Abstract
As the world’s population is exploding day by day, the number of patients and hospital capacity is also increasing due to high-demands. This situation leads to engaging more people to monitor the overall situation of a hospital. However, it is quite difficult to observe the cabin room, and the patient thoroughly 24 h. To tackle such a situation, we have propounded a scalable IoT-based system, where a large number of hospital cabin and the patient can be monitored without any hassle. We leverage a mechanism that can handle many clients and their related data and undertake immediate actions based on the situation. For this purpose, we use Raspberry Pi as our main server that is capable of analyzing a large number of hospital cabins’ and patients’ data. Particularly, Raspberry Pi performs analysis based on receiving data that are related to environmental conditions, the patient’s body movement, and pulse rate. The environment can be monitored by observing the amount of \(CO_2\) and the temperature of a cabin room that helps us to track a fire situation and also allows us to realize if a cabin has an overwhelming number of people. Moreover, if a patient faces any issue, we can track that based on the patients’ body movement and pulse rate. If the system discovers any unexpected situation, it immediately raises a buzzer and notifies the administrator.
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Zaman, S., Imteaj, A., Hossen, M.K., Arefin, M.S. (2021). IoT-Enabled Lifelogging Architecture Model to Leverage Healthcare Systems. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2020. Advances in Intelligent Systems and Computing, vol 1324. Springer, Cham. https://doi.org/10.1007/978-3-030-68154-8_85
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