The Internet of Things (IoT) forms a network of devices or ‘things’, interconnected via the internet, that facilitates the creation of integrated ‘smart’ applications for homes and businesses worldwide. Cloud service providers, such as Amazon Web Services (AWS), are enabling IoT applications to achieve high security, scalability, and efficiency. Among all cloud platforms, AWS IoT is a pioneer in delivering services for creating intelligent managed IoT solutions.
AWS IoT securely connects IoT devices to Amazon Web Services (AWS), as well as other IoT devices. By scaling to billions of devices, providing analytics & security features, and data management, AWS IoT helps developers build IoT applications for many use cases.
There is much more to AWS IoT than offering bi-directional communication between IoT devices and the cloud. Dgtl Infra helps you understand more about AWS IoT and what its services can offer for building intelligent IoT applications.
What is AWS IoT (Internet of Things)?
Amazon Web Services internet of things or AWS IoT is a platform that connects billions of IoT devices with AWS cloud services and other IoT devices. Think of it as a middle layer between IoT devices and various AWS services, providing bi-directional and secure communication between them, over the internet.
IoT devices can be computers, electrical & electronic appliances, and cell phones. While AWS services include Lambda, databases, streaming services, computing services, and many more. AWS IoT uses the MQTT, WebSocket, and HTTP/1.1 protocols for messages passing between devices and AWS’ services.
AWS IoT is used for several consumer, commercial, industrial, and automotive applications. For example, AWS IoT helps in “asset condition monitoring”, which determines if specific equipment performs optimally by capturing IoT data like temperature, vibrations, and error codes.
For the consumer, home automation is a key use case, providing an integrated smart home experience. Specifically, AWS IoT enables simple to complex operations like switching light bulbs off autonomously, to security systems that automatically detect threats and send notifications to homeowners.
Overall, AWS IoT removes the burden of managing cloud infrastructure while allowing users to build secure, reliable, and scalable applications for every IoT use case.
Importantly, AWS IoT is secure by design. It protects device data through various security mechanisms like encryption, access control, and monitoring. Also, it enables more intelligent IoT solutions to be built, which can keep learning by leveraging artificial intelligence (AI) and machine learning (ML).
What Does AWS IoT Offer?
AWS IoT offers three types of services to support IoT solutions: i) device software, ii) connectivity and control services, and iii) analytics services.
AWS IoT device software helps build IoT applications for any platform and allows them to be extended to edge devices. The following are the device software components for building and operating various IoT solutions:
- Device and Mobile SDKs: consists of all the open-source libraries and other learning materials so that developers can leverage any platform and easily build IoT solutions
- Greengrass: helps connect IoT devices and operate them at the edge
- FreeRTOS: operating system which enables IoT devices, including small, low-power edge devices in IoT solutions
- Device Tester: used for testing AWS IoT Greengrass and FreeRTOS
- ExpressLink: connectivity module for linking devices to the cloud and using a range of AWS services
Connectivity and Control Services
AWS IoT’s connectivity and control services help secure and manage IoT devices in the cloud:
- AWS IoT Core: helps devices connected to AWS IoT securely interact with cloud applications and other devices
- AWS IoT Core Device Advisor: fully-managed service that provides tests for validating IoT devices during ‘device software’ development
- AWS IoT Device Defender: protects IoT devices from various security vulnerabilities by auditing and monitoring the connected devices
- AWS IoT Device Management: used for essential functions like remotely accessing devices, managing device updates, monitoring, and troubleshooting issues
AWS IoT Analytics facilitates the analysis of IoT data to extract value from massive amounts of information more rapidly. This fully-managed analytics platform automates every step of analytics, from data cleaning and transformation, to querying and analyzing data. The platform’s Analytics services allows efficient queries on IoT data with a built-in SQL query engine.
Additionally, other capabilities of AWS IoT Analytics services exist, which help businesses and consumers use analytics to build innovative applications.
What is AWS IoT Core?
AWS IoT Core is the heart of AWS IoT architecture that interconnects IoT devices with AWS services and other IoT devices. Notably, IoT Core can interact with devices when they are offline.
Using a registry feature, AWS IoT Core maintains a unique identity for each connected device and tracks device metadata. Users can leverage AWS SDKs to connect and authenticate IoT devices and applications with IoT Core and pass messages using standard IoT protocols. Additionally, AWS IoT Core has several other features for connecting, managing, and securing IoT solutions in the cloud.
AWS IoT Core’s fully-managed and scalable Device Gateway manages all active IoT connections and ensures their secure and efficient communication with the IoT Core. This feature supports communication with standard IoT protocols and enables low-latency connections when communicating with MQTT or WebSocket protocols. The Device Gateway feature also makes AWS migration easy for users.
AWS IoT Core includes a Message Broker feature for high throughput and low-latency message transmission between IoT devices and applications. This fully-managed and scalable feature supports many messaging patterns, allowing users to exchange messages from any connected device. Also, Message Broker’s access control mechanisms allow users to control who can access the service.
AWS IoT Core’s Rules Engine allows users to define business rules, based on which the service can process and analyze device data. Users can set rules for devices to behave according to parameters like message content and other device data. Additionally, Rules Engine has capabilities such as message routing to other AWS services and providing defined functions for data transformation.
AWS IoT Core’s Device Shadow is a virtual version of the connected IoT device. Specifically, this feature maintains the “latest device state” and “desired future state”, which other devices can use to interact with the IoT device, using highly-available REST APIs.
Alexa Voice Service (AVS) and Sidewalk Integration
AWS IoT Core integrates with Alexa Voice Service (AVS) and Sidewalk. Firstly, the AVS integration utilizes a virtual Alexa Built-in device for Alexa-related functionalities like audio decoding and mixing, which ultimately reduces the cost of creating Alexa Built-in devices. Secondly, the Amazon Sidewalk Integration is a free service that improves connectivity and simplifies device setup.
In addition, AWS IoT Core supports long-range wide area network (LoRaWAN) technology. In turn, this allows users to connect wireless devices with LoRaWAN, as well as authentication and authorization mechanisms like certificate-based authentication, customer-created token-based authentication, and encryption to secure access to IoT devices.
What is AWS IoT Greengrass?
If users require an IoT solution with pre-built components for common use cases and want to rapidly build more simplistic IoT applications from scratch, then AWS IoT Greengrass provides the perfect solution. Per Amazon Web Services, AWS IoT Greengrass is an open-source edge runtime and cloud service for building, deploying, and managing device software.
Modular Components and Software Catalog
AWS IoT Greengrass enables intelligent device software to be created easier and faster by providing pre-built modular components. This functionality eliminates the need to have familiarity with device protocols, external APIs, and credential management.
Additionally, AWS offers a Greengrass Software Catalog, which is an index of Greengrass components on GitHub, developed by the Greengrass community. Users can leverage and modify these tools to accelerate the development of IoT applications.
Local Processing for Cost Reduction
AWS IoT Greengrass enables local processing support for AWS Lambda, containers, and device shadows, which reduces costs for transferring data to the cloud.
For example, local processing allows users to execute Lambda functions on the device itself so that it can respond faster to events and interactions and perform data processing. Also, AWS IoT Greengrass facilitates local messaging, resource access, and development.
Local ML Inference
AWS IoT Greengrass local ML (machine learning) Inference provides ML models trained and built in the cloud to perform ML inference on local devices. In turn, local ML Inference eliminates the data transfer costs and high latency when using ML models in the cloud.
Data Stream Management
AWS IoT Greengrass supports collecting, processing, retaining, and exporting data streams from IoT devices. This feature also allows managing the lifecycle events of a data stream, data retention policies, and data transfer to the cloud.
AWS IoT Greengrass security features permit users to protect sensitive information. For example, the service’s Secrets Manager protects ‘secrets’ like credentials, keys, and endpoints, at the edge. Also, the feature allows for protecting private keys on a secure hardware component.
Another useful feature of Greengrass is the ability to update the AWS IoT Greengrass Core software running on Greengrass devices. Particularly, these over-the-air (OTA) software updates help keep devices constantly up-to-date with the latest security patches, bug fixes, and new features.
What is AWS IoT SiteWise?
AWS IoT SiteWise is a managed service, dedicated to industrial use cases, for collecting, modeling, analyzing, and visualizing data generated from industrial equipment at-scale. The service models assets, processes, and facilities to understand the industrial device and equipment relationships through the asset hierarchy it creates. Ultimately, IoT SiteWise allows users to focus on optimizing workloads, while leaving unnecessary operations like data collection and application management to Amazon Web Services.
AWS IoT SiteWise can compute transforms (mathematical expressions) and asset metrics at user-defined intervals to make them available for analytics. Additionally, AWS IoT SiteWise automatically generates statistical data like count, sum, and average over a specific period and visualizes them using the SiteWise Monitor feature.
AWS IoT SiteWise Edge
Another feature of AWS IoT SiteWise is that AWS IoT SiteWise Edge software uses AWS IoT Greengrass to locally process equipment data before sending it to the cloud.
READ MORE: What is an Edge Data Center? (With Examples)
AWS IoT SiteWise Edge uses multiple industrial protocols for data collection and it executes on local hardware. When data processing is completed, the data can be sent to SiteWise storage or long-term storage.
AWS IoT SiteWise can be used for managing gateways and it provides APIs to see all the active gateways. Users can monitor gateway health, status, and performance using Amazon CloudWatch.
AWS IoT SiteWise Monitor
AWS IoT SiteWise Monitor is a feature that enables users to interact with data from AWS IoT-connected devices. Beyond that, AWS IoT SiteWise Monitor helps users visualize real-time asset and metrics data, using various diagrams such as graphs.
In addition, if users want to see how their equipment behaves and capture any issues, they can set alarms using the AWS IoT SiteWise Console, Monitor, or SDK.
What is AWS IoT Analytics?
IoT devices generate massive volumes of real-time data, which can often bear hidden insights to help make informed business decisions and improve business operations.
Because of the i) highly unstructured nature of IoT data, ii) degree of ‘noise’ included in this information, and iii) many other complexities associated with IoT data, it is often difficult to leverage traditional analytics platforms to process and easily harness hidden insights within the data.
AWS IoT Analytics attempts to solve some of these common data analysis issues:
Automating the Analytics Steps
AWS IoT Analytics performs efficient analytics execution with a large volume of Internet of Things data, fully-managing the whole analytics experience. Specifically, this service automates every step of the analytics process, including data transformation, filtering, and enriching the data before feeding the information into AWS’ analytics engine. After the necessary pre-steps, users can run SQL queries on the data or perform machine learning to attain more powerful business insights.
ML Tools and Analytics Models
AWS IoT Analytics has pre-built ML (machine learning) models which users can employ to start analytics directly, without building algorithms from scratch.
In addition, custom analytics capabilities provide various fully-managed ML tools. For example, AWS IoT Analytics enables a Jupyter Notebook to be created, which directly connects with Internet of Things data and runs ML to build accurate models.
Furthermore, AWS IoT Analytics imports code from external tools like MATLAB and Octave and allows users to run them according to their schedules.
Optimized Data Storage
AWS IoT Analytics delivers optimized data storage for processed analytics data and automatically stores raw data for processing later. This optimized storage from Amazon Web Services (AWS) makes queries on Internet of Things (IoT) data efficient by reducing response time.