Smart City Approaches Using Machine Learning and the IoT

Pandey, Jay Kumar; Veeraiah, Vivek; Talukdar, Suryansh Bhaskar; Talukdar, Veera; Rathod, Vinod Motiram; Dhabliya, Dharmesh

doi:10.4018/978-1-6684-6408-3.ch018

Cited by 2 publications

(1 citation statement)

References 28 publications

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“…Facial expression analysis is one of the most widely studied areas in computer vision-based systems for the SHH [13]- [16]. It has been shown that facial expressions are reliable indicators of emotional changes and can provide valuable information about the patient's mental state [17], [18].…”

Section: Introductionmentioning

confidence: 99%

Improving of Smart Health Houses: Identifying Emotion Recognition using Facial Expression Analysis

SHI,

2024

IJACSA

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Smart health houses have shown great potential for providing advanced healthcare services and support to individuals. Although various computer vision based approaches have been developed, current facial expression analysis methods still have limitations that need to be addressed. This research paper introduces a facial expression analysis technique for emission recognition based on YOLOv4-based algorithm. The proposed method involves the use of a custom dataset for training, validation, and testing of the model. By overcoming the limitations of existing methods, the proposed technique delivers precise and accurate results in detecting subtle changes in facial expressions. Through several experimental and performance evaluation tasks, we have assessed the efficacy of our proposed method and demonstrated its potential to enhance the accuracy of Smart Health Houses. This study emphasizes the importance of addressing emotional well-being in healthcare. As experimental results shown, the prosed method achieved satisfy accuracy rate and the effectiveness of the YOLOv4 model for emotion detection suggests that emotional intelligence training can be a valuable tool in achieving this goal.

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Section: Introductionmentioning

confidence: 99%

Improving of Smart Health Houses: Identifying Emotion Recognition using Facial Expression Analysis

SHI,

2024

IJACSA

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A Review of AI in Medicine

Talukdar,

Sharma,

Lakshmi

2023

Artificial Intelligence in the Age of Nanotechnology

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The field of Artificial Intelligence has great potential in various fields ranging from manufacturing industry to medicine. This study investigates the emergence of Artificial Intelligence (AI) in medicine, looking at their present applications, possible advantages, difficulties, and prospects. The content of the paper provides a preface of recent advances in AI in medicine, highlights the key scenarios where such technologies are already being used in clinical settings, and discusses the challenges that healthcare providers and organizations face when implementing augmented medicine, both in actual patient care and in the training of future medical leaders. The core of the paper also explores how AI is reshaping healthcare in many different ways, from drug development to individualized treatment plans to medical imaging and diagnostics.

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Smart City Approaches Using Machine Learning and the IoT

Cited by 2 publications

References 28 publications

Improving of Smart Health Houses: Identifying Emotion Recognition using Facial Expression Analysis

Improving of Smart Health Houses: Identifying Emotion Recognition using Facial Expression Analysis

A Review of AI in Medicine

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