Data-driven Smart cities

Updated: Oct 16, 2021

The big data revolution is heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities. Big data technologies have become essential to the functioning of cities. Consequently, urban processes and practices are becoming highly responsive to a form of data-driven urbanism that is the key mode of production for smart cities. Such form is increasingly being directed towards tackling the challenges of sustainability in the light of the escalating urbanization trend. This paper investigates how the emerging data-driven smart city is being practiced and justified in terms of the development and implementation of its innovative applied solutions for sustainability.


Smart urbanism: a data-driven approach


The sustainable smart city as a holistic paradigm of urbanism represents an approach to sustainable urban development, a strategic process to achieve the long–term goals of urban sustainability—with support of advanced technologies and their novel applications. Accordingly, achieving the status of such city epitomizes an instance of urban sustainability. This notion refers to a desired (normative) state in which a city strives to retain a balance of the socio–ecological systems through adopting and executing sustainable development strategies as a desired (normative) trajectory. This balance entails improving and advancing the environmental, economic, social, and physical systems of the city in line with the vision of sustainability over the long run—given their interdependence, synergy, and equal importance. This strategic goal requires fostering linkages between scientific research, technological innovations, institutional frameworks, policy formulations, planning practices, and development strategies in relevance to sustainability.


Furthermore, the sustainable smart city relies on constellations of instruments across many scales that are connected through multiple networks augmented with intelligence, which provide and coordinate continuous data regarding the different aspects of urbanity in terms of the flow of decisions about the environmental, economic, social, and physical forms of the city. The evolving research and practice in the field of sustainable smart urbanism tends to focus on harnessing and exploiting the ever–increasing deluge of the data that flood from urban systems and domains by leveraging the value extracted from this deluge through analytics in advancing sustainability.


The Place of Big Data in Smart City Projects


Data-driven smart cities produce different types of data at a dizzying pace. At the beginning of 2018, 39% of smart city IoT projects were related to traffic management. They 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 over one billion connected devices will be installed in private apartments and houses.


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.

Utilities and Energy Management

n 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 rational. 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. For example, smart sensors can be installed on the renewable energy stations. The data they produce can be processed to find out whether a renewable energy source operates correctly. If it doesn’t, a utility provider can make the required adjustments like fine-tuning the solar panel or changing the wind turbine settings or location.


Conclusion


The concept of data-driven smart cities employs data analytics technologies to change the way citizens live, work, and get around. This change is definitely for the better. Big data and smart cities cherish innovations, create new workplaces, and do well for the environment. Despite tangible progress in recent years, the challenges of ubiquitous connectivity continue to grow. It means authorities, tech providers and citizens should ally to make their cities cybersecurity resilient. Fertile land for entrepreneurs, data-driven smart cities are the places where technology can finally increase the quality of life, improve security, and protect nature. Will we see massive prosperity of smart cities in near future? The answer depends on us.

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