Internet of Things (IoT)

The automation is rarely discussed without the Internet of Things (IoT). In fact, The Internet of Things (IoT) development has a surge in recent years, particularly in the last couple of years. Internet of Things enables us to create a network of objects which are not basically intended for connectivity or computation. As a matter of fact, the Internet of Things (IoT) connects the things other than our mobile phones, PC or laptops.

We can drive intelligence from IoT through data which the sensors collect. Sensors receive input from their surroundings and either send data for storage or share with another device. The analytics on this collected data play an important role in smart decision making. Also, it can drive other actuators to perform a certain action.

Role of Data Analytics in IoT

Data is most important entity for an IoT application. Often IoT applications are data intensive. Sensors collect and store large volumes of data. You should drive maximum value from this collected data. Analysing data gives insight into the conditions in which IoT application is working. It gives you meaningful conclusion so that we can improve decision-making.

Role of Data Analytics in IoT

There are different forms of data analytics. If there is a need for quick decision making we need to apply streaming data analytics where we analyze real-time data streams. For instance, in connected vehicles, streaming data need to be analyzed for the quick response. As another example, in a temperature monitoring application of an industrial facility, the immediate action should take place when the temperature crosses a certain threshold.

The second form of data analytics is called spatial analytics where we analyze geographical patterns. This type of analytics is applicable in applications like pet tracking or children tracking where we want to find out the area in which the pet is roaming. Another case where we can apply spatial analytics is monitoring the health of animals in smart irrigation. A wearable device equipped with various sensors for monitoring temperature and other physical conditions can be used for this purpose.

The Time Series analytics allow us to analyze data to determine associated trends and patterns. It has applications in weather forecasting and rainfall prediction so that we can take timely actions.

Descriptive analysis is useful when we want to aggregate data from two or more IoT applications. For instance, suppose a surveillance applications make use of proximity sensor nodes as well as cameras then the descriptive analysis can provide more detail about a certain incident.


Further Reading

Arduino

Role of Sensors in IoT

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