Developing Energy-Efficient IoT Architecture with Edge and Fog Computing for Smart Cities
Internet of Things (IoT) technologies are being used in smart towns because people want more clever, efficient, and environmentally friendly systems. But the fact that these methods use a lot of energy is still a big worry. This article talks about creating an IoT design that uses less energy by using Edge and Fog Computing to make the best use of resources and boost speed in smart city apps. The suggested design uses both Edge Computing and Fog Computing. Edge devices process data locally, which means they don't need to use cloud services as much. Fog nodes bring processing even closer to the edge of the network, which ensures low delay and low energy use. The design includes energy-aware programs that make the best use of real-time energy supply and network conditions to send and process data. Our results show that smart city IoT systems actually use a lot less energy and work much more efficiently. We use a lot of models to show that moving processing from the cloud to the edge and fog layers can cut the total amount of energy needed by up to 30%. The suggested structure also guarantees very little delay in data processing, which is very important for real-time smart city applications like tracking the environment, managing traffic, and collecting trash. The results show that combining Edge and Fog Computing can make IoT systems in smart towns more energy-efficient.
Authors
- Monali Gulhane (ORCID: https://orcid.org/0000-0001-5017-1738)
- Dharmesh Dhabliya (ORCID: https://orcid.org/0000-0002-6340-2993)
- Sheetal R. Kashid
- Yatin Gandhi (ORCID: https://orcid.org/0009-0001-1479-2796)
- Ankita Tiwari (ORCID: https://orcid.org/0000-0001-6433-7831)
- Saurabh Bhattacharya (ORCID: https://orcid.org/0000-0002-4202-8437)
Institutions
- Galgotias University (IN)
- International Institute of Information Technology (IN)
- Symbiosis International University (IN)
- MIT Art, Design and Technology University (IN)
- Koneru Lakshmaiah Education Foundation (IN)
Publication Details
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1109/esci63694.2025.10988125
- Primary Topic
- Human Mobility and Location-Based Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00