of devices poses key challenges for successful deployment.
• Ubiquitous connectivity, scalability, interoperability, security/privacy, and high traffic and storage needs affect IoT system architecture.
• IoT elements include; sensing, digital identification, services, communication, semantics, and computation.
• Three-Layer architecture has perception, network, and application layers involved.
• Five-layer IoT architecture involves Object (Perception), Object Abstraction (Network), Service Management (Middleware), Application, and Business layers.
• Six-Layer: Focus, Cognizance, Transmission, Application, Infrastructure, Competence
• Seven-Layer: Collaboration (and) Processes, Application, Data Abstraction, Data Accumulation, Fog/Edge, Connectivity, Things.

Perception Layer

• The perception layer collects various information types from physical sensors (e.g., RFID, sensor objects, etc.).
• This layer transmits processed information to the next layer through service interfaces.
• Perception of environmental factors, using low-power and nanoscale technology in smart things, is a challenge.

Network Layer

• The network layer (also called the transmission layer) forwards data from the perception layer to the internet and other communication technologies.
• Various communication technologies (e.g., WLAN, Wi-Fi, LTE, Bluetooth) are integrated with IoT gateways to transmit data.
• The network layer performs data operations within the cloud.

Application Layer

• The application layer provides requested services to users (e.g. temperature, moisture, humidity, etc.).
• Besides user-requested services (e.g., temperature, humidity), the application layer provides data management services (e.g., warehousing, Big data storage, data mining) for semantic data analysis.

Business Layer

• The business layer manages overall activities/services within the IoT system.
• Services are managed through charts, business models, and graphs derived from received data.
• Automatic decision-making and development of smart business strategies are supported using Big Data analysis within this layer.

Focus Layer

• Modules in this layer identify smart objects, focusing on the aspects of the considered IoT system.

Cognizance Layer

• This layer consists of sensors, actuators, and data monitoring modules responsible for collecting sensing information from smart objects.

Transmission Layer

• This layer manages the transmission of sensed data from the cognizance layer to the application layer.

Infrastructure Layer

• This layer handles the availability and access to service-oriented technologies (e.g., cloud computing, big data technology, etc.)

Collaboration and Processes

• In IoT, multiple individuals usually use the same application for various purposes. The primary goal is empowerment, enabling better workflows and collaboration. Processes related to business mostly transcend the boundaries of individual applications.

Explore the foundational components enabling IoT systems in this quiz. Learn about ubiquitous computing, the roles of various enabling technologies, and the stages of the information value loop essential for IoT functions. Test your knowledge on identification, sensing, and wireless communication technologies.