Machine Learning Techniques Integrated in Robotics, Electrical and Electronics Engineering, and IoT Devices.

@article{1706277,
      author = {Poram Tarun Prakash, P. Satyanarayana Rao},
      title = {Machine Learning Techniques Integrated in Robotics, Electrical and Electronics Engineering, and IoT Devices.},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {3},
      pages = {158-163},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706277.pdf},
      abstract = {This paper aims to find the best machine-learning technique used for integration in robotics, electrical and electronics engineering, and IoT devices. We investigated different recurrent neural networks such as LSTM, BiLSTM, and GRU for combination with Convolution neural networks. We experimented with three different categories related to robotic arms, electrical circuits, and IoT-based smart agriculture. Models are evaluated based on Precision, recall, and F1 score. Finally, we conclude combination of a convolution neural network and a bi-directional long short-term memory model performs well for different predictions.},
      keywords = {Deep Learning, Electrical Systems, Electronics, IoT, Machine Learning, Robotics},
      month = {September},
  }