Data Science Techniques used in IoT applications
- Cognitive Computing: Advanced techniques such as Natural Language Processing, Pattern Matching and Machine learning can be used by the organizations/businesses to gain meaningful insights from huge amounts of data which cannot be done using conventional methods.
- Real-Time Processing: The data coming from IoT devices is continous and non stop. The actions must be taken immediately based on the incoming data and a delay can cause huge loss and also a second or a minute is a huge thing.
- Deep Learning: Various techniques of Deep Learning such as Neural Networks can be used to process unstructured data either in the form of text,image,audio or a video. Image recognition, Speech recognition, Natural Language Processing and Autonomous Decison-Making techniques can be utilized in IoT applications.
- Big Data Analysis: Big Data alludes to a huge arrangement of data that no traditional management tool of data can deal with and permits admittance to huge data sets in real time. They can be used to gather insights from IoT data that would be very difficult to deal with traditional methods.
- Edge Computing: Edge computing refers to processing or utilizing data at the edge of the network or closer to where its being generated which adds value to real-time processing in IoT applications. This also improves the response time and minimizes bandwith.
Data Science for Internet of Things (IoT) Applications
As we all know today’s digital world revolves around data. To deal with huge amounts of dynamic data, we adopt data science techniques with IoT devices to make lives easier and to handle scenarios taking immediate action.
In this article, we will discuss the different techniques of data science that can be used with IoT and the key applications of Data Science for IoT. Finally, we discuss the Challenges that are faced while applying Data Science to IoT applications. Let us start with “What is IoT”?
Table of Content
- What is IoT?
- What is Data Science?
- Difference between Traditional Data Science and IoT
- Data Science Techniques used in IoT applications:
- IoT Applications Empowered by Data Science
- Challenges of IoT Applications in Data Science
- Conclusion
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