Sathishkumar V E

The fast development of urban advancement in the past decade requires reasonable and realistic solutions for transport, building infrastructure, natural conditions, and personal satisfaction in smart cities. This paper presents and explores predictive energy consumption models based on data-mining techniques for a smart small-scale steel industry in South Korea. Energy consumption data is collected using IoT based systems and used for prediction.

DOI Link: 
10.21227/112a-dk82
Links or DOI: 
Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city
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[1] Sathishkumar V E, "Steel Industry Energy Consumption", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/112a-dk82. Accessed: Jan. 02, 2025.
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doi = {10.21227/112a-dk82},
url = {http://dx.doi.org/10.21227/112a-dk82},
author = {Sathishkumar V E },
publisher = {IEEE Dataport},
title = {Steel Industry Energy Consumption},
year = {2022} }
TY - DATA
T1 - Steel Industry Energy Consumption
AU - Sathishkumar V E
PY - 2022
PB - IEEE Dataport
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Sathishkumar V E. (2022). Steel Industry Energy Consumption. IEEE Dataport. http://dx.doi.org/10.21227/112a-dk82
Sathishkumar V E, 2022. Steel Industry Energy Consumption. Available at: http://dx.doi.org/10.21227/112a-dk82.
Sathishkumar V E. (2022). "Steel Industry Energy Consumption." Web.
1. Sathishkumar V E. Steel Industry Energy Consumption [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/112a-dk82
Sathishkumar V E. "Steel Industry Energy Consumption." doi: 10.21227/112a-dk82