Design and Implementation of a Prototype Automatic Reading System for the Consumers’ Electrical Energy Meters

The biggest problems of our time are environmental pollution and the reduction of fossil fuel resources. In recent years, photovoltaic (PV) has started to be used efficiently in order to produce electrical energy from solar energy throughout the world. In this study, a wheat mover machine taking its energy with PV technology transformation from the sun was designed supported by smart sensors. The designed vehicle was tested in two wheat fields in Sivas in Turkey. It was seen that daily average sunshine rates were not lower than 700 Watt/m2during the testing dates and time. The amounts of electrical charge used to mow 5 m2and 50 m2areas are obtained as 500 mAh and 3395 mAh, respectively. Also maximum power is calculated from used PV panel as 26.15 Watt during the day of the experiments. The range of solar radiation intensity is found 4.5 kWh/m2/day at the studied kWh which was$0.140 USD on the date of November 2015. This system is 94.5% more economic than conventional mowers over an area of 1000 m2.

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The estimation of electrical energy consumption in abnormal automatic meter reading system using multiple linear regression

2013 International Conference on Electrical Machines and Systems (ICEMS) ◽

10.1109/icems.2013.6713143 ◽

2013 ◽

Cited By ~ 3

Author(s):

V. Kantikoon ◽

V. Kinnares

Keyword(s):

Energy Consumption ◽

Linear Regression ◽

Multiple Linear Regression ◽

Electrical Energy ◽

Electrical Energy Consumption ◽

Automatic Meter Reading ◽

Automatic Meter Reading System ◽

Reading System

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Design and Implementation of Wireless Electric Power Meter Based on XBee Model

Iraqi Journal for Computers and Informatics ◽

10.25195/ijci.v41i1.92 ◽

2014 ◽

Vol 41 (1) ◽

pp. 15-19

Author(s):

Mofeed Rashid

Keyword(s):

Electric Power ◽

Electrical Energy ◽

Gulf War ◽

Wireless Sensor ◽

Electrical Energy Consumption ◽

Power Meter ◽

Design And Implementation ◽

Central Computer ◽

Measurement Devices ◽

Electric Power Meter

Since the 1991 Gulf War, Iraq is still suffering from the crisis and irregular in the processing of electric power to customers.Damage to the network, the old measurement devices for measuring electrical energy consumption, and irregularities and corruption in theprocess of measuring and calculating fees of the consumption, all these reasons led to the deterioration of the performance of thedistribution network in Iraq. In this paper, Wireless Electric Power Meter Based on XBee Module has been designed and implementedwhich ZigBee wireless sensor network (WSN) will be used for wireless electric power meter communication supported by PICmicrocontroller which used for power unit measurements. Wireless metering system will be controlled by central computer which place inbase station; also database will be design to record and manage all data and information of consumers.

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An Unsupervised Classification Technique for Detection of Flipped Orientations in Document Images

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i5.pp2140-2149 ◽

2016 ◽

Vol 6 (5) ◽

pp. 2140

Author(s):

Vijayashree CS ◽

Shobha Rani ◽

Vasudev T

Keyword(s):

Unsupervised Learning ◽

Unsupervised Classification ◽

Document Image ◽

Document Images ◽

Orientation Direction ◽

Average Accuracy ◽

Direction Detection ◽

Automatic Reading ◽

Reading System ◽

Specific Orientation

<table width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>Detection of text orientation in document images is of preliminary concern prior to processing of documents by Optical Character Reader. The text direction in document images should exist generally in a specific orientation, i.e., text direction for any automated document reading system. The flipped text orientation leads to an unambiguous result in such fully automated systems. In this paper, we focus on development of text orientation direction detection module which can be incorporated as the perquisite process in automatic reading system. Orientation direction detection of text is performed through employing directional gradient features of document image and adapts an unsupervised learning approach for detection of flipped text orientation at which the document has been originally fed into scanning device. The unsupervised learning is built on the directional gradient features of text of document based on four possible different orientations. The algorithm is experimented on document samples of printed plain English text as well as filled in pre-printed forms of Telugu script. The outcome attained by algorithm proves to be consistent and adequate with an average accuracy around 94%.</p></td></tr></tbody></table>

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