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- W3176796398 abstract "This work is about optimizing the existing meters that provide meter reading at the end of the month to the consumers with the help of a person who notes them down manually. This paper mainly highlights the existing methodology of electricity billing that takes place in the households and proposes a method with the aim of requiring minimum human interference and very high efficiency by incorporating data transfer via the internet. Thus without man-power power companies or organizations are able to provide services to its customers by feeding data in an integrated energy management system. The same data will be made accessible to the consumer and billing authorities over cloud. This way the customer is fully aware of his daily consumption. Energy theft is prevalent in the societies and by using this concept we can efficiently mitigate the same. The option of online payment is also included thus making it very convenient for the consumer to pay their bills. Further, using neural networks we have also analysed the trend of energy consumption or requirements of energy in the household. High fidelity billing and its related remote metering services are successfully implemented through this project." @default.
- W3176796398 created "2021-07-05" @default.
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- W3176796398 date "2018-01-01" @default.
- W3176796398 modified "2023-09-27" @default.
- W3176796398 title "Design and Implementation of a Smart Energy Meter Based on Internet of Things and Neural Network Approach" @default.
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- W3176796398 doi "https://doi.org/10.2139/ssrn.3170196" @default.
- W3176796398 hasPublicationYear "2018" @default.
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