Presented By: Keshav Kannan
The Symbiotic Relationship
IoT applications generate a massive volume and velocity of data. Cloud computing provides the essential backbone for storing, processing, and analyzing this data, turning raw sensor readings into actionable insights.
Edge/Fog Computing
Initial, real-time processing of raw sensor data happens at the edge, close to the source. This is crucial for applications requiring low latency, like autonomous vehicles or industrial automation.
Cloud Computing
Data is sent to remote, powerful server networks for in-depth analysis, long-term storage, and access to a vast array of services like machine learning, security, and big data processing.
The Vision of Connected Living
IoT and the cloud are fundamentally reshaping our environments, creating a seamless ecosystem of "Connected Living" that spans our homes, workplaces, and cities.
Connected Houses
Home Automation, Energy Saving, Health Monitoring
Connected Work
Mobility, Mobile Working, Enterprise Networking
Connected City
Smart Transportation, E-learning, E-governance
Connected Living
Integrated Data Services
Providing ubiquitous connectivity and services anywhere, anytime by integrating a rich variety of data such as video, voice, and structured information.
Layers of the Cloud
Cloud services are delivered in different layers of abstraction, each providing a specific level of control and management. These models allow developers to choose the right tools for their IoT applications.
IaaS
Infrastructure-as-a-Service
Provides fundamental resources like virtual machines, storage, and networking. Offers maximum control.
e.g., AWS EC2, Google Compute Engine
PaaS
Platform-as-a-Service
Offers a platform for developers to build, deploy, and manage applications without worrying about the underlying infrastructure.
e.g., Google App Engine, Heroku, Azure App Service
SaaS
Software-as-a-Service
Delivers ready-to-use software applications over the internet, typically on a subscription basis.
e.g., Google Workspace, Salesforce, Office 365
A Framework for Integration
Integrating IoT with the cloud creates a powerful, scalable system. This framework highlights the key components working in concert to bridge the physical and digital worlds.
Handling the Data Deluge
Specialized open-source platforms are essential for processing the massive datasets generated by IoT devices. These tools form the core of the cloud's data processing capabilities.
Apache Hadoop
An ecosystem of tools for distributed storage (HDFS) and batch processing (MapReduce) of very large data sets across clusters of computers.
Apache Spark
A fast, general-purpose cluster computing system that excels at in-memory data processing, making it ideal for streaming data, machine learning, and interactive analytics.
Specialized IoT Cloud Services
Beyond general computing, the cloud offers specialized services tailored for the unique needs of the Internet of Things, treating sensors and events as on-demand resources.
SEaaS: Sensing-as-a-Service
Provides on-demand access to sensing data collected by cloud-enabled sensors, allowing multiple applications to share and utilize the same data streams.
SAaaS: Sensing and Actuator-as-a-Service
Virtualizes physical sensors and actuators, offering them as services over the cloud. This enables remote control and interaction with physical devices.
SEaaS: Sensor Event-as-a-Service
Triggers actions or notifications based on specific events detected from real-time sensor data, such as temperature thresholds or traffic density changes.
Major IoT Cloud Platforms
Numerous providers offer end-to-end IoT cloud platforms, each with unique strengths in scalability, cost, and functionality. Here are some prominent examples.
Kaa IoT Platform
An open-source, multipurpose middleware platform for end-to-end IoT development, known for its modularity and flexibility.
ThingSpeak IoT Platform
An open-source platform focused on collecting, storing, and visualizing sensor data in the cloud, with strong integration with MATLAB for analysis.
Google Cloud IoT
An end-to-end platform focused on easy connection, storage, and management of IoT data, known for its smart device integration and per-minute pricing.
Oracle Cloud IoT
A PaaS offering that provides real-time IoT data analysis, endpoint management, and high-speed messaging for critical business decisions.
REST APIs: The Language of IoT
Representational State Transfer (REST) is the preferred architectural style for IoT web services due to its simplicity, lightweight nature, and stateless communication over standard HTTP.
Client
(e.g., IoT Device, App)
Server
(Cloud Application)
Key Principle: The interaction is stateless. Each request from the client contains all the information needed for the server to fulfill it, without relying on any stored context.
Thank You
Open for Questions
Thank you for your attention. I am now open for any questions you may have about the integration of IoT and Cloud Computing.