Beyond identifying and analyzing the sales capabilities and market landscape, data and analytics can also be leveraged to build a smart city. But what is a smart city, you ask? A smart city can be defined as an urbanized area where various entities cooperate to achieve sustainable outcomes through insights gained from real-time information across domains, sectors, and systems. Smart cities are a combination of buildings, public services, education, healthcare, transportation, and utilities that leverage technology and systems, thereby ensuring connectivity and generating real-time information.
Building a Smart City with IoT and Analytics
A smart city or an urbanized region consists of IoT sensors and network devices that help improve the quality of life and ensure smart usage of resources such as time, energy, and money. Due to the recent surge in the usage of connected devices and the growing popularity of internet of things, big data, and analytics, local authorities have started capitalizing on real-time information to curb traffic, pollution levels, crime rates, and energy consumption. Predictive analytics is a form of advanced data analytics that enables decision-makers to make future predictions using various analytical techniques such as predictive modeling and data mining to study past patterns and forecast the future. How is this possible, you ask? Here are the top four applications of predictive analytics in building a smart city.
- Intelligent weather adaptive lighting enables smart power and electricity; thereby, eliminating energy wastage and ensuring optimum utilization of resources
- IoT enabled sensors and networks use cloud-based architecture and big data automation to offer real-time traffic support, creates flexible and efficient public transport, monitoring driver behavior, and decreasing road accidents. Smart transportation management enables drivers to locate the nearest available parking slot and receive notifications through a mobile interface
- Predictive analytics helps local authorities and police department to predict crime rates and locations by leveraging past data and location history. Analytics is a key enabler to ensure smart security and create safer cities through insights gained from various data streams
Contact us to know more about the role of big data and predictive analytics in smart city planning.
- For building a smart city, local authorities must ensure an efficient and robust city planning strategy. Data and analytics can be used to gain insights into building zoning, amenity creation, and other infrastructural elements in the city. Smart city planning ensures the implementation of city models that maximizes area accessibility, minimizes overloading risks, and ensures optimum usage of infrastructural spaces with a high level of accuracy and flexibility