Machine learning based power saving mechanism for fridge: An experimental study using GISMO III board

Author:

Ganapathi Raju N.V.,Radhanand A.,Balaji Kumar K.N.,Pradeep Reddy G.,Sampath Krishna Reddy P.

Publisher

Elsevier BV

Subject

General Medicine

Reference12 articles.

1. S. Qiao, H. Zhu, L. Zheng and J. Ding, “Intelligent Refrigerator Based on Internet of Things,” 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Guangzhou, 2017, pp. 406-409

2. Gao, Y., Lian, J. & Gong, B. Automatic classification of refrigerator using doubly convolutional neural network with jointly optimized classification loss and similarity loss.J Image Video Proc.2018,93(2018).https://doi.org/10.1186/s13640-018-0329-z

3. Thermal and Energy Evaluation of a Domestic Refrigerator under the Influence of the Thermal Load;Belman-Flores;Energies,2019

4. M. Pritoni M. Graziano (2017). Cloudfridge: A Cloud-Based Control System for Commercial Refrigeration Systems.Lawrence Berkeley National Laboratory. https://escholarship.org/uc/item/12f2q9ff

5. Osisanwo, Folasade, Shade Kuyoro, and OludeleAwodele. “Internet refrigerator–A typical internet of things (IoT).” 3rd International Conference on Advances in Engineering Sciences & Applied Mathematics (ICAESAM’2015), London (UK). http://iieng. org/images/proceedings pdf. 2015

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