HealCity: usando dados de sinais vitais dos cidadãos e a técnica de elasticidade para gerência de ambientes de saúde no contexto de cidades inteligentes

Abstract

Smart cities can improve the quality of life of citizens by optimizing the utilization of resources. In an IoT-connected environment, people’s health can be constantly monitored, which can help identify medical problems before they become serious. However, overcrowded healthcare environments can lead to long waiting times for patients to receive treatment. The global COVID-19 pandemic has exacerbated this problem. In an increasingly connected environment, such as smart cities, people’s health can be monitored at all times so that situations requiring medical support can be identified in advance. Thus, smart cities would adapt the hospital allocation of healthcare professionals to patient demands based on previously collected data. The literature presents alternatives to address this problem, such as sharing human resources between hospitals, adjustments to work shifts and human resources on-the-fly in order to adjust the capacity to demand. However, there is still a need for a solution that can adjust human resources on-the-fly in multiple healthcare settings, which is the reality of cities. In this context, this work presents HealCity, a smart city-focused model for human resources optimization that can monitor patients’ use of healthcare settings and adapt the allocation of health professionals to meet their needs. HealCity uses vital signs data and prediction techniques to anticipate when the demand for a given environment will exceed its capacity and suggests actions to allocate health professionals accordingly. Additionally, HealCity introduce the concept of Multilevel Human Resources Elasticity in Smart Cities, an extension of the concept of resource elasticity in Cloud computing to manage human resources at different levels of a smart city. An algorithm was also developed to manage future patients in the smart city, automatically identifying the appropriate hospital for a possible future patient. HealCity was evaluated by simulating a smart city composed of four healthcare environments and obtained promising results: compared to medical environment with static professional allocations, the model was able to reduce waiting time for care by up to 87.62%, with an increase in cost of only 9.68%. In this context, it is believed that flexibility in human resources management can be a good alternative to mitigate health problems, which appear to a greater or lesser extent in practically every country in the world.