Notice Board :

Call for Paper
Vol. 16 Issue 2

Submission Start Date:
Feb 01, 2024

Acceptence Notification Start:
Feb 10, 2024

Submission End:
Feb 25, 2024

Final MenuScript Due:
Feb 28, 2024

Publication Date:
Feb 28, 2024
                         Notice Board: Call for PaperVol. 16 Issue 2      Submission Start Date: Feb 01, 2024      Acceptence Notification Start: Feb 10, 2024      Submission End: Feb 25, 2024      Final MenuScript Due: Feb 28, 2024      Publication Date: Feb 28, 2024




Volume XII Issue II

Author Name
Rahul Kumar, Sneha Jain, Bhaskar Singh
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 2
Abstract
This technology will give immediate access to information about the physical world and the objects in it leading to innovative services and increase in efficiency and productivity. The IoT is enabled by the latest developments, smart sensors, communication technologies, and Internet protocols. This paper contains a description of networks. Using IoT systems based on PLC technology. Power line communication is basically meant for carrying not only the electric power but also the data over the conductors and as the application alters so do the need to change the technologies, like the requirement to alter the technology in case of home automation and for internet access and in order to create a sufficient level of separation between them, they are usually differentiated by means of frequency alteration. The substation usually prevents the propagation of signal. Data rates and the distance vary in accordance with power line communication standards. Power line communication has been emanat
PaperID
2020/EUSRM/2/2020/57228

Author Name
Mithilesh Kumar Sharma, Jitendra Sheetlani
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 2
Abstract
In the past decades, Human Activity Recognition (HAR) grabbed considerable research attentions from a wide range of pattern recognition and human–computer interaction researchers due to its prominent applications such as smart home health care. The wealth of information requires efficient classification and analysis methods. Deep learning represents a promising technique for large-scale data analytics. There are various ways of using different sensors for human activity recognition in a smartly controlled environment. Among them, physical human activity recognition through wearable sensors provides valuable information about an individual’s degree of functional ability and lifestyle. There is abundant research that works upon real time processing and causes more power consumption of mobile devices. Mobile phones are resource-limited devices. It is a thought-provoking task to implement and evaluate different recognition systems on mobile devices. This work present the review of literat
PaperID
2022/EUSRM/2/2022/57229