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To date, the protracted pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had widespread ramifications for the economy, politics, public health, etc. Based on the current situation, definitively stopping the spread of the virus is infeasible in many countries. This does not mean that populations should ignore the pandemic; instead, normal life needs to be balanced with disease prevention and control. This paper highlights the use of Internet of Things (IoT) for the prevention and control of coronavirus disease (COVID-19) in enclosed spaces. The proposed booking algorithm is able to control the gathering of crowds in specific regions. K-nearest neighbors (KNN) is utilized for the implementation of a navigation system with a congestion control strategy and global path planning capabilities. Furthermore, a risk assessment model is designed based on a “Sliding Window-Timer” algorithm, providing an infection risk assessment for individuals in potential contact with patients.

Population ageing becomes a perplexing conundrum with social and economic development. Many senior citizens are now empty nesters because the younger generation prefer to stay in metropolises for a better life. Therefore, living in a nursing home is a popular choice for the aged. This objective-oriented paper proposes a sustainable elderly healthcare system for nursing homes. The main work is the design and implementation of a new rapid and interactive assistance service. Based on cost-effective fingerprint indoor-positioning technology, the alert message that a person is at risk will be immediately sent to nearby people before professionals arrive. Warning messages are available when nearing marked areas (e.g., slippery floors). The parallel path-finding algorithm plays a significant role in finding nearby people and alerting people who approach specific areas. Furthermore, this system provides application programming interfaces to connect to health devices, such as smart bracelets, watches, and glasses. In general, the system is designed to ensure the safety of the elderly and improve management efficiency, which corresponds to present smart elderly care proposals from governments.

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This paper proposes a sustainable management and decision-making model for COVID-19 control in schools, which makes improvements to current policies and strategies. It is not a case study of any specific school or country. The term one-size-fits-all has two meanings: being blind to the pandemic, and conducting inflexible and harsh policies. The former strategy leads to more casualties and does potential harm to children. Conversely, under long-lasting strict policies, people feel exhausted. Therefore, some administrators pretend that they are working hard for COVID-19 control, and people pretend to follow pandemic control rules. The proposed model helps to alleviate these problems and improve management efficiency. A customized queue model is introduced to control social gatherings. An indoor–outdoor tracking system is established. Based on tracing data, we can assess people’s infection risk, and allocate medical resources more effectively in case of emergency. We consider both social and technical feasibility. Test results demonstrate the improvements and effectiveness of the model. In conclusion, the model has patched up certain one-size-fits-all strategies to balance pandemic control and normal life.