What do you think the future on earth looks like?
We all think of a future where humans and machines interact seamlessly. Our idea of the perfect future is influenced by how it looks in movies and TV shows.
Most of these fictional future worlds have one thing in common: super-smart devices.
Whether it’s the ultra-futuristic world of Blade Runner 2019 or the toned-down future of Black Mirror episodes, all of them feature smart devices that interact with the characters.
These fictional worlds, however, are not all that rooted in fiction. Some of this technology already exists in the present world, albeit with limited functionality and capabilities. These devices are called IoT devices—interconnected devices equipped with sensors and cameras that allow them to communicate with neighbouring devices over the internet.
Businesses, though, are not resting on their haunches. They are trying to create smart devices with greater functionality and capabilities, just like in the movies. Data analytics tools like SAS analytics for IoT are helping engineers create these uber-smart devices.
Early IoT devices had simple functions and limited capabilities due to the lack of data needed to improve their intelligence. As a result, they were not smart—only a little less dumb.
Early smart doorbells, for example, only relayed a video feed of the front door to occupants inside the house. While this is undoubtedly useful, it was not very smart.
Modern smart doorbells not only relay a video feed to occupants but also identify the person at the front door. In addition, they notify occupants about the arrival of guests, all through the power of analytics.
This identification function, in particular, uses cameras, AI and data analytics to identify different people. Cameras capture the image and data analytics helps identify the individual by comparing the image to information in a database.
Analytics tools like SAS analytics for IoT have been critical in improving home assistants powered by the likes of Google Nest Home and Amazon Echo.
These digital home assistants use AI-powered data analytics to study our behaviour through various sensors located. Studying our behavioural patterns helps these devices automate actions like setting the temperature through a thermostat or switching lights on and off.
IoT devices are not only making a splash in our homes but also in our factories and commercial spaces. Many organisations are now using IoT devices in their manufacturing lines, which previously required manual labour.
Early manufacturing equipment relied on human knowledge about each machine for maintenance. Unless there were trained machine operators on-site, these expensive machines were rendered useless when they broke down.
Modern manufacturing lines include IoT devices so that maintenance and troubleshooting become easier. Modern manufacturing equipment includes sensors and cameras that not only monitor the production process but also monitor the optimal operation of these machines.
These sensors stream large amounts of data to servers to deliver visual analytics insights about the manufacturing process and components inside the machines. With these insights from IoT devices, employees are able to detect faults in the machines and fix them, reducing downtime across the manufacturing process.
Modern devices not only share data but also use AI to pinpoint faults, eliminating the hassle of troubleshooting for employees.
In the future, data analytics tools for IoT devices may help us build intelligent manufacturing lines that fix themselves, making production seamless.
All of us envision a future powered by smart technology that automates our mundane tasks.
Thanks to data analytics for IoT, this reality is not too far away. The IoT analytics challenges that prevented widespread adoption is fast becoming a thing of the past as more and more smart devices are used across industries.
Soon, we might not need special effects to create the fantastical scenarios we see in movies.