Artificial Intelligence and Internet of Things (AIoT) is one of the newest players in the field of technology, and it has already gained attention at a rapid pace. This is thanks to a compelling combination of intelligent cognition, edge computing and autonomous capabilities.

While IoT is powerful in itself, connected networks can only take things so far while still performing at the peak. When AI is brought into the same picture, things get seriously advanced.

IoT is already well established and is still set to grow, with over 41 billion IoT devices to be used by 2027. In addition, Gartner predicts that more than 80 percent of enterprise IoT projects will include an AI component by 2022. But why is this widespread acceptance on the cards?

Imagine if your IoT-powered infrastructure could run with self-repair capability.
Think, not only self-repair, but have the ability to implement predictive maintenance, and automatically adjust external variables.

AI promises to offer these benefits due to its ability to analyze the vast amounts of real-time data collected by IoT devices and make autonomous, intelligent decisions based on this data.

AIoT has the potential to increase productivity and efficiency for any enterprise employing IoT technology. AIoT is also expected to be particularly transformative for manufacturing, autonomous vehicles and robotics. Let’s see what happens to these industries when AI is combined with IoT.

AIOT. staying ahead of the manufacturing curve with
Smart factories and warehouses were some of the early adopters of IoT technologies.

The World Economic Forum has already identified over 1000 smart factories in 2018. However, as more production plants and factories join the trend, their competitive edge diminishes.

AI is pegged to deliver the next competitive advantage for organizations that already have their own IoT infrastructure. AIoT will further enhance the capabilities of factory equipment such as remote sensors, smart meters and production machines as they can process vast amounts of data and allow the devices to intelligently respond to their environment.

Such changes enable products to reach market faster, production lines automatically respond to external market demand and provide new business insights from operational data.

Take regular IoT setup – and add in AI.
With IoT setup, machinery can send automated service updates to the system so that maintenance repairs can be scheduled. With the addition of AI, this process becomes fully automated. The computer system will place the order for the required parts and schedule set up.

Nokia Production-Finland.
Nokia’s production site in Olu, Finland saw a 30% increase in productivity and they are now able to bring products to market 50% faster. A whole-digital approach coupled with cutting-edge technology like Digital Twins and Intelligent Automation made this possible.

Agriculture Specialist Major Additions.
German digital farming experts have teamed up with Ontera Inc. to create an intelligent feedback system that directly adjusts to agricultural needs. The project uses computer vision to monitor crop and climate conditions which are fed back to the plant. If signs of insect damage or vitamin deficiency are found, the plant will formulate accordingly. Formulating ensures that crops receive only the formula they need at the time, reduces the production of unnecessary treatments, and helps improve overall crop yield.

AIoT fueled an era of autonomy
Autonomy is another important deliverable promise for organizations that embrace IoT in their digital transformation strategies.

Many public and private buildings are keen to embrace the power of IoT to improve their operational systems and allow for real-time service adjustment. Smart heating systems are one example of how this trend is shaping up.

AIoT helps monitor variables such as weather, pollution levels, or the number of workers in specific locations, and auto-adjust equipment throughout the building. Knowing the exact occupancy number improves conditions for a building’s users, prevents unnecessary energy consumption, and sets the basis for predictive analysis.

Toronto-based Ecobee uses a range of AI-powered smart thermostats that continuously adjust based on real-time data coming from occupancy and humidity sensors, outdoor temperature readings and predictions based on prior user behavior patterns. Ecobee’s latest feature ties the system to periodic energy pricing that allows AI models to prioritize energy use when it’s cheapest.

When talking about the future of AIoT, we touch on autonomous vehicles. McKinsey predicts that up to 15% of all cars will be autonomous by 2030. AI provides data to control systems so that vehicles can react to objects, control speed, and change direction accurately.

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