Abstract
Healthcare 4.0 is about collecting huge amounts of data and getting it to work in applications, enabling healthcare management decisions well-informed while providing for important gains in effectiveness and cost control. Diagnostics based on the digital footprint depend on wearable technology's ability to gather and extract essential patient data. Artificial intelligence (AI) technologies allow the analysis of real-time observed data and continuously developing from data to understand the world surrounding them. To connect and access intelligent healthcare services, people, and devices at any time, a secure wireless mobile communication system is essential. This article suggests a mHealth-based patient monitoring system (mHealth-PMS) based on AI for healthcare 4.0. Mobile healthcare applications motorized by Convolutional Neural Network (CNN) have enabled people to triage their conditions and preemptive treatment decisions. Information collected has been analysed for substantiating cause, and alert and preventive messages have been immediately sent through the mobile application. The performance analysis has been executed, and the proposed mobile application-based surveillance provided much-enhanced reporting of information quickly on diseases, symptoms, factors, and more. The mHealth-PMS strategy shows an accuracy ratio of 95.6%, monitoring ratio of 93.5%, data management ratio of 94.4%, data security ratio of 91.7%, data privacy ratio of 92.1%, prediction ratio of 95.3%, a cost-effective ratio of 25.5% compared to the existing methods.