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Android Based Measurement System with Optical Character Recognition


Affiliations
1 Anna University, Chennai-25,Tamil Nadu, India
2 Fluid Control and Research Institute, Kanjikode, India
3 Anna University, Chennai-25, Tamil Nadu, India
     

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Across the world, electric utilities are deploying smart meters also known as AMI (Automated Metering Infrastructure) to their residential customers and industrial applications. Smart meters provide two-way digital communications between the utility and the customer. Thus, enabling, customer energy management and demand response via both information and rate programs. Utility operational advantages such as outage detection and management, remote meter reading, and remote customer connections are possible by smart meters. Smart meter deployment causes controversies regarding mainly health, privacy and cost. Traditional measurement system met with lot of difficulties in terms of estimated billing and energy wastage. A measurement system lying in between Smart meters and traditional meter reading system is proposed here. Android is the first truly open and comprehensive platform for mobile devices. It is an open-source development platform for creating mobile applications. This application contains OCR (Optical Character Recognition), barcode reader and data transfer applications. A prototype measuring system using Android hand held device is developed. Meter Identity and reading is two important parameters for any measurement system. These two parameters are captured and stored in android data base for future analysis. The consumer data base and meter readings can be exported to PC. A SQlite(Structured Queried Language) data base also created in the PC. Data base can be converted in to CSV (Comma Separated Values) files and can be exported to android device. OCR is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text.

Keywords

AMI, CSV, OCR, SQL.
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  • Android Based Measurement System with Optical Character Recognition

Abstract Views: 254  |  PDF Views: 3

Authors

M. K. Thara
Anna University, Chennai-25,Tamil Nadu, India
M. Suresh
Fluid Control and Research Institute, Kanjikode, India
L. Sheela
Anna University, Chennai-25, Tamil Nadu, India

Abstract


Across the world, electric utilities are deploying smart meters also known as AMI (Automated Metering Infrastructure) to their residential customers and industrial applications. Smart meters provide two-way digital communications between the utility and the customer. Thus, enabling, customer energy management and demand response via both information and rate programs. Utility operational advantages such as outage detection and management, remote meter reading, and remote customer connections are possible by smart meters. Smart meter deployment causes controversies regarding mainly health, privacy and cost. Traditional measurement system met with lot of difficulties in terms of estimated billing and energy wastage. A measurement system lying in between Smart meters and traditional meter reading system is proposed here. Android is the first truly open and comprehensive platform for mobile devices. It is an open-source development platform for creating mobile applications. This application contains OCR (Optical Character Recognition), barcode reader and data transfer applications. A prototype measuring system using Android hand held device is developed. Meter Identity and reading is two important parameters for any measurement system. These two parameters are captured and stored in android data base for future analysis. The consumer data base and meter readings can be exported to PC. A SQlite(Structured Queried Language) data base also created in the PC. Data base can be converted in to CSV (Comma Separated Values) files and can be exported to android device. OCR is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text.

Keywords


AMI, CSV, OCR, SQL.



DOI: https://doi.org/10.36039/ciitaas%2F4%2F5%2F2012%2F106907.194-202