IoT is termed as the network of inter-connected physical objects or devices that are implanted with various sensors, software and network communication techniques, so that they can collect data from their surroundings and exchange the data with other devices over the internet. And as soon as the technology is becoming advanced with IoT and automation, there is the interconnection between billions of devices, which generate a very large amount of data in the IoT network. Therefore, computational mechanism such as Machine Learning is required to process and manage such an enormous amount of data. ML is capable of analyzing and recognizing the patterns, classifying the data, predicting the outcomes, etc. and provide a sense of intelligence to the IoT devices like a human.
In this paper, we have discussed about IoT and ML and given an overview of how these technologies can be integrated. After that, we have discussed about various applications of ML in IoT. And at last, the challenges and scope in this new integration are also mentioned that can be the other research areas.
Key words: Internet of Things (IoT), Machine Learning, Unsupervised Learning, Supervised Learning, Deep Learning, Deep Reinforcement Learning.
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