Integrating Artificial Intelligence And Big Data Mining For Iot Healthcare Applications: A Comprehensive Framework For Performance Optimization, Patient-Centric Care, And Sustainable Medical Strategies
Keywords:
Artificial Intelligence, Big Data Analytics, IoT in Healthcare, Performance Enhancement, Patient- Centric Care, Sustainable Healthcare Approaches.Abstract
Background Information: Healthcare systems encounter issues include ineffective resource management,
escalating expenses, and the necessity for individualised patient care. The integration of Artificial Intelligence
(AI), Big Data Mining, and Internet of Things (IoT) technology provides creative solutions to enhance healthcare
efficiency and foster sustainability.
Objectives: The objective of this project is to create a complete framework for optimising performance, providing
patient-centric care, and implementing sustainable strategies in IoT-enabled healthcare systems. Primary
objectives encompass advancing predictive analytics, optimising resource utilisation, and minimising operational
inefficiencies.
Methods: The proposed framework incorporates IoT for real-time data acquisition, Big Data Mining for
actionable insights, and AI for predictive modelling and decision-making. Advanced algorithms analyse diverse
healthcare data, facilitating seamless connectivity and tailored healthcare delivery. Metrics including reaction
time, accuracy, cost efficiency, and resource utilisation are assessed.
Results: The integrated solution surpassed current techniques, with a response time of 0.55 seconds, a prediction
accuracy of 93.2%, resource utilisation of 92.5%, and a patient satisfaction rating of 4.9 out of 5. Cost efficiency
enhanced to 95.5 USD per patient.
Conclusion: The integration enhances healthcare systems through real-time data processing, predictive analytics,
and sustainable resource management, providing scalable and patient-centered solutions for contemporary
healthcare issues.
