scholarly journals Real-Time Speech Emotion Analysis for Smart Home Assistants

2021 ◽  
Vol 67 (1) ◽  
pp. 68-76
Author(s):  
Rajdeep Chatterjee ◽  
Saptarshi Mazumdar ◽  
R. Simon Sherratt ◽  
Rohit Halder ◽  
Tanmoy Maitra ◽  
...  
Author(s):  
S. Devi ◽  
Dr. M. Rajalakshmi ◽  
S. Saranya ◽  
B. Jeevanandan ◽  
A. Ramya

2014 ◽  
Vol 513-517 ◽  
pp. 1915-1918
Author(s):  
Heng Wang ◽  
Bi Geng Zheng

As one of the freshest technologies nowadays, the development of Internet of Things is attracting more and more concerns. Internet of Things is able to connect all the items to Internet via information technology such as RFID and Wireless Sensor Network, in order to realize intelligent identification and management. It is supposed in Internet of Things environments, satisfactory services can be provided through any devices or any networks, whenever it is demanded. It makes that not only PC device but also other small devices with intelligence can be connected to the same network. As a result, It is much more convenient for people to obtain real-time information and then to take corresponding actions.


2021 ◽  
Author(s):  
Deepali Joshi ◽  
Anant Dhok ◽  
Anuj Khandelwal ◽  
Sonica Kulkarni ◽  
Srivallabh Mangrulkar
Keyword(s):  

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 194373-194383
Author(s):  
Bomiao Liang ◽  
Weijia Liu ◽  
Leibo Sun ◽  
Zhiyuan He ◽  
Beiping Hou
Keyword(s):  

Author(s):  
Rana M. Amir Latif ◽  
Laiqa-Binte Imran ◽  
Muhammad Farhan ◽  
Mohamed Jaward Bah ◽  
Ghazanfar Ali ◽  
...  

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2562
Author(s):  
Leehter Yao ◽  
Fazida Hanim Hashim ◽  
Chien-Chi Lai

A home energy management system (HEMS) was designed in this paper for a smart home that uses integrated energy resources such as power from the grid, solar power generated from photovoltaic (PV) panels, and power from an energy storage system (ESS). A fuzzy controller is proposed for the HEMS to optimally manage the integrated power of the smart home. The fuzzy controller is designed to control the power rectifier for regulating the AC power in response to the variations in the residential electric load, solar power from PV panels, power of the ESS, and the real-time electricity prices. A self-learning scheme is designed for the proposed fuzzy controller to adapt with short-term and seasonal climatic changes and residential load variations. A parsimonious parameterization scheme for both the antecedent and consequent parts of the fuzzy rule base is utilized so that the self-learning scheme of the fuzzy controller is computationally efficient.


Sign in / Sign up

Export Citation Format

Share Document