
How Big Data Applications can Trigger Smart City Innovations
Big data is acknowledging common problems in smart cities and addressing them with other emerging technologies.
Smart city is a buzzword heard both in the technology and government sectors. Upgrading the normal city to an unprecedented development level has been a dream for governments and leaders across the globe. The mission is nearing the possible mark with smart Artificial Intelligence (AI) applications like big data. The emerging technology is acknowledging common problems in the city and uses other features to address them.
Smart cities are the developed hub that uses sensors and connected devices to collect and analyze data. The data is used to optimize city operations, manage resources, and improve citizens’ everyday lives. They are the need of the hour when the sustainable development of every sector in society is necessary. The world is undergoing a major crisis of the growing population. But the natural and social resources are drastically plummeting. To tackle the challenge, the only exit door that we have is to make cities smart and make energy sources renewable. Smart cities have the biggest advantage of minimizing energy usage, which can benefit both financial and ecological aspects. The expansion of big data has played a pivotal role in the feasibility of smart city initiatives. Big data leverages the facility to obtain valuable insights from a large amount of data collected through various sources, and Internet of Things devices like the integration of sensors, radio-frequency identification, and Bluetooth helps collect real-world information.
Governments and leaders are also considering adopting the smart city concept in their cities and implementing big data applications that support smart city components to reach the required development level. Cisco estimates that cities that run on information can improve their energy efficiency by 30% within 20 years. Remarkably, the smart city’s IT market opportunity is expected to be at US$34 billion annually. Some of the high-end smart cities that are reaching full-fledged implementation of technology are Barcelona, Amsterdam, Seoul, Santa Cruz, New Songdo City, etc.
Applications of big data in smart city management
Smart education
Providing smart educations to everyone is on priority. A smart education system enhances the education processes’ efficiency, effectiveness, and productivity. Big data unravel the facility to provide better use of information, enhanced control and assessment, and higher support for life-long learning for all people. People who enroll in smart education will get an overview of how technologies can impact the city to perform better. This will help them adapt to the rapid changes in society.
Smart mobility and transport
Cities, especially smart cities, are exploding in population. This leads to massive traffic congestions. However, with big data, the flow of transportation, both public and private, can be monitored closely to sort the times and areas of high traffic inflow. One of the main aspects of smart cities is smart traffic lights and congestions. Smart traffic lights are interconnected to traffic grids to offer more information on traffic patterns.
Smart healthcare
Smart healthcare facilities in cities help treat the patients quickly, and at the same time, manages people from ending up in public health risk. The big data collected from various sources in smart cities is used to detect diseases even before it turns to be an epidemic or a pandemic. Smart sensors can also gather data from medical facilities and detect the spread of diseases.
Smart grid
In a smart grid environment, a large amount of data is generated from different sources such as power utilization habits of users, phasor measurement data for situational awareness, and energy consumption data measured by widespread smart meters. This gathered data can be used to make wise decisions based on their predicted outcomes. In the future, the predictive analysis on the smart grid is anticipated even to sort out power supply decisions.