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  1. Home
  2. Volume 9, Issue 7
  3. Author

Online ISSN: 2515-8260

Volume9, Issue7

Machine Learning Trained Edge Computing Device for PhysicallyDisabled

    U.Vijaya Laxmi, V.Vijaya Ramaraju , P.Srividya Devi

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 7, Pages 8994-9001

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Abstract

Biomedical devices play a crucial role in community as these are revolutionizing with breath taking approach in both the medication and the exposure of many diseases. The paper aims to Design edge-based home automation using ESP-32 for Physically Disabled People. Edge computing is an applicable manner to meet the immense estimation and flat-dormancy conditions of deep learning on edge devices and implements increased interests in isolation, bandwidth efficiency, and expandability. ESP-32 receives data from the sound sensor and recognizes the voice command which is already trained and trigger the relay. Automated system using ESP-32 with voice command controls the home appliances. The paper mainly focuses on disabled people to facilitate integrated system that is easy–to–use using Machine learning Technique. The home automation system allows one to control household appliance centralize wireless control unit. This paper aims to control home appliances with user handy, economical, effort less installation for Physically disabled people
Keywords:
    Deep learning ESP-32 Home Automation Supervised Machine Learning
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(2023). Machine Learning Trained Edge Computing Device for PhysicallyDisabled. European Journal of Molecular & Clinical Medicine, 9(7), 8994-9001.
U.Vijaya Laxmi, V.Vijaya Ramaraju , P.Srividya Devi. "Machine Learning Trained Edge Computing Device for PhysicallyDisabled". European Journal of Molecular & Clinical Medicine, 9, 7, 2023, 8994-9001.
(2023). 'Machine Learning Trained Edge Computing Device for PhysicallyDisabled', European Journal of Molecular & Clinical Medicine, 9(7), pp. 8994-9001.
Machine Learning Trained Edge Computing Device for PhysicallyDisabled. European Journal of Molecular & Clinical Medicine, 2023; 9(7): 8994-9001.
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