Data-Driven Smart Cities: From Big Data to Security
Yesterday, living in data-driven smart cities was perceived as a science-fiction fantasy. Today, city administrators have introduced a Chief Data Officer role to make the most of sophisticated data services. Big Data and smart cities are two terms more frequently used together. All because, among other, data-driven smart cities have raised the quality of life for people around the globe. We discuss data science developments to find out which urban services could benefit the most from Big Data and analytics.
Modern terminology defines smart cities as government entities with common practices of collecting digital data from citizens, infrastructure objects, and electronic devices for various administrative and managing purposes. But, it’s the ability to leverage data that gives meaning to the smart city notion. Big Data and smart cities are a perfect pair for a wide range of urban services, including traffic and transportation, data-driven healthcare, water supply, waste management, law enforcement, and others.
In a broader sense, data-driven smart cities are at the top level of tech-enabled urban progress. The combination of Big Data and smart cities solutions promotes innovations and increases educational incentives. It builds a bridge between citizens and tech advancements. Plus, it establishes a digital connection between society and government, offering a new level of goods and services to local communities.
Data-driven smart cities produce different types of data at a dizzying pace. At the beginning of 2018, 39 percent of smart city IoT projects were related to traffic management. Those projects are followed by IoT projects to manage utilities, lightning, environmental protection, and public safety. The smallest number of IoT projects within a smart city segment relates to electric vehicle charging. Supporting the smart home concept, it’s predicted that over one billion connected devices will be installed in private apartments and houses.
Let’s have a closer look at each of the segments extensively using Big Data and analytics.
Transportation is a huge and indispensable constituent of a smart city ecosystem. Living up to the prediction of world population growth and cities becoming more crowded, Big Data and analytics come to the rescue in transportation. Municipal transportation systems can leverage Big Data to optimize routes and schedules, decrease traffic congestion, and increase environmental friendliness. Big Data analytics and historical data help in reducing accidents. By analyzing the history of mishaps, traffic authorities can get the cause of the accidents to prevent them in practice.
The data going back and forth within a traffic infrastructure can optimize goods transportation. Analytics help to find alternative routes and decrease the number of accidents connected with the freight movements. In this way, data-driven smart cities receive improved shipment processes and reduced supply chain waste.
Among other options, data-driven transportation systems can lower the environmental impact, facilitate smart parking applications, improve user experience, and add to smart city security.
In data-driven smart cities, Big Data and analytics help utilities to gain operational efficiency. Authorities and citizens start considering not only how to deplete resources but also how to make their use rationale. Utility management has witnessed the rise of ‘smart everything:’ smart grids, smart water, and smart energy. The rapid distribution of smart grids has enabled analysis of real-time power generation and consumption data. The analytics of power use habits of citizens and industrial objects can help predict the need for the power supply in the future. In practice, a smart grid can redistribute electricity from areas with excess to the spots where it’s really needed.
Big Data and smart cities can help in the coordination of wind and solar energy with traditional energy sources.
