TY - GEN
T1 - Automatic reading of electro-mechanical utility meters
AU - Ocampo-Vega, Ricardo
AU - Sanchez-Ante, Gildardo
AU - Falcón-Morales, Luis E.
AU - Sossa, Humberto
PY - 2013
Y1 - 2013
N2 - Electro-mechanical meters are commonly employed to measure the consumption of utilities. Basically there exist two types of analog meters: the ones that use rotary dials (like an odometer) and the ones with pointer dials (like a speedometer). Former approaches to automated meter reading have dealt with the first kind of meters. Considering that automated reading of the latter ones can be confusing, in this work we introduce a methodology based on image processing and segmentation to enable the image acquisition and processing of pointer dials to obtain efficiently and accurately readings. This methodology uses an image acquired with a smartphone and by applying a sequence of image processing functions it finds and extracts the dial images of such meter images. Then the methodology identifies the position of the pointers followed by a clever implementation that enables the reading. The database is composed with more than a hundred images taken under different light conditions, perspectives and angles. The method is able to extract the reading in an average of 3 seconds, with a 92% accuracy with images taken in-field. Our method, enables the use of a common smartphone to acquire and automatically extract the reading of a pointer-type dial meter. This allows interesting applications that could help people to monitor their energy consumption and learn patterns to save energy. This could be one step ahead of energy saving policies that can be discovered through massive data analysis.
AB - Electro-mechanical meters are commonly employed to measure the consumption of utilities. Basically there exist two types of analog meters: the ones that use rotary dials (like an odometer) and the ones with pointer dials (like a speedometer). Former approaches to automated meter reading have dealt with the first kind of meters. Considering that automated reading of the latter ones can be confusing, in this work we introduce a methodology based on image processing and segmentation to enable the image acquisition and processing of pointer dials to obtain efficiently and accurately readings. This methodology uses an image acquired with a smartphone and by applying a sequence of image processing functions it finds and extracts the dial images of such meter images. Then the methodology identifies the position of the pointers followed by a clever implementation that enables the reading. The database is composed with more than a hundred images taken under different light conditions, perspectives and angles. The method is able to extract the reading in an average of 3 seconds, with a 92% accuracy with images taken in-field. Our method, enables the use of a common smartphone to acquire and automatically extract the reading of a pointer-type dial meter. This allows interesting applications that could help people to monitor their energy consumption and learn patterns to save energy. This could be one step ahead of energy saving policies that can be discovered through massive data analysis.
KW - Image enhancement
KW - Image segmentation
UR - http://www.scopus.com/inward/record.url?scp=84894213302&partnerID=8YFLogxK
U2 - 10.1109/MICAI.2013.28
DO - 10.1109/MICAI.2013.28
M3 - Contribución a la conferencia
AN - SCOPUS:84894213302
SN - 9781479926053
T3 - Proceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
SP - 164
EP - 170
BT - Proceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
T2 - Proceedings - 2013 12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Y2 - 24 November 2013 through 30 November 2013
ER -