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Role of Big Data Analytics in Smart City Projects


October 29, 2021

Big data solutions include storage, backup, analysis, and visualization, as well as administrative controls for enormous volumes of data. Big data solutions make a complicated data infrastructure more efficient. Furthermore, big data technologies allow smart cities to leverage expanded capabilities. Internet of Things (IoT) technologies, smart sensors, smart transportation, and other innovations are all part of this. This article tells you the fundamental principles of a smart city and how big data affects them.


What is a Smart City?

Sensors and linked gadgets are used in smart cities to gather and evaluate data. This information is utilized to enhance city operations, manage the resources, and improve inhabitants’ daily lives. Smart cities use technology to enhance public transportation, traffic management, water and electricity supply, law enforcement, schools, and hospitals, among other things.


How Big Data Impacts Smart Cities?


Citizens’ safety is a major concern for every community, and it is critical to safeguard them in any situation. To avoid any problems in the city, the predictive analysis may be used to look at historical and geographic data to see when and where crimes are most likely to occur. When the necessary data transforms a city into a safer environment, a large quantity of progress will be visible.


City Planning

The sensors installed in the city offer a clear image of what is missing in a city and how to improve the present condition. Analyzing a city’s present needs with the use of data can aid in finding areas that require repair and updating. When you utilize extremely precise data to indicate exactly where growth is needed, modeling infrastructure needs in a city is simple.



When big data comes to the rescue, transportation can be readily handled. Everyone despises traffic, but it is feasible to reduce it by properly utilizing previous data. You may investigate trends that will result in reduced traffic congestion and assist transport authorities in developing smarter ways to manage and monitor transportation inside the city by analyzing data obtained from transportation authorities. Accidents will be reduced thanks to big data analytics.



Our cities are becoming smarter by the day as a result of increased urbanization, and there are still a number of plans in the works to fully transform the smart cities of the future. Inside the city, there is a technology for intelligent traffic management, as well as real-time administration and monitoring. Data gathered from a variety of sources may be used to create a more sustainable environment with improved energy efficiency and reduced resource waste. It is feasible to examine the expansion of present infrastructure and prepare for the city’s future demands using predictive analysis.



Regularly monitoring a city’s development will offer ongoing development updates, allowing appropriate improvements to be made as needed. The number of products created when the technology is implemented will provide a clear picture of the development required, which is among the keys to long-term sustainability. Data is a key aspect in determining the outcomes of city development. Changes may be made in the city, but maintaining the current level of growth is tough.


Effective Spending

Making the required improvements and achieving the desired results that would transform a city requires a significant amount of money. Money is often spent on the rehabilitation or remodeling of a city, which is classified as modest infrastructure upgrades. Data acquired in a smart city might identify severely impacted locations and what sort of renovations are required using big data analytics. Investments in the appropriate domains can be made based on thorough analysis.


Smart City Data Storage

Cloud Storage

For analytical reasons, smart cities require a vast volume of data. In their data centers, cloud data systems employ solid-state drives, delete redundant data, and secure data transfer. Payment choices for cloud-based systems are frequently more flexible than those for on-premise data centers.


Edge Computing

You may process data near the source with edge computing. Streaming data to a distant storage site and subsequently to appropriate city authorities might be more expensive than using edge computing. In certain places, edge computing capabilities such as artificial intelligence (AI) traffic control are already being developed. Intelligent automation is used in AI traffic management to identify traffic congestion and accidents and give faster responses to various circumstances.


Hybrid Data Storage

The advantages of cloud and edge storage are combined in hybrid data storage systems. Cities may make new judgments based on real-time warnings on situations as well as rich data repositories thanks to hybrid data storage.



Big data plays a significant part in a smart city’s processing of data gathered via IoT devices so that additional analysis may be performed to identify trends and requirements in the city. Sensors deployed across the city create massive quantities of data, but if it is used efficiently, it may lead to numerous changes. Cities can discover trends and requirements by analyzing data from IoT devices and sensors. The analysis can assist drivers to find a parking place and minimizing the number of road accidents and congestion. Data may also help with crime reduction, smart city lighting, and water and electricity systems.

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