Back then, you had internet, but you had to build the connectivity, state machines and operating logic more or less from scratch. One could argue, that with the advent of IaaS providers such as AWS, Azure, IBM bluemix some ten years ago, the IoT finally came together. As of today, it seems odd to speak about IoT without cloud services.
Cloud is the hub
To connect the devices or things together, one needs a central place to manage it all. In this data hub one can build state machines, operating logic and deeper understanding of the sensor data. Logical place for this form of data hub with application logic is IaaS offerings.
Most of the IaaS providers offer support for MQTT, which is standardized lightweight low power device message protocols. Using standard protocols eazes the data ingestion and sending control messages to devices.
To further simplify data transfer two main players, AWS and Azure, have both lately invested in the IoT connectivity in order to make connectivity of devices ever easier. AWS even offers operating system for the microcontrollers and small microprocessors, to aid the connectivity all the way.
IoT data is big data
When it comes to critical data, devices may send the data once a second, or even more shorter time period. This creates 86 400 data points per day from one device. Even though each data point contains small set of data, this time series data grows quite rapidly to very large amounts.
Luckily, the cloud services offer cheap and reliable way to store data.
For expanding data sets, you only pay for the storage you use, so you do not need to know beforehand how much data you will consume.
In order to create knowledge from the data, this large amounts of data need to be processed, cleaned and structurized. From here, operating logic can be build, state machines created and machine learning can be used to gain greater understanding of the devices.
Cloud offering is very well suited to tackle these problems as well, with the on demand flexible compute capacity to match heavy calculations or big data processing.
Cloud comes to the edge
Typical set up between devices and the cloud is to use gateways. In this way many simple and cheap devices, such as sensors or servos, can be connected to gateway that maintains the communication logic between the devices and cloud. AWS Greengrass and Azure Edge IoT are cloud providers software for the gateways and that further simplify the connection and data transfer logic.
With the development of more powerful calculation capacity devices with lower power consumption allows gateways to do more than just the connectivity.
Gateways can now do computing at the edge or even run machine learning models on the data.
With more powerful gateways only necessary data is send to the cloud for storage and processing, which allows more cost efficient solutions to be build. If no connectivity is present gateways can store the data until connectivity is reestablished.
Cloud is the enabler
Cloud services offer flexible ondemand compute and storage capacity to meet the demands of any IoT project. They offer easy solutions for standardized connectivity protocols and go as far as providing their own solutions to the gateways and edge computing.
Once the data is in the cloud, with flexible compute capacity and cheap storage options, data can be processed from data to knowledge using multiple set of tools.
This knowledge can then be used to allow device to communicate with one another, build new solutions or simply understand the world around us. In the end, cloud is the enabler, connecting and orchestrating the internet of things.