scholarly journals Memory Management in Smart Home Gateway

10.5772/8406 ◽  
2010 ◽  
Author(s):  
Beizhong Chen ◽  
Ibrahim Kamel ◽  
Ivan Marsic
2021 ◽  
Vol 23 (4) ◽  
pp. 75-80
Author(s):  
Byungseok Kang ◽  
Jaeyeop Jeong ◽  
Hyunseung Choo

Author(s):  
Tianze Li

With the development of science and technology, people's demands for life are getting higher and higher, smart home has become the new theme of the times. Smart home more and more people to become a necessary way to pursue a comfortable life. When the smart home gateway to the family in a variety of home appliances through the home bus technology together, it constitutes a powerful, highly intelligent modern smart home system. This paper mainly introduces the wisdom of home, and its related concepts and core technology, as well as from domestic and foreign market situation and the application of electronic technology in intelligent home.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Kai Guan ◽  
Minggang Shao ◽  
Shuicai Wu

This paper proposed a remote health monitoring system for the elderly based on smart home gateway. The proposed system consists of three parts: the smart clothing, the smart home gateway, and the health care server. The smart clothing collects the elderly’s electrocardiogram (ECG) and motion signals. The home gateway is used for data transmission. The health care server provides services of data storage and user information management; it is constructed on the Windows-Apache-MySQL-PHP (WAMP) platform and is tested on the Ali Cloud platform. To resolve the issues of data overload and network congestion of the home gateway, an ECG compression algorithm is applied. System demonstration shows that the ECG signals and motion signals of the elderly can be monitored. Evaluation of the compression algorithm shows that it has a high compression ratio and low distortion and consumes little time, which is suitable for home gateways. The proposed system has good scalability, and it is simple to operate. It has the potential to provide long-term and continuous home health monitoring services for the elderly.


Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1593
Author(s):  
Zeinab Shahbazi ◽  
Yung-Cheol Byun ◽  
Ho-Young Kwak

The development of information and communication technology in terms of sensor technologies cause the Internet of Things (IoT) step toward smart homes for prevalent sensing and management of resources. The gateway connections contain various IoT devices in smart homes representing the security based on the centralized structure. To address the security purposes in this system, the blockchain framework is considered a smart home gateway to overcome the possible attacks and apply Deep Reinforcement Learning (DRL). The proposed blockchain-based smart home approach carefully evaluated the reliability and security in terms of accessibility, privacy, and integrity. To overcome traditional centralized architecture, blockchain is employed in the data store and exchange blocks. The data integrity inside and outside of the smart home cause the ability of network members to authenticate. The presented network implemented in the Ethereum blockchain, and the measurements are in terms of security, response time, and accuracy. The experimental results show that the proposed solution contains a better outperform than recent existing works. DRL is a learning-based algorithm which has the most effective aspects of the proposed approach to improve the performance of system based on the right values and combining with blockchain in terms of security of smart home based on the smart devices to overcome sharing and hacking the privacy. We have compared our proposed system with the other state-of-the-art and test this system in two types of datasets as NSL-KDD and KDD-CUP-99. DRL with an accuracy of 96.9% performs higher and has a stronger output compared with Artificial Neural Networks with an accuracy of 80.05% in the second stage, which contains 16% differences in terms of improving the accuracy of smart homes.


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