Internet of Things Based on Compressive Sensing

In this era of digitization, we are moving more and more towards the usage of smart devices. These smart devices includes Smart watches, Smart Phones, Tablet PCs and many other smart hand held devices. These devices comes along with many powerful sensors which are used to collect real time data from the surroundings. These real time data can be later used for various purposes like data analytics, controlling of devices and etc.

Fundamentally IoT Architecture consist of 3 layers:

  • Layer-1:
    This layer deals with sensors, which are used to collect real-time data.
  • Layer-2:
    This is the transmission layer with or without filtering out the useless data.
  • Layer-3:
    It is the Application layer.

In Compression Sensing Based IoT Applications there are 3 layers, but there is a slight difference in the layer 2:-

  • Layer-1:
    This layer collects real-time data just like the one I have mentioned above. This is also called as CS-Based Acquisition Layer.
  • Layer-2:
    This layer is called as the CS-Based Reconstruction layer. This layer plays a crucial role in this entire system. Here the data is filtered out and only the salient features are transmitted to the Cloud. This in turn significantly reduces the network bandwidth utility.
  • Layer-3:
    It is the Application layer. Just like the previous layer.

Importance of Layer 2 in Compression Sensing Based IoT Application:
Usually while collecting real time data from smart devices or from sophisticated IoT devices, the information contains redundant data, which is actually of no use. And if these redundant data is transmitted across the internet then there is unnecessary utilization of the network bandwidth. So to avoid these, help of edge computing is taken. Here at first the collected data is transmitted to a local processing unit that has got ample amount of space and computing capacity to perform various pre-processing techniques to extract various info and features. Only the important information and features that are required is transmitted to the Cloud which in turn significantly reduces the network bandwidth.

Advantages of Using Compression Sensing Based IoT Applications:

  • Energy efficient.
  • Only significant data is transmitted to the Cloud.
  • In the Application layer, Data Analytics algorithms can be implemented on these selectively transmitted data as per the requirements.


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