Search

Con la rápida transformación digital, la medicina de precisión ha sido una parte esencial para elevar la conciencia de la atención médica con respecto al modelo biopsicosocial con la ayuda de sistemas de monitoreo remoto de pacientes. Los gemelos digitales han tenido éxito en muchas industrias, en la atención médica puede optimizar el bienestar del cuerpo humano para mejorar el bienestar físico y mental, incluidas las poblaciones enfermas no diagnosticadas y las poblaciones rurales. En este artículo, discutimos los desafíos en términos de computación para implementar un sistema complejo llamado Wellness Digital Twin-based Remote Patient Monitoring. Siguiendo la Ingeniería de Sistemas Basada en Modelos, presentamos la definición y las necesidades del gemelo digital en el contexto del Bienestar y la atención médica, un estudio de viabilidad seguido de un concepto de operaciones. Posteriormente, presentamos los requisitos y la arquitectura, incluida la computación en memoria (memorias emergentes no volátiles, dispositivos memristivos) que mejorarán la detección, el análisis y las palancas de acción., With fast-paced digital transformation, precision medicine has been an essential part to elevate the conscience of healthcare with respect to the biopsychosocial model with the help of Remote Patient Monitoring Systems. Digital twins have been successful in many industries, in healthcare, it can optimize the wellness of the human body to improve physical and mental wellness including the non-diagnosed diseased populations and rural populations. In this paper, we discuss the challenges in terms of computing to implement a complex system called Wellness Digital Twin-based Remote Patient Monitoring System following Model-Based Systems Engineering (MBSE), we present the definition, needs of the digital twin in the context of wellness and healthcare, a feasibility study followed by a concept of operations. Subsequently, we present the requirements and architecture including In-memory computing, (Emerging Non-Volatile Memories, memristive devices) that will enhance sensing, analytics, and levers of action

The standard for measuring solar irradiance utilizes the units of watts per meter squared (W/m2). Irradiance meters are both costly and limited in the ability to measure low irradiance values. With a lower cost and higher sensitivity in low light conditions, light meters measure luminous flux per unit area (illuminance) utilizing the units of lumens per meter squared or lux (lx). An effective conversion factor between W/m2 and lx would enable the use of light meters to evaluate photovoltaic performance under low solar irradiance conditions. A survey of the literature found no definitive and readily available “rule of thumb” conversion standard between solar irradiance and illuminance. Easy-to-find Internet sources contain conflicting and widely varying values ranging from 688449 to 21000 lx for 1000 W/m2 (1 Sun) of solar irradiance. Peer-reviewed literature contains Luminous Efficacy equivalent values ranging from 21 to 131 lx per W/m2. This manuscript explores the relationship and establishes a theoretical and laboratory measurement guide for the conversion between solar irradiance and illuminance. The conversion factor includes standards data, equipment calibration accuracy, and uncertainty estimates. Solar Irradiance of 1 Sun (1000 W/m2) for an LED-based solar simulator is (116 ± 3) klx and (122 ± 1) klx for outdoor sunlight.