Two-Way Economical Smart Device Control and Power Consumption Prediction System

2022 ◽  
pp. 415-429
Author(s):  
P. Anantha Prabha ◽  
N. Arjun ◽  
J. Gogul ◽  
S. Divya Prasanth
Keyword(s):  
Power Consumption ◽  
Smart Device ◽  
Prediction System ◽  
Power Consumption Prediction ◽  
Consumption Prediction

Pre-execution power consumption prediction of computational multithreaded workloads

2014 ◽  
Vol 17 (4) ◽  
pp. 1323-1333 ◽  
Author(s):  
Hamid Fadishei ◽  
Hossein Deldari ◽  
Mahmoud Naghibzadeh
Keyword(s):  
Power Consumption ◽  
Multithreaded Workloads ◽  
Power Consumption Prediction ◽  
Consumption Prediction

scholarly journals Power Consumption prediction of IoT application Protocols Based on Linear Regression

2021 ◽  
Vol 11 (2) ◽  
pp. 0-0
Keyword(s):  
Linear Regression ◽  
Power Consumption ◽  
Smart Grids ◽  
Smart Cities ◽  
Data Communications ◽  
Iot Applications ◽  
Access To Data ◽  
Application Protocols ◽  
Power Consumption Prediction ◽  
Consumption Prediction

The advent of the Internet of Things (IoT) augurs new cutting-edge applications in modern life such as smart cities and smart grids. These applications require protocols more efficient for ensuring the reliability of data communications in the IoT networks. Many works state that IoT cannot meet their demands without application protocols improvement with Artificial Intelligence (AI) as IoT are expected to generate unprecedented traffic giving IoT researchers access to data that can help in studying and analyzing the demands and develop application protocols conceptions to meet the requirement of IoT applications. In literature, several works introduced AI in some layers of the TCP/IP model including wireless communication and routing. In this article, an evaluation of application protocols HTTP, MQTT, DDS, XMPP, AMQP, and CoAP has been presented; and subsequently, the power consumption prediction of MQTT and COAP based on the linear regression model is analyzed, in order to enhance data communications in IoT applications.

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