The Internet of Things in Our Everyday Life
IoT(Internet of things), something that is very fast emerging to be the next big thing in our world. When many would be not familiar with the concept of IoT, a lot will be familiar with their applications. For Example, when you can control your AC by your smartphone or using a smartwatch that gives you real-time biometric readings.
IoT is all about making all the devices in your everyday life to act smart. IoT provides a super platform for the devices to get connected. All the devices can send and receive messages through this connection with the help of sensors in the devices. According to business insider intelligence, 24 billion IoT devices will be installed by the year 2020.
Can Artificial Intelligence & machine learning give a boost to the growth of IoT?
Artificial Intelligence is no longer confined to the Sci-fiction movies but has indeed become a reality now. Artificial intelligence is a broad concept that is loosely defined, it is something that makes the computers behave like they have human intelligence. It gives the machine the ability to learn, solve the problem and think logically.
Many people still doubt where is AI used (remove the pictures of Roberts from your head when say AI), you have used it while watching Netflix, web searching through Google Assistant, Mobile banking & filters used in Email etc. Now that's the tricky part, we didn't even realize its the machine that is giving the shots here.
Machine learning is a part of AI where the machine is trained in the same way as a child or a pet to have human intelligence. It is an application of AI that provides machine the ability to automatically learn and improve from their experience.
Now you know that AI and machine learning will aid you in problem-solving and you can do a lot more work in less time. Then why not utilize AI and machine learning to bring out the true potential of IoT.
Achieving financial benefits through IoT has become difficult. And the reason is that we cannot minimize the cost without affecting its performance. For example, industrial companies produce a massive amount of data on a daily basis. However large, companies fail to systematically collect, store, analyze and use such data to improve process efficiency or meet other goals. We need to find a more effective method to organize the data.
Real-time decision-making in IoT systems is still challenging due to cost, form factor limitations, latency, power consumption, and other considerations. We use AI, Big Data & Machine learning to overcome this issue and optimize the performance per dollar and performance per power consumption.
For Example, Edge TPU is Google’s purpose-built ASIC chip designed to run machine learning (ML) models for edge computing which was announced in July 2018. It uses the Cloud IoT Edge software stack, which combines gateway functions using the Edge IoT Core software, with Edge ML, a machine learning runtime based on TensorFlowLite.
What that really changes with IoT with the implementation of AI and Machine learning is that we are moving from connectivity of the devices to intelligence. Without real intelligence or insights on the data that is generated by those devices, it is really hard to get the investments in return. According to the study, the data generated by the IoT devices will be 40 billion Zettabyte by the year 2025, which is a huge amount of data which is mostly real-time data, and decision making here will become difficult.
Based on previous experiences, Cloud IoT core was introduced, which is a fully managed service that provides us with an easy and secure connection with millions of different devices in different areas and thus manage their data easily.
So in the future, many real-time applications will emerge in IoT by combining AI and machine learning that gives the computing power to analyze the huge data generated by IoT devices.
"Imagine a future where the ambiance in our house will be preset daily according to our mental and physical comforts automatically."
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