How IoT can Help with Data Mining in Public Places

24 February 2021

How IoT can Help with Data Mining in Public Places


Cities around the world have become smarter, adopting various internet of things (IoT) innovations in order to dismantle all the tough problems of living in the city, such as pollution, waste, security and traffic. 

To start disentangling these complex issues cities have started to mine data from public places. Yet, to repeat the word “complexity” just one more time again, these data from the public places are enormously diverse and large-scale. 

Mining the real-time data about traffic, with various devices powered with sensors, actuators and apps, is one thing. Sorting them out and analyzing them properly is another thing.

Although various articles have pointed toward the difficulty of effectively analyzing big data, some latest developments in the IoT realm can possibly make you more confident about adopting them because lately, they have improved their efficiency greatly.

An upbeat outlook

A July 2020 article published by the Journal of King Saud University -- Computer and Information Sciences penned by Priyank Sunhare, Rameez R. Chowdary and Manju Chattopadhyay revealed that all in all, IoT was more efficient in taming the seemingly disparate, large-sized data obtained from various public places.

Some of the latest developments, the article went on to reveal, had been made possible by cloud technologies which had the capacity it took to not only accumulate mammoth-sized data from a highly heterogeneous environment but also to transform them into precious insights. 

The precious insights have been used by various cities to inform intelligent decision making, boost public system performance and optimize management of public resources and services.

Furthermore, an article written by Feng Chen, Pan Deng, Jiafu Wan, Daqiang Zhang, Athanasios V. Vasilakos and Xiaohui Rong published by the International Journal of Distributed Sensor Networks in 2015 revealed that IoT was capable of extracting hidden information from data, allowing you to look at root causes beyond the obvious tip-of-the-iceberg phenomena. 

The article also offers a reassurance that the big data analysis allowed by the IoT system will get better along the way, as the more raw data we collect from the public places, the better the system’s algorithm will become.

With all these new developments and positive outlooks combined, the authors of the 2015 article were confident that IoT had a big business value. 

The data analyzing process and its outputs

Data mining in public places will involve data preparation in the beginning, according to the 2015 article. The preparation involves integrating data into various data sources and cleaning noise from data, extracting some parts of data into a data mining system, as well as pre-process the data to facilitate the data mining. 

Then, algorithms will be applied to the data to find the patterns and evaluate patterns of discovered knowledge. The data will later be presented in a multidimensional visualized form.

Therefore, knowing that the IoT and big data analytics is getting better in time as they mine data on a daily basis, perhaps 2021 is the right time for Jakarta to start considering mining data in public places using the sensors, apps and actuators. 

This will represent the next step in the city’s journey toward a smart city. Perhaps the process will be a little bit hard in the beginning, when these apps have just started to mine the data little by little. 

But with the accumulation of the data, they can actually achieve much more in improving urban life quality, especially in terms of traffic, waste, pollution and security. 

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