AWS IoT(Internet of Things)

The Internet of Things or IoT is a system of interrelated computing devices ,mechanical and digital machines,objects,animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

A thing in the internet of thing can be a person with heart monitor implant,a farm animal with a biochip transponder,an automobile that has built-in sensors to alert the driver when tire pressure is low or any other natural or man-made object that can be assigned an IP address and is able to transfer data over a network.

AWS IoT provides secure,bi-directional communication between internet-connected devices such as sensors,actuators,embedded micro-controllers or smart appliances and the AWS Cloud. AWS IoT is trying to help developers overcome all of common obstacles and make the work much easier. The main goal of this platform which was launched in 2015 is to offer tools that will help to spend more time on product development and not on common tasks that could be easily automated.In order to achieve it they created several services that are tightly connected to each other.All you need is to think about functionalities your project needs and pick services that will help you to develop them.

Basic Functionality of IoT is to connect all the devices to the Amazon Cloud. It allows them to interact with cloud applications and other connected modules. It’s said that it can support billions of devices and trillions of messages and can process and route them to the needed endpoint. The good thing is that it supports all the common communication protocols such as HTTP,HTTPS,WebSockets and MQTT etc. And the AWS IoT message broker,a core embedded service-enabling message exchange,also supports MQTT over the WebSockets.Because of these protocols your IoT startup’s developers can effectively connect the product to the cloud infrastructure of various shapes and sizes.

MQTT (Message Queuing Telemetry Transport) is an ISO standard (ISO/IEC PRF 20922)[3] publish-subscribe-based messaging protocol. It works on top of the TCP/IP protocol. It is designed for connections with remote locations where a “small code footprint” is required or the network bandwidth is limited. The publish-subscribe messaging pattern requires a message broker.

WebSocket is a computer communications protocol, providing full-duplex communication channels over a single TCP connection. The WebSocket protocol was standardized by the IETF as RFC 6455 in 2011, and the WebSocket API in Web IDL is being standardized by the W3C.

WebSocket is a different protocol from HTTP. Both protocols are located at layer 7 in the OSI model and, as such, depend on TCP at layer 4. Although they are different, RFC 6455 states that WebSocket “is designed to work over HTTP ports 80 and 443 as well as to support HTTP proxies and intermediaries” thus making it compatible with the HTTP protocol. To achieve compatibility, the WebSocket handshake uses the HTTP Upgrade header[1] to change from the HTTP protocol to the WebSocket protocol.

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Interesting thing is that AWS Core is storing the latest state of a device so in result it appears to some client application as if it was online all the time. There is also one cool thing with the state updates — it will automatically update them when the device will reconnect in the future and prevent the situation when important change could be missed. All of it is happening in a secure way thanks to Device defender which is another service in AWS list.

AWS IoT is really simple and a 1-click service . This is not require any heavy custom specifications. Amazon IoT has the option of 1-click service and in short it enables devices to execute any function you want them to just right out of the box.There is no additional configuration,no need to write your own firmware and thinking about security. All you need to do is to wire that click with some AWS Lambda functions like C#,Java,Python.

When you think about the pricing of this service,you need to start working with the services that are going to be used.Each of them has it’s own price list with different rates.However wthat connects them together is the fact that s the hi pricing is relative to the amount of data/devices you are using through Amazon services.

AWS IoT has the highest IoT security standards . IoT security is an issue of public concern and a stumbling block for the majority of IoT startups. Amazon doesn’t spare resources to protect its customer’s data,device and communication. Being a tech giant it can afford state-of-the-art approaches to solving security issues.To ensure that data exchange between the AWS IoT platform and connected devices us secure all the way.There are multiple authorization,authentication and encryption levels. Both authorization methods-the AWS method and the traditional approach using X.509 certificates are used with HTTPS communications. MQTT uses the certification based approach whole SigV4 connectivity protects the WebSockets connection.Moreover,product owners can form and enforce their own security policies through the AWS Console or using an API.AWS IoT is integrated with IAM. The service also supports Cognito,an identity management service for mobile and web apps.On top of that AWS arms customers with AWS CloudTrail a powerful service that locates and fixes security issues in an AWS IoT account.

Serverless Architecture is the right choice for IoT Startups. Using the serverless approach ,an IoT startup can reduce the cost of building an MVP and prototypes as well as add agility to the entire development process.Amazon purpose-built service enables all this serverless goodness with a rather straightforward configuration-AWS Lambda. AWS Lambda is a useful element in the architecture of an IoT backend.With AWS IoT and AWS Lambda ,your startup can build a highly customizable and flexible serverless backend that is highly automated and available.

AWS Iot Analytics paired with AI and Machine Learning responding to the soaring demand fr data-analytic capacities in IoT software.AWS has introduced a number of essential analytical tools. Take AWS IoT analytics and Amazon Kinesis Analytics for example. AWS IoT analytics is a powerful service for working with the data received from IoT devices. It’s a historical type of analytics for understanding long-term device performance,business reporting and ad-hoc analysis as well as predictive fleet maintenance. Another issue is that the amount of data generated by IoT devices outnumbers the accepted approaches to dealing with it. Making sense out of machine data and using it to achieve desired business goals is quite a task to perform. Humans can’t possibly process, review, and interpret this much data. Even computer software can’t do that. This is where AI(Artificial Intelligence) and machine learning (ML) algorithms come in.

The potential of Big Data is incredible. AI in IoT is how we unlock it. According to Deloitte, the acquisition of AI and IoT startups was growing fast in 2017 and is expected to hit record numbers in the future. AI-focused IoT startups deal with intelligent reasoning and speedy data analysis showcasing it across industries.

Artificial intelligence is a functional solution to managing multiple connected IoT elements. On top of that, its unlimited processing and learning abilities are critical for making sense of piles of data transmitted by IoT devices. Companies can achieve this in practice by using a powerful subset of AI which is called machine learning.

Automated vacuum cleaners, like that of the iRobot Roomba , iRobot set the standard with it’s first commercially successful automated vacuum in 2002. Founded by MIT roboticist, the company has developed technology to help it’s puck-shaped vacuum robots to map and “remember” a home layout, adapt to different surfaces or new items, clean a room with the most efficient movement pattern, and dock itself to recharge it’s batteries.

Smart thermostat solutions, like that of Nest Labs ,Though the “smart home” hasn’t exactly revolutionized life for most of us, some companies are ardently aiming to change that — and there’s few better examples than Nest, the company acquired by Google for a reported $3.2 billion.

Self-driving vehicles, such as that of Tesla Motors Cars are “things,” and insomuch as we’re interested in “things” that leverage powerful artificial intelligence, automotive technology is ahead of the curve (pun intended, I suppose). This isn’t necessarily because autonomous vehicles will be the easiest IoT innovation to bring to life (with legal and ethical concerns, the jury is out on how long it’ll take to have driverless highways anytime soon), but with nearly all major car manufacturers throwing billions of dollars at the problem, it certainly has momentum (pun intended, I suppose).

In other case AWS IoT is very much rely on Machine learning. IoT is the data “supplier” while machine learning is the data “miner.” To make the data supplied by IoT work, it needs to be refined. Dozens of IoT sensors and external factors are producing a myriad of data points. The “miner’s” task here is to identify correlations between them, extract meaningful insight from these variables and transport it to the storage for further analysis.

With the traditional analytical approach to data, a system needs past data and some expert thought to explain and report results based on data processing. IoT and machine learning works more on prediction instead. It starts with the desired outcome and searches interactions between input variables to meet the criterion. So, when an ML algorithm receives a goal, it “learns” on the IoT data. These factors are critical for achieving the set result.

Another merit of applying ML to IoT data is in the ability to automatically improve its algorithms. With more data being received and aggregated, a smart system returns even more accurate predictions. In this way, businesses can receive the most rational decision without actual “thinking.” The artificial cleaver system has answers to various aspects, starting from the machine safety or power reduction to the increased supply of personalized goods and services.