In IoT-based smart healthcare services, the heterogeneity of connected wearable sensing devices open up a wide opportunity to develop various healthcare services. However, it also poses an interoperability challenge since each sensing device and application may have different communication mechanisms. Considering that challenge, web platform can be seen as a promising candidate for providing an interoperability layer as we can abstract various devices as single representation i.e. web resource. In this paper, we propose the design of middleware for enabling efficient web of things access over healthcare wearable devices. The proposed middleware consists of three components: gateway-to-cloud device, messaging service and data access interface. The gateway-to-cloud device has a role to perform low level sensor data collection from various wearable sensing device through bluetooth low energy (BLE) communication protocol. Collected data are then relayed to the cloud IoT platform using a lightweight MQTT messaging protocol. In order to provide device abstraction along with access to the stored data, the system offers two kind of interfaces: the Restful HTTP identified by unique universal resource locator (URL) for batch access and MQTT websocket interface identified by unique topic to accommodate access on sensing data in near real time stream manner.
At the end of December 2019, the virus emerges from Wuhan, China, and resulted in a severe outbreak in many cities in China and expanding globally, including Indonesia. Indonesia is the fourth most populated country globally. As of February 2021, Indonesia in the first rank of positive cases of COVID-19 in Southeast Asia, number 4 in Asia, and number 19 in the world. Our paper aims to provide detailed reporting and analysis of the COVID-19 case overview and forecasting that have hit Indonesia. Our time-series dataset from March 2020 to January 2021. Summary of cases studied included the number of positive cases and deaths due to COVID-19 on a daily or monthly basis. We use time series and forecasting analysis using the Naïve Forecast method. The prediction is daily case prediction for six months starting from February 1, 2021, to June 30, 2021, using active cases daily COVID-19 data in all provinces in Indonesia. The highest monthly average case prediction is in June, which is 35,662 cases. Our COVID-19 prediction study has a mean absolute percentage error (MAPE) score of 15.85%.
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