AWS IoT services work with the Internet of Things (IoT) offering control and data services, opening up opportunities for businesses to fully and confidently utilize the IoT and the cloud.
The Internet of Things (IoT) comes up during regular technical conversations now more than ever. Kevin Ashton first defined the IoT in 1999, during his “Internet of Things” presentation, in which he described the IoT as a network of objects connected to the internet.
Today, when you think about the IoT, what types of things do you imagine? How often do you say, “Alexa, turn on the lights?” Alternatively, how many Tesla vehicles do you notice on the road? Do you adjust your Nest thermostat from your phone?
These devices belong to the IoT.
How Does the IoT Work?
IoT devices have web-enabled capabilities with embedded processors, sensors, and communication hardware enabling everything to connect to the Internet, send messages, and collect and exchange data.
First, we need access to the internet. Then, we can transfer data by cell phones, WiFi, Bluetooth, ZigBee, Z-Wave, and more! Basically, the type of device is not as important as the ability to connect to the internet or cloud services.
IoT Impact
The adoption of the IoT continues it’s rapid increase in healthcare, financial services, manufacturing, retail, and automotive industries.
The demand for IoT services and solutions to leverage data is also growing. There is so much data to collect and analyze. We need to think about the IoT together with Big Data. There is no limitation in the number of devices we connect to the network and no limitation on the volume of data we can produce. The sky is the limit!
The IoT encourages companies to rethink their business and IT strategies. There are a few quick, vital benefits we cannot ignore such as monitoring business processes, improving business strategies, improving customer experience, improving company operation, making a better business decision, and optimizing costs.
When I think about the IoT system, I think about three main data blocks:
- Collect data
- Analyze data
- Take Action based on data
Cloud Platform
AWS IoT offers a managed cloud platform that interacts with Amazon Big Data services like Kinesis, DynamoDB, Machine Learning, and computer services like Lambda. With AWS IoT, devices can communicate securely with other devices and applications.
AWS IoT services support billions of devices and trillions of messages that route to other AWS services. If you are on AWS already, you see the AWS IoT concept is quite user-friendly.
AWS IoT offers control services and data services. One of the control services AWS IoT Core provides is connectivity and messaging. Devices connect to IoT Services by HTTPS, MQTT, and MQTT over WebSocket protocols. AWS IoT Message Broker is the core embedded service enabling message exchange for future analytics.
AWS IoT provides high IoT Security standards. AWS implements multiple authorizations, authentications, and encryption security levels to ensure data integrity.
AWS IoT devices for HTTPS communication use X.509 certificates, where the mobile application may use Amazon Cogito Identities and finally web, and desktop application may use IAM or federated identities for authentication. Next, we must develop policies authorizing what authenticated identity can do.
Most policies we use include a combination of AWS IoT policies and IAM policies.
Serverless Architecture
Most of us prefer the IoT for its serverless architecture. At first, start-ups embraced serverless architecture, but now the new ways of designing systems, especially when clouds services or migration to the cloud providers are in place, appeals more to larger companies.
With AWS IoT and Lambda, we can build a highly available and flexible application with automated and scalable infrastructure that’s adjustable to customer demand.
Analytics, AI and Machine Learning
Finally, let’s touch on how this all impacts Analytics, Artificial Intelligence (AI), and Machine Learning (ML). Collecting so much data from IoT devices provide opportunities for big data analytics and ML learning platforms.
Amazon provides two services you must consider for IoT data analytics: AWS IoT Analytics and Amazon Kinesis Analytics. For the analysis of historical, long-term performance data, business reporting, and other generated reporting, consider checking AWS IoT Analytics. Next, Amazon Kinesis Analytic is an excellent solution for real-time data analytics when using Amazon Kinesis Streams.
Amazon SageMaker is a fully-managed platform that deserves to be mentioned when it comes to Machine Learning. AWS blogs and webinars have covered this service a lot since “re:Invent 2018.” There are many references on AWS sites you can use to start with this service. If you have a ML project, and are planning to use AWS IoT data, most likely Amazon SageMaker is the best choice.
A Big Impact on Our Future
According to Gartner, in 2020, the number of all devices that connect to the internet will increase to 26 billion. Also by 2020, the IoT market growth predictions estimate a worth of $1.5 trillion. This type of growth poses certain challenges:
- How do we manage all that data?
- How do we secure our devices and network?
- How do we store data?
- How do we analyze this data to provide business value?
It’s time to plan for the future of the IoT and embrace the change it, and Big Data, offer.
As Kevin Ashton, “The Internet of Things has the potential to change the world, just as the internet did. Maybe even more so.”
Putting It Into Play
So, where do we start? Beacon technology acts as a primary baseline for a lot of large scale environments.
Stay tuned for the next blog in this series as we explore BlueBeak, our very own beacon technology framework, and take a deeper dive into what this technology means for the IoT.
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