Smart City Gnosys
Smart city article details
| Title | Machine Learning Based Approach For Energy Management In The Smart City Revolution |
|---|---|
| ID_Doc | 35924 |
| Authors | Deepica S.; Kalavathi S.; Angelin Blessy J.; Vianny D.M.M. |
| Year | 2022 |
| Published | Hybrid Intelligent Approaches for Smart Energy: Practical Applications |
| DOI | http://dx.doi.org/10.1002/9781119821878.ch9 |
| Abstract | The smart city (SC) aims to advance the monetary turn of events, improve government assistance of residents, and help in the capacity of individuals to utilize advances to assemble manageable administrations. Data and communication advancements, wellbeing, energy, the travel industry, development, media communications, data security, transportation, sustenance, sustainable power sources (breeze, sun based, biofuels and so on), squandering the executives and non-usage of energy, atmosphere, and contamination issues ought to be recorded as factors of present-day urbanization and each issue ought to be addressed while building up future brilliant urban regions. Smart city structures and perceptive frameworks should expect to standardize city life by lessening the complexities from the expansion of populace in built-up territories. The advantages of computerized innovation ought to be additionally used to improve government assistance of residents living in urban communities. Fast movement from country to urban regions prompts the rise of urbanization and maintainability issues. The board and checking of resources and frameworks are becoming increasingly significant today in packed urban areas. Energy utilization is expanding with the developing populace and has increased in exceptionally populated parts of urban community. This expanded energy utilization brings about high energy as the creation of toxins is severe, as well as the presence of high temperatures in these cities. The design of the smart city has risen in various landmasses where we have improved road light controls, structure checking, open welfare and scouting, physical precautions, meter peruse, transport exploration, and streamlining frames are conveyed on a city-wide level. The administration of contamination and heat issues prompts an extra energy request. In this way, energy productivity is turning out to be crucial assessment for urban life. For all intents and purposes, all exercises orchestrating city life require energy. For example, work exercises, transportation, security, atmosphere, food, amusement, trade, and so forth. In this study, we survey dynamic and latent methodologies which can be used for development of energy efficiency and manageability of development in present urban communities. We have proposed a machine algorithm for optimizing the energy sources in smart cities. This methodology can be useful for future smart city plans and adequately dealing with our energy resources. © 2022 Scrivener Publishing LLC. |
| Author Keywords | Energy management; Machine learning; Smart city |
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