International Journal of Contemporary Research In Multidisciplinary, 2025;4(2):322-326
Development Of Environmentally Sound Smart Cities with Reduced Energy Consumption Using Green Internet of Things and Big Data
Author Name: Ankur N. Shah;
Paper Type: research paper
Article Information
Abstract:
The development of environmentally sustainable smart cities hinges on innovative advanced technologies that drastically reduce energy usage and enhance urban living. This paper delves into the transformative potential of combining Big Data analytics with the Green Internet of Things (IoT) to achieve these goals. The Green IoT comprises a network of interconnected devices and sensors that monitor and manage energy resources in real-time, facilitating the efficient use of electricity, water, and other essential utilities. By collecting vast amounts of data from these devices, big data analytics can provide actionable insights that can inform smart urban planning and resource management. This synergistic approach optimizes energy consumption, cuts waste, and minimizes the urban environmental carbon footprint. For example, smart grids adjust the energy distribution in response to real-time demand, and intelligent transportation systems can minimize traffic congestion and emissions. Moreover, the integration of these technologies supports the predictive maintenance of infrastructure, prevents energy losses, and prolongs the lifespan of urban assets. This paper highlights case studies of cities effectively implementing Big Data and Green IoT solutions, demonstrating tangible benefits such as cost savings, improved air quality, and enhanced quality of life for residents. Challenges such as data privacy, cybersecurity, and the need for robust regulatory frameworks.
Keywords:
Big Data, Internet of Things, Green Internet of Things
How to Cite this Article:
Ankur N. Shah. Development Of Environmentally Sound Smart Cities with Reduced Energy Consumption Using Green Internet of Things and Big Data. International Journal of Contemporary Research in Multidisciplinary. 2025: 4(2):322-326
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