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A Review on The Application of Machine Learning To Predict The Battery State That Enables A Smart, Low-Cost, Self-Sufficient Drying And Storage System for Agricultural Purposes.

Anak Agung Ngurah Perwira RediRyo Geoffrey WidjajaIwan AgustonoMuhammad AsrolArief S. BudimanFergyanto E. Gunawan
Published in: ICONETSI (2022)
Keyphrases
  • low cost
  • computer vision
  • data sets
  • state space
  • power supply
  • databases
  • social networks
  • feature selection
  • battery powered