The Role of Smart Buildings in the Digital Transformation Era: Insight on China

Veglianti, Eleonora; Li, Yaya; Marco, Marco De

doi:10.1007/978-3-030-85893-3_6

Cited by 1 publication

(1 citation statement)

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“…To promote the concept of smart cities across multiple continents [19], this offers a variety of suggestions, including but not limited to: urban planning; improved traffic management; network monitoring; public safety and health and supervision; security protocols; gunfire recognition; metres; and transit analysis. The Internet of Things was made possible thanks to smart buildings that provided users with access to low-cost IoT services.…”

Section: Related Workmentioning

confidence: 99%

A Novel Energy Optimization System for Renewable Demand using Heuristics, Distributed Systems, and Machine Learning in a Smart City

Duraipandy¹,

Prabhu²,

Alshehri³

et al. 2022

Preprint

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Transportation, environmental conditions, quality of human life within smart cities, and system infrastructure have all needed practical and dependable smart solutions as urbanization has accelerated in recent years. In addition, the emerging Internet of Things (IoT) provides access to a plethora of cutting-edge, all-encompassing apps for smart cities, all of which contribute significantly to lowering energy consumption and other negative environmental impacts. For smart cities to meet the challenge of using less energy, the authors of this research article suggest planning and implementing an integrated power and heat architecture that puts renewable energy infrastructure and energy-storage infrastructure at the top of the list. To address these issues, we describe a smart proposed NEOSRD architecture that uses a distributed smart area domain to optimize renewable demand energy in a smart city across a wide area network. The energy requirements of desalination procedures are negligible when compared to the total local energy consumption and transportation, a feat accomplished by the proposed NEOSRD system. Here, the computational model shows how the established system is a valuable response to our problems and a cost-effective strategy for creating smarter structural elements that cut down on overall smart cities' energy costs.

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Section: Related Workmentioning

confidence: 99%