The impact of data analytics on smart cities

Smart city projects are already commenced in nearly 280 cities around the globe. As per a study by Navigant Research, the global smart city technology sums to $97 billion in 2019 and this is expected to reach almost $1.7 trillion over the next decade.

Check how data analytics can lend a helping hand in designing intelligent cities and tackle urban problems fruitfully.

How data analytics can help in building smart cities

• Glean insights from diverse data sources

To make a city, smart, urban planners require data from multiple sources. A composite of geospatial data, traffic data, foot traffic on streets, crime statistics, vehicle data, carbon footprint data, and many such are essential for city planners to sketch the smart city blueprint. Through machine learning and data analytics, such insights can be extracted seamlessly from various sources.

• Predict the future and plan accordingly

A smart city plan should be laid with both the present and the future in mind. With data analytics, urban planners can manage dynamic factors like population, lifestyle, vehicle population, etc. while building programs and policies for smart city management. Also, through predictive analytics, modern architects can statistically foresee the future needs of the city along with the changes it may encounter and plan accordingly.

• Improve data security

As AI will play a vital role in the smart city growth story, it is crucial to strengthen data security while shaping the virtual environment. Using operational analytics – a subset of data analytics, vulnerabilities, and security holes can be promptly detected, and data security can be enhanced largely.

Some real-time impact of data analytics on smart cities

• Effective Spending

Budget allocation has been a major challenge for smart cities. Most times large funding goes wasted on vanity projects leaving less for vital projects. Through data analytics, elected officials and urban planners can track spending and optimize budgets adequately.

• Transport

Transport can be greatly regulated with data analytics. Leveraging data analytics helps minimize congestions and delays and improve the efficiency of transport networks. Furthermore, predictive analytics can help foresee transport demands during special events and make public transport arrangements appropriately.

Remember the London 2012 Olympics? The city had to cope with 18 million journeys made by spectators, and it was no miracle the TFL and train operators handled the situation smoothly. It is through data analytics that the operators could create an effective and flexible transport network for the city during that time.

• Streamline Web Provision

Smart cities are primarily dependent on the ‘connectivity’ factors of devices. Fast internet speed and web access are essential for a good connection in the digital space. Identifying correct areas and people is crucial to streamline bandwidth in smart cities.

To give a clear picture, commercial and financial areas may require more bandwidth from Monday to Friday, while residential areas may require more bandwidth on Saturday and Sunday. With data analytics, smart cities can shift bandwidth within cities effectively.

Real-time challenges with big data analytics for smart city development

While data analytics empowers smart city development, it also comes with its set of challenges. Below are some of them.

• Data Integration

Data integration is a key requisite to live the smart city vision. While data integration within organizations is a current-day challenge in the IT world, integration of data across different environments, organizations and smart devices can be even more complicated and painful.

• Data Privacy

Another concern with the evolution of smart cities is data privacy. This is a sore point as the ubiquitous data can no longer be easily accessed or utilized for advancement purposes. Besides, National and international data privacy regulation like EU GDPR (General Data Protection Regulation) proactively ensures that data compliance regulations are stringently followed while establishing smart cities programs.

• Lack of data skills

Last but not the least, skill gaps will be a major setback in the digital landscape. Right skill sets are essential for effective policymaking and handling the big data efficiently with technology’s assistance. However, the increase in the number of professionals in the field of Data science should help handle the challenge effectively.

On the Whole

Apart from industries and businesses, urban development is also driven by big data. This makes it essential to leverage sophisticated data tools and algorithms to make cities smart, sustainable, and healthier across the world. With the capabilities to harness real-time and granular data, data analytics can surely afford to develop smart cities successfully.

Harsh is a passionate author and loves spreading knowledge throughout her writing. He's proficient in social media marketing, brand strategy, email marketing, Seo, Google Analytics. He's also passionate about content writing and graphic designing.