Internet of Things (IoT) developments are gaining momentum as illustrated by a new offering from Amazon. In October 2015, Amazon Web Services, Inc. (AWS) introduced AWS IoT along with an ecosystem of partners. The AWS IoT is service-oriented platform that leverages a plug-n-play Internet and cloud infrastructure to monitor and control devices while using big data to optimize. AWS allows users to begin their IoT journeys without making a capital investment and incur associated ongoing lifecycle investment costs. The AWS IoT infrastructure easily scales to support a high volume of simultaneous connections between cloud services, mobile apps, and an array of devices which may connect only intermittently and have limited compute, storage, or battery life. Developments like this are part of the shift in technology that is likely to change industrial automation systems by adding more value at lower cost.
Edge to Cloud
AWS IoT provides secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the AWS cloud. This enables the collection of data from multiple devices for storage and analysis for a wide range of functions including alarm monitoring, historic data logging, control, optimization, and predictive maintenance. Applications also can enable users to control these devices from phones or tablets. The outcomes of cloud logic, analytics, and decision analysis are securely communicated to command real-time control for edge devices. The architecture builds on industry standards for communications including HTTP and Message Queue Telemetry Transport (MQTT), an industry-standard, lightweight communication protocol designed for sensors and mobile devices, making them interoperable independent of protocols. AWS IoT customers is a pay-as-you-go service and scales to connect any number of disparate devices. Devices can securely interact with each other, cloud services, and applications while keeping them up-to-date, and collecting, analyzing, and taking action on the continuous streams of data they generate. The overall architecture is illustrated at:
Cyber Secure AWS IoT provides mutual authentication so that data is never exchanged between devices and AWS IoT without proven identity, and encrypts all data coming into and out of connected devices. AWS IoT is fully integrated with AWS Identity and Access Management (IAM), making it easy to set granular permissions for individual devices, or fleets of devices, and manage them throughout the lifecycle of the device. Users can generate and embed security credentials in their existing connected devices, or AWS IoT can generate new ones when devices are first activated. Rules Engine The AWS IoT Rules Engine makes it possible to build IoT applications that gather, process, analyze and act on data generated by connected devices at global scale without having to manage any infrastructure. The Rules Engine evaluates inbound messages published into AWS IoT and transforms and delivers them to another device or a cloud service, based on business rules you define. A rule can apply to data from one or many devices, and it can take one or many actions in parallel. Rules can be authored to behave differently depending upon the content of the message. For example, if a temperature reading exceeds a certain threshold it could trigger a rule to transmit data to adjust a setpoint. Rules can also be authored to take into account other data in the cloud, such as data from other devices. For example, you could say take an action if this temperature is more than 15% higher than the average of 5 other devices and send alarm messages to appropriate personnel. The Rules Engine provides a wide range of available functions that can be used to transform data and trigger the execution of other functions. Amazon Machine Learning Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide users through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Amazon Machine Learning is based on the same proven, highly scalable, ML technology used for years by Amazon’s internal data scientist community. The service uses powerful algorithms to create ML models by finding patterns in your existing data. Then, Amazon Machine Learning uses these models to process new data and generate predictions for your application. There is no upfront hardware or software investment since it is a pay as you go model. Gateways Edge devices such as sensors, detectors, and controllers need AWS IoT gateway software to communicate securely and function with AWS IoT. Developers Developers can use the AWS IoT Software Development Kit (SDK) to easily and quickly connect hardware devices or mobile applications. The AWS IoT Device SDK enables your devices to connect, authenticate, and exchange messages with AWS IoT using the MQTT or HTTP protocols. The Device SDK supports C, JavaScript, and Arduino, and includes the client libraries, the developer guide, and the porting guide for manufacturers. You can also use an open source alternative or write your own SDK. Starter Kits The AWS IoT Hardware Program helps AWS customers get started with their connected hardware project with bundled hardware, software that is compiled and optimized incorporating the AWS IoT SDK. AWS IoT Hardware partners offer IoT starter kits powered by AWS that include the AWS IoT SDK and hardware components that are validated and ready to connect to AWS IoT services. Current AWS Hardware Partners include Arrow, Broadcom, Intel, Marvell, Mediatek, Microchip, Qualcomm, Renasas, SeedStudio, and Texas Instruments. Available for purchase on , these kits offer a wide range of microcontroller, sensor, and development boards that developers and manufacturers can use to rapidly prototype AWS IoT-enabled connected devices. Thoughts & Observations The IoT (Internet of Things) technologies will be deployed in a wide range of applications. Proliferation of these technologies will create low-cost sensing, communications, and software that can be leveraged for industrial automation applications to deliver more value at lower cost. Related Articles ● Stimulus for New Automation Architecture ● Industrial automation lacks essential elements for IoT ● Azure Machine Learning democratizes analytics ● Bill’s Automation Perspective - IoT Impact on Industrial Automation? ● Will Industry 4.0 & IIoT create new standards wars? ● From IoT Buzzword to Reality （轉(zhuǎn)載）
