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Not content to be the dominant player in the book retail and growing cloud storage market – Amazon have recently announced the newest addition to their popular suite of cloud computing services – the AWS Internet-of-Things platform. AWS IoT is a managed cloud platform for supporting large numbers of devices in Internet-of-Things applications and securely connecting them to each other, as well as to web applications and other AWS services.

AWS IoT can support a huge number of devices and messages, and it can reliably and securely process and route these messages to AWS endpoints and to other devices or services.

It allows networks of IoT devices to maintain responsive connections to the cloud, and makes it easier to develop cloud applications that interact with IoT “things”. It receives messages from things and then filters, records, transforms, or routes these messages as needed.

The AWS IoT service provides an easy-to-use interface that allows applications running in the cloud and on mobile devices to access data sent from IoT devices, and to send data and commands back to those devices. This makes it easy to integrate your IoT devices and data with existing Amazon Web Services components including Amazon Lambda, Amazon Kinesis, Amazon S3, Amazon Machine Learning, and Amazon DynamoDB. Using these services, you can build IoT applications, manage infrastructure and analyse your data.

Connected devices, such as sensors, actuators, wearables, smart appliances, and other embedded devices connect to AWS IoT securely, using either the HTTPS or MQTT protocols. AWS IoT provides authentication and end-to-end encryption throughout the entire platform, and data is never exchanged between devices and AWS IoT without without proper authentication and identity of each server or component in the network.

Using MQTT, the AWS IoT platform enables devices to communicate with the service through a publish-subscribe model. This means that a device, such as a smart thermostat, can publish its latest sensor readings and status updates to AWS IoT, and the server will push that data out to any subscribers to the thermostat’s MQTT channel. Any other application or device can be subscribed to the thermostat’s MQTT channel, such as a user-facing smartphone app or a home’s network-connected air conditioner.

Amazon makes it easy for developers to get started with AWS IoT by providing several SDKs. These SDKs help IoT developers to easily and quickly connect their hardware devices, applications and mobile devices to the AWS IoT platform. The Amazon IoT Device SDK makes it easy to set up devices that connect, authenticate and exchange messages with AWS IoT using either MQTT or secure HTTP.

With AWS IoT, you can filter, transform and act upon device data on the fly, based on business rules you define. You can update your rules to implement support for new devices or new application features at any time. The AWS IoT Rules Engine enables you to continuously process data from devices connected to AWS IoT, and filter and transform that data in whatever way you need. Using an intuitive SQL-like syntax, the Rules Engine can process data and deliver messages to your own Web services or third-party services, as well as routing messages to other AWS components including Lambda, Kinesis, S3 and DynamoDB.

For example, a rule may be configured as a trigger to start storing time-series data in DynamoDB when a sensor reading exceeds a certain threshold, or it may invoke Amazon’s Simple Notification Service to deliver push notifications to users.

This integration makes it easy to use the entire AWS ecosystem for further processing, analytics and storage of your IoT data. Furthermore, all internal message transport within the AWS ecosystem is not billed – moving messages between these services is free, regardless of the volume of data involved.

Pricing is based on the number of messages published to AWS IoT as well as the number of messages delivered by AWS IoT to devices or applications. (Traffic is measured in blocks of data, or messages, that are 512 bytes long).

The free AWS account tier allows you to get up and running to evaluate AWS IoT and other AWS components for free, with a limit of up to 250,000 messages published or delivered per month for 12 months.

Hardware support for the new AWS IoT platform is provided thanks to several hardware starter kits from partners including Broadcom, Intel, Qualcomm and Texas Instruments. These starter kits include microcontrollers and sensors that are already tested and documented for easy integration with the AWS IoT platform – allowing you to easily get started prototyping and developing IoT applications.

With prebuilt hardware, the AWS IoT device SDK, and a simple getting-started guide included, you can get up and running quickly to see if the AWS IoT service is a good fit for your IoT needs. If you already have appropriate hardware, you can simply download the IoT Device SDK and programming examples from Amazon to get started.

Here at the LX Group we have end-to-end experience and demonstrated results in the entire process of IoT product development, and we’re ready to help bring your existing or new product ideas to life. Getting started is easy – click here to contact us, telephone 1800 810 124, or just keep in the loop by connecting here.

LX is an award-winning electronics design company based in Sydney, Australia. LX services include full turnkey design, electronics, hardware, software and firmware design. LX specialises in IoT embedded systems and wireless technologies design.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

When it comes to developing Internet-of-things systems, a lot of public focus is placed on the hardware and networking infrastructure required to make it a physical reality. However when designing a system, the processing and analysis of collected data requires an equal or increased effort – and anything that can make this easier or more cost-efficient is necessary.

One example of efficient data processing for the Internet-of-things can be provided by the Amazon Kinesis – a new managed service for real-time processing of streaming data at massive scale, adding big-data services to the Amazon Web Services line-up.

Kinesis can collect and process hundreds of terabytes of data an hour from hundreds of thousands of sources, allowing you to write applications that process information in real time from all sorts of different data sources.

Data can be harvested from almost anything- such as sensors and instruments, user interfaces, or other sources of data. Let’s take a quick look at Kinesis and its potential role in Internet-of-Things applications.

Kinesis service accepts real-time data, replicates it and delivers it to applications running on Amazon’s cloud, allowing applications to tap big data in real time. Real-time operations on large amounts of data made possible by Kinesis enable you to collect and analyse information in real-time, answering questions about the current state of your data without waiting.

With Kinesis, developers can get more creative about what to do with large amounts of data flowing in live, and developers building applications on Amazon’s cloud services can now more easily take advantage of sensors collecting data, which is an important development for realising the potential of large-scale analytics on data collected from Internet-of-Things networks.

This certainly makes Amazon Web Services an attractive choice for developers seeking to put large scale data collected from sensor networks to work in the cloud.

The system can be scaled elastically for real-time processing of streaming data on a large or small scale, taking in large streams of data records that can be consumed in real time by multiple data-processing applications running on instances of Amazon’s Elastic Compute Cloud (EC2).

Data-processing Kinesis applications use the Amazon Kinesis Client Library, and these applications can read data from the Kinesis stream and perform real-time processing on the data they read. The processed records can be emitted to dashboards, used to used to generate alerts, or emit data to a variety of other Amazon big data services such as Amazon Simple Storage Service (S3), Amazon Elastic MapReduce (EMR), or Amazon Redshift.

Interoperability and compatibility with existing, established Amazon cloud computing services and products is an important factor which is likely to give the uptake and usability of Kinesis a significant advantage for established Amazon Web Services users. Kinesis applications can also emit data into another Kinesis stream, enabling more complex data processing.

With Kinesis applications, you can build real-time dashboards, capture exceptions and generate alerts, output data to drive user interactions, and output data to Amazon S3, DynamoDB or other cloud computing services.

Kinesis makes it possible to respond to changes in your data stream in seconds, at any data scale – for example, in Internet of Things applications, such a response may take the form of activating a certain device or automation system in a specified way.

You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.

Kinesis will scale up or down based on your needs, seamlessly scaling to match the data throughput rate and volume of your data, from megabytes to terabytes per hour.

This allows your systems to reliably collect, process, and transform all of your data in real-time before delivering it to data stores of your choice, where it can be used by existing or new applications. Connectors enable integration with Amazon S3, Amazon Redshift, and Amazon DynamoDB.

Kinesis provides developers with client libraries that enable the design and operation of real-time data processing applications – a new class of big data applications which can continuously analyze data at any volume and throughput in real time.

Kinesis is cost effective for workloads of any scale – you can pay as you go, and you will only pay for the resources you use, like with other Amazon cloud computing services. Initiall you can start by provisioning low-throughput streams, and only pay a low hourly rate for the throughput you need.

Kinesis enables sophisticated streaming data processing, because one Kinesis application may emit Kinesis stream data into another Kinesis stream. Near-real-time aggregation of data enables processing logic that can extract complex key performance indicators and metrics from that data.

Complex data-processing graphs can be generated by emitting data from multiple Kinesis applications to another Kinesis stream for downstream processing by a different Kinesis application. You can use data ingested into Kinesis for simple data analysis, real-time metrics and reporting in real time.

For example, metrics and reporting for system and application logs ingested into the Kinesis stream are available in real time, allowing data-processing application logic to work on such data as it is streaming in, rather than wait for data bunches to be sent to the data-processing applications later.

Data can be taken into Kinesis streams, helping to ensure ensure durability and elasticity. The delay between the time a record is added to the stream and the time it can be retrieved is less than 10 seconds – in other words, Kinesis applications can start consuming the data from the stream less than 10 seconds after the data is added – this is useful in applications where real-world actuation or control of automation devices needs to happen relatively quickly.

By using such a powerful and scalable system such as Kinesis, you can get the power you need without paying for surplus processing capacity – but still have reserves ready on demand. But how to get started with Kinesis and your Internet-of-things plans?

Simply join us for an obligation-free and confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.