| Autor: |
Nanhay Singh, Ramneek Kalra, Shally Gupta |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 IEEE International Conference on Computing, Power and Communication Technologies (GUCON). |
| DOI: |
10.1109/gucon48875.2020.9231101 |
| Popis: |
As of today's technical domains like Cloud Computing, 5G Spectrum, Internet of Things, Machine Learning is leading towards advancement. Such technologies create opportunities for a better environment and more growth in every aspect. But a large number of devices that are being used to provide a better environment to users such as smart IoT devices generates a huge amount of data that needs to be processed locally to reduce network traffic. The possibility of sending such huge amount of data to the cloud every time has led to an increase in latency and requires more bandwidth. To deal with such an issue, a new paradigm has evolved which is known as “Fog Computing”. The vision of Fog computing is decentralized data processing and resource virtualization to produce better and faster results with more reliability. Therefore, we are aiming to perform a simulated method of providing Fog Computing for the automated and transparent solution to Home Electricity Meters, which we called “FogMeter: Computing for Fog Based Electricity Meter”. This proposed method overcomes some of the most probable shortcomings in Indian Based Electricity Meters installed by the Electricity Department of India in Citizens Home. This study will reflect some of the important transparent solutions that will make a smart electricity meter in this upcoming era of Internet of EveryThing. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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