Machine Learning Paradigm for Internet of Things Applications. Группа авторов
When it comes to designing the cities of the future, “smart cities” is the new term. To bring a new brand and distinctive appeal to the lifestyle, smart cities are supposed to be the cornerstone to balancing a prosperous future with sustained economic development and job production.
Cloud-based output and storage face common obstacles to smart city applications. For example, the complexities of cloud-based smart grids include cost-effective provisioning without replacing ageing infrastructure and stable integration of modern capabilities with existing networks [33]. Although the ML has both added advantage and disadvantages, it leads to the deep learning process which enhances development in the technologies like the data visualization in real-time modern world.
Development accomplished by cities is tied to their desire to holistically solve urbanization-based problems and related social, environmental, and economic issues, while at the same time making the most of potential opportunities [30]. It is possible to interpret the smart city idea as a paradigm for incorporating this vision of advanced and modern urbanization. In future, vision is the urban center of the future, making sustainable, safe, eco-friendly, and competitive as all buildings are designed, built, and controlled using new, manufactured materials, sensors, electronics, and networks integrated with computerized systems consisting of databases, surveillance, and de-connected networks.
1.12.4 Conclusion
To make civic processes more cost-effective and environmentally competitive, smart cities make use of digital technologies. By turning streetlights on only when a road is in service, sensors installed in buildings and grid networks will help communities embrace green technologies and conserve electricity [32]. Sensors, smart cards, and digital cameras feed real-time data into advanced control systems, and better infrastructure and analytical technologies will enable decision-making. Rapid urbanization has contributed to extreme road jams as large numbers of citizens choose to enter cities by vehicle. As a result, air pollution has been a major challenge for cities. Development in smart cities has led to the introduction of creative integrated transport networks designed to satisfy the needs of residents. For starters, able to implement real-time mobility systems, smart travel passes, shared car trips, smart vehicles (driverless cars), and personal rapid transit.
One of the largest smart city projects currently taking place is the India Smart Cities Competition, a contest where 100 cities can receive funds from the Ministry of Urban Development and Bloomberg Philanthropies. Competition is meant to promote more innovation from municipal officers and their partners, as well as more involvement from people, in the development of smart city plans [31, 32]. As several critics find out that critical needs such as drinking water and sanitation need to be resolved, this problem has been scrutinized.
Using technologies and data improves resistance to urban problems, through greater efficiencies, and using creativity and industry introduces these fantastic opportunities for our communities. Those with good leadership and productive public-private collaborations working with community participation are the cities positioned to build on these possibilities.
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