Integrating AI with Green Internet of Things in Healthcare for Achieving UN’s SDGs

Abstract

The integration of the Green Internet of Things (Green-IoT) and Artificial Intelligence (AI) in healthcare has the potential to revolutionize a wide range of industries, including healthcare wherein Green-IoT-connected medical devices and wearables can collect health data, which can be analyzed by AI algorithms to improve patient outcomes and support better decision-making by healthcare professionals. The convergence of AI and IoT in the field of smart health coupled with machine learning algorithms are enabling new and innovative solutions for healthcare delivery and management. AI algorithms and machine learning techniques can be used to analyze vast amounts of data generated by IoT devices, such as wearable devices, sensors, and smart home health devices, to provide insights into patient health and well-being. This research presents a review of patients’ healthcare services. Particularly, we first give an overview of essential parameters of patients’ healthcare services through Green-IoT-enabled sensor technologies under the use case scenario. We then present a basic architecture for IoT-based healthcare systems considering key requirements in the light of the UN’s Sustainable Development Goals discussing their strengths and weaknesses in the context of the framework for patients’ healthcare services. Finally, we explored various security threats for AI-based architecture and their solutions with a comprehensive methodology to design robust and resilient patients healthcare services system needed in the context of the UN’s sustainable development goals.