Cost Savings in Industrial Applications:
Predictive capabilities are extremely useful in an industrial setting. By drawing data from multiple IoT sensors in or on machines, machine learning applications can “learn” what’s typical for the machine and then detect when something abnormal begins to occur.
Predicting when a machine needs maintenance via IoT data is incredibly valuable, translating into millions of dollars in saved costs. A great example is Goldcorp, a mining company that uses immense vehicles to haul away materials.
When these hauling vehicles break down, it costs Goldcorp $2 million per day in lost productivity. Goldcorp is now using machine learning models to predict with over 90% accuracy when machines will need maintenance, meaning huge cost savings.
Shaping Experiences to Individuals:
We’re actually all familiar with machine learning applications in our everyday lives. Both Amazon and Netflix use machine learning to learn our preferences and provide a better experience for the user. That could mean suggesting products that you might like or providing relevant recommendations for movies and TV shows.
Similarly, in IoT machine learning can be extremely valuable in shaping our environment to our personal preferences.
The billions of sensors and devices that will continue to power connected devices, smart homes, and IoT devices in the coming years will generate exponentially more data. This huge increase in data will drive great improvements in machine learning, opening countless opportunities for us to reap the benefits.
Not only we will be able to predict when machines need maintenance, we’ll be able to predict when we need maintenance too. Machine learning development services will be applied to the data from our wearables to learn our baseline and determine when our vitals have become abnormal, calling a doctor or ambulance automatically if necessary.
Beyond individuals, we’ll be able to use that health data at scale to see trends across entire populations, predicting outbreaks of disease and proactively addressing health problems.
Although both machine learning and IoT can be over-hyped, the future of machine learning applications in IoT are worthy of that hype. We’re really just scratching the surface of what’s possible.
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