IoT and data analytics foster similarities, analytics algorithms can prove handy for IoT applications

Geetika Goel during her talk at the event

Data analytics and IoT were the two important technology buzzwords, heard most at the, held this year at the Bengaluru International Exhibition Centre (BIEC).  The event ran for 3 days, from 2nd of March to the 4th. The event focused on bringing together creators of IoT solutions in the fields of electronics design, embedded systems, software development, product-enclosure design, cloud, analytics, system integration, and more.

The expo brought an array of companies and startups across the electronics, IoT, and analytics industries, who featured their unique and innovative product portfolio. The show featured many interesting talks, workshops and sessions on all the three days, revolving around smart industry, profit from IoT, smart buildings, smart automobiles, and more.

The CTO for Jigsaw Academy, Geetika Goel was also present during the event. Geetika presented her talk on the second day of the event. She spoke on the topic, titled “Adapting analytics algorithms for IoT.” The central idea of her talk revolved around drawing comparison between the two emerging areas – data analytics and IoT. She concentrated on discussing how analytical techniques can come handy while approaching IoT for practical applications. Besides, the data obtained from sensors and other IoT eventually are analyzed by data-driven techniques to generate insightful information.

The defining aspects that relate analytics with IoT

During her talk, Geetika focused on explaining the four aspects which relate the two technologies. The similarity between the two makes it possible to leverage analytics-based algorithms for IoT applications. Both the technologies are not that different; you are bound to analyze copious amounts of data in either case.

That being stated, let’s glance through the four crucial attributes:

  •         The volume of the data.
  •         The velocity of the data
  •         The variety in data
  •         Non-reliability of end devices.

The volume of data in the present decade continues to proliferate at an outrageous rate, owing to the increase in the volume of computing devices. “The volume of data obtained today is no more bigger, in fact, it’s gigantic,” comments Geetika. Moreover, the sensors used for IoT applications are extremely tiny and large in numbers. This only implies that there will be more data coming our way. The rate at which the data is being produced also has no bounds. Enterprises are producing huge amounts of data on a regular basis using multiple devices. This increase in velocity of data obtained in case of IoT applications is pretty similar to the field analytics.

Besides the volume and velocity of data, there is need to stress on and comprehend the variety of data types. Geetika pointed out that web data can be unstructured, but most of it is still text data, which is not the case when it comes to IoT data.

The fourth aspect touches upon the non-reliability of end devices, such as sensors, actuators, etc. These devices do most of the important work, i.e., collating data from physical systems, data which could be analyzed and made use of. It becomes necessary to ensure these devices are functioning properly, so that the data obtained is devoid of any error.

Use of IoT to streamline car parking services – a potential use case

Geetika drew an interesting use case for IoT during her talk. She gave the instance of a car parking facility inside a mall to explain a possible IoT application. Usually, there’s a guy at every floor of a parking facility, who guides you to your slot. This person will know the number of empty slots, so that he can guide new vehicles approaching accordingly to the empty slots. However, Geetika brought out this case study to present a scenario where this person is missing. Who will guide those vehicles then?

In the words of the speaker, IoT will help in addressing this challenge. A complete IoT integration of all the slots will be able to determine if a slot is occupied or vacant. Light sensors can be installed in each slot. If there’s no vehicle and the slot senses the light, it is implied that the slot is vacant, and vice versa. Geetika extols, “No additional personnel are required to execute the job of guiding vehicles, implementing this idea. People can easily find the vacant slots on their own.”

Moreover, data scientists can further apply a layer of analytics on this data obtained from implementing IoT technology to obtain more insightful information. The analytics round can help answering few other questions, to generate meaningful insights.

Some of the questions that can pertain to the above example:

  •         Is a particular parking space used very less? Can it be rented out?
  •         Is there any correlation between parking peak time and mall footfall peak time?
  •         Is there any correlation between mall revenue and parking density?

Geetika ended her talk by focusing on the importance of the end devices. Bad devices and sensors can lead to us obtaining inaccurate data, rendering the whole process of applying IoT useless.


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Bhasker Gupta
Bhasker is a techie turned media entrepreneur. Bhasker started AIM in 2012, out of a desire to speak about emerging technologies and their commercial, social and cultural impact. Earlier, Bhasker worked as Vice President at Goldman Sachs. He is a B.Tech from the Indian Institute of Technology, Varanasi and an MBA from the Indian Institute of Management, Lucknow.

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