Healthcare technology is one of the most popular studies nowadays. With the development of healthcare technology, the lifespan of people has successfully extended. However, people in the rural area are still having a hard time to obtain professional healthcare services due to the barrier of distance and lack of doctors. A remote patient monitoring system is one of the best solutions to overcome this issue. This paper proposes an Internet of Things (IoT) based real-time remote patient monitoring system that is able to guarantee the integrity of the real-time electrocardiogram (ECG). Message Queuing Telemetry Transport (MQTT) protocol is used for transmitting the real-time ECG from the proposed system to the webserver. The doctor can access the webserver via smartphone or computer to monitor the realtime or previously recorded ECG data. The proposed system has been tested in both Local Area Network and Wide Area Network environments. The results show that the proposed system has no package loss and packet error in both Local Area Network and Wide Area Network.
In small cell wireless networks, fast and precise vertical handover decision making algorithms are needed to minimize the handover failures and unnecessary handovers, especially in high-speed scenario. In small cell wireless networks such as WLAN and 5G, shorter traveling time is anticipated for a fast-moving user traversing the cell coverage. This results in frequent handovers. It leads to poor user experience and wastage of network resources. To overcome this problem, this paper proposed a new handover decision making algorithm that integrates the traveling distance prediction technique with the bandwidth based handover algorithm. The simulation results show that the proposed algorithm has successfully reduced the number of unnecessary handovers and handover failure in small cell wireless networks.
The evolution of 5G small cell networks has led to the advancement of vertical handover decision-making algorithms. A mobile terminal (MT) tends to move from one place to another and, as the 5G network coverage is small, user network access will change frequently and lead to a high probability of unnecessary handover, which is a waste of network resources and causes degradation of service quality. This paper aims to reduce the number of unnecessary handovers in 5G heterogeneous networks by proposing a handover decision-making algorithm that integrates the dwelling time prediction technique and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The proposed algorithm reduces the number of unnecessary handovers by estimating the connection time to a small cell network using the dwell time prediction technique. The TOPSIS evaluates the network quality and chooses the best network based on user preference. The result shows that the proposed handover algorithm reduces the number of unnecessary handovers to small cell networks in high-speed scenarios. It also saves the network connection cost by up to 27.51% compared with the TOPSIS-based handover algorithm. As for throughput achievement, the proposed algorithm yields an improvement of 5.12%. The proposed algorithm significantly reduces the number of unnecessary handovers in the high-speed scenario while fulfilling user preferences.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.