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  • Srishti Saha

IoT Data Scraping: All You Need to Know About Scraping IoT Data

Updated: Feb 12, 2021

IoT a.k.a the Internet of Things is not just a buzzword. It is a remarkable piece of technology that converts any physical object into a smart device. IoT is the process of controlling several connected devices using an automated intelligent framework of sensors, analytical and computing capabilities. What drives the IoT infrastructure is the huge volume of data that is generated by all devices and its consumers. Data stored in a centralized location can be processed, analyzed and directed for further computation and actions by the devices. This requires an intricate network to procure, store and reuse IoT data regularly.

Organizations are accomplishing the above process via IoT data scraping.

On gauging the potential of IoT as a technology, one can safely predict that it will penetrate and command the operations of almost every industry. A McKinsey report had stated that barring any major hitches and glitches, using IoT to connect the physical and digital worlds could generate around $11.1 trillion a year in economic value by 2025. This calls for enterprises to invest in building IoT data scraping capabilities which will help them to scrape data from IoT devices and

the network and then, use them to derive actionable insights for the growth of the business.

Let us look at how IoT, data scraping and analytics can be used together to improve market performance.

What is Web Scraping?

Web scraping or web data extraction is the process of pulling data from multiple websites.

This data forms the basis of several other analytical processes and business decisions. One thus needs to store the data in a usable, organized and structured format. A typical Web scraping software crawl over various text and media files available over the Internet. These raw data transforms into useful metrics and records within the blink of an eye. What may take a humungous amount of human effort, automatic Web scraping software and platforms do this job for us within a fraction of its time.

So, how does web scraping exactly transform raw data forms into usable data-sets? There are two ways in which most web scraping platforms function:

  • Extraction of data through an API (application programming interface) or a web interface.

  • Extraction of data from the web-page JSONs (user-friendly JavaScript Object Notations of the web-page and its components) using projects written in various programming languages like Python or R.


How does Data Scraping or Web Scraping work?

Before we delve into IoT data scraping, let us look at how a general web scraping process looks like. The process of web scraping comprises five basic steps:

  1. Crawling – This step replicates the process of browsing in an automated fashion. You have to mention the URLs of the web pages and the software accesses the same.

  2. Scraping – This step collects the data from the web pages that the crawler browsed through. You can compare it to the process of copying data from one place onto the clipboard, to another file- only in a faster and automated manner.

  3. Extracting – Once you have the data, you need to put it in a structured format. This step does precisely that.

  4. Formatting – Since most data-sets feed into analytical platforms, you need to ensure that it is uniform and understandable in its format. Formatting a data-set ensures the data is presentable in a simple file format like csv.

  5. Exporting – Web-scraping automates the data extraction process from one end to the other- including the process of exporting and delivering the data-set to the consumer. The data extraction platforms achieve that in this process using readily available APIs.

When we extend this process to data scraping in general, we could cover a large variety of information sources. Imagine being able to scrape data from a huge corpus of PDF documents or software generated machine drawings. The opportunities are endless. Now that we have understood the various steps in a data scraping process, let us look at how web scraping can enhance the IoT experience for you.

How can Web Scraping enrich the IoT experience?

Since IoT operates on the cardinal concept of data streaming and feedback loops controlling various devices, the network should have uninterrupted access to all forms of data. IoT data scraping is vital to support the hardware and the middleware components of the network.

While the hardware comprises of sensors and physical devices, the middle-ware consists of

routers, connectors, and switches. There is a high volume of high-velocity and high-veracity

data flowing between the connected devices, servers, actuators, and the sensor devices.

How can IoT data extraction help you improve the performance of your business?

IoT data scraping can provide the infrastructure access to accurate data at the right time. This will further empower the IoT network to analyze and then transfer it on to the application interfaces like mobile devices, laptops, and servers. It will allow you to gain insights on critical questions like which data element is the most crucial or adds the most value to the real-world problem.

Moreover, it also helps you decide what data you should relay urgently and determine what data should have a continuous flow for a long time. Imagine being able to get all this information without having to invest in a lot of manual labor and time! Isn’t that exemplary for a piece of technology?

How can such decisions help you extract the maximum potential of the IoT infrastructure?

Data scraped from the web can help you design effective analytical studies and deductions for further application, improve the efficiency of the IoT network or even better the quality of IoT-based-analytics. Moreover, the advantages of IoT data scraping extend into data security applications, statistical studies, metric calculation, and event correlation.

IoT Data Scraping: All You Need to Know About Scraping IOT Data

Application of IoT Data Scraping

People now need data to run any kind of business. It is the new oil that helps operational engines run smoothly. This has caused Data as a Service (DaaS) to flourish as an industry in itself.

Thus, companies like Datahut help various firms procure, churn and process data to influence

their decisions positively. Datahut has helped various firms create business value with scraping

and data extraction services.

A very popular application of IoT data scraping is when you wear a fitness band and use it to monitor your health. Specific enterprises can extract data from the band itself or the back-end system to create more advanced solutions. These solutions include recommender engines for the user to find the most appropriate diet options. It would also encompass a predictive system that can inform the user about possible health updates and precautions if necessary.

Manufacturing companies are scraping IoT data to optimize their operations. Industrial IoT (IIoT) is an upcoming branch of technology. It has garnered a lot of attention in a very short span of time. So, how does an advanced technology like IoT fit into a conservative and conventional space like manufacturing?

Manufacturing floors use sensors to monitor the health of their machines and conveyor belts. You can extract data from these sensors and connectors to predict any operational failure. Information on such processes can then help them take preventive and corrective measures to avoid losses and hence, increase the efficiency and throughput of the manufacturing floor. This leads us to believe that if an industry like manufacturing can adopt advanced data extraction and processing algorithms, any other industry can, as well.

Where else can IoT data scraping be used?

A wide plethora of industries have adopted IoT. These range from healthcare companies to

real-estate enterprises, insurance firms to energy companies and even novel concepts like

self-driving cars and smart cities. Companies are now developing skills or partnering with firms

to scrape valuable data off the Internet and these smart devices. They are then building analytical capabilities to used this data to make more informed business decisions. All these pursuits are

to gain a competitive edge over the rest of the industry. If you don’t want to be left out, you

should definitely jump on to the bandwagon before it is too late.

The hospitality and tourism industry is also investing in data scraping from travel websites, location details from GPS-enabled devices, social media reviews, competitor strategies and prices to gain business intelligence. Web scraping helps several other industries get insights into the customer sentiment and basic market trends. Banking services, retail and even healthcare industries form some of the biggest consumers of the trend.


The information cloud is expanding at a rapid rate. Companies need to tap into this pool of data and explore its potential. By combining the power of unconventional and alternative data, you can unveil latent insights and take more effective business decisions. How do you build the necessary infrastructure and the muscle for the same? You can train your own personnel on the same, which is quite time-consuming.

Another alternative is to partner with companies that provide data extraction and scraping services. Datahut is one such competitive enterprise that plays in the same space. Using state-of-the-art IoT data extraction processes along with advanced predictive analytical algorithms can improve the performance of any industry or a company. 

Wish to leverage web data scraping to grow your business? Contact Datahut, your big data experts.

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