Comments (5)
Hi, Aleonnet,
thanks for your issue. A conference paper about this approach is on the way. Actually, from the perspective of application, the performance of DNN-based approaches in the existing researches is quite close.
As for the real time disaggregation, I think Raspberry's computing power should cover this approach of such size. And I'm sorry that I haven't tested it on any mobile platform(including Raspberry pi). You can test it. I'm also looking forward to your test.
Several related papers maybe useful for you:
Sequence-to-point learning with neural networks for nonintrusive load monitoring
Sliding Window Approach for Online Energy Disaggregation Using Artificial Neural Networks
Neural Network Ensembles to Real-time Identification of Plug-level Appliance Measurements
Good Luck!
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Hi, Aleonnet,
I replied you on an e-mail client, not on github, maybe you can not see the attached image on github.
Here you can have a try.
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Hi @ZhangRaymond
I'm trying to check some results. How do you generate pickle per house?
FileNotFoundError: [Errno 2] No such file or directory: 'data/house_2.pickle'
Thanks!
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Hi Zhang,
What do you mean by "I attached an inner structure image of house_{}.pickle for you"?
There's nothing attached...
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