Intelligent IoT-Enabled Self-Nursing Framework for Automated Pre-Consultation Medical Assessments

Efficient pre-consultation medical assessments optimize healthcare workflows and enhance patient experience. However, hospitals face bottlenecks due to nursing staff shortages, leading to prolonged waiting times and operational inefficiencies. This paper proposes an loT-enabled self-nursing framework to automate pre-consultation assessments, reducing reliance on personnel while ensuring accuracy and accessibility. The system integrates biometric authentication via national ID and fingerprint recognition with a sensor-driven platform, allowing patients to independently measure vital signs like blood pressure, pulse, oxygen saturation, height, and weight. An IoT-based real-time data transmission mechanism ensures seamless communication with healthcare centers, enabling automated risk assessment, immediate alerts for high-risk patients, and enhanced medical record management. By leveraging automation, IoT connectivity, and patient-driven diagnostics, this scalable solution modernizes pre-consultation healthcare, improving efficiency, accuracy, and accessibility in clinical environments.