As the popularity of smart homes and smart appliances increases so is the need of analyzing the data that these devices generate. The sensors working in these smart appliances constantly generate data which quickly takes high volume. In this post on How Internet-of-Things (IoT) is related to Data Science, you will understand the need for applying Data Science techniques on IoT data.
Basically, Data Science comprises of a set of techniques that aim for extracting useful information and insights from large volumes of data. Besides, the data may be available in any format. Also, it can be structured or unstructured.
Why is it Important to Analyze IoT Data?
The data emerging from various IoT applications can help in improving the efficiency of these applications. Moreover, the people and business organizations both can use these analytics to make smart decisions. In other words, the IoT data analytics can enable us to get insights into various real-life situations.
IoT is all about smart things. Sensor nodes in an IoT application keep on generating data. While the volume of this data is often very large, it helps in making accurate decisions if we analyze this data appropriately. To further emphasize it, it is important to illustrate with few use cases.
Use Case 1
Consider an example of an IoT application that keeps monitoring customer behavior in a retail store. The IoT nodes present on the smart shelves keep track of the time customers spend there and whether they purchase such items or not. It helps in deciding which items are more profitable.
Use Case 2
The similar applications of IoT data analytics can be found in a public library where the analytics helps in deciding the most preferred section of books.
Use Case 3
Security and surveillance is another important area where better data analytics is helpful. Additionally, it helps in protecting both the people and the infrastructure. Data analytics in such cases can detect unusual activities.
Use Case 4
The analytics on data coming from a Smart TV helps in detecting the consumers’ emotions when a specific advertisement plays. Marketing personnel can use this information to play ads that are interesting to the user.
In a similar way, the analytics on Smart TV data can also help in deciding which events and sports the users prefer to watch.
Use case 5
The analytics on data generated by Smart Energy Meters can help consumers to better manage their energy needs.
All the above use cases describe How Internet-of-Things (IoT) is related to Data Science.
Internet-of-Things (IoT) applications help in improving people’s lives in various ways. As the IoT applications use lots of sensors that generate large volumes of data quickly, it is important to analyze this data that helps us in decision making. Data Science techniques applied to the IoT data can further enhance the quality of these applications by providing us helpful information and enable smart decision making.