Intelligent Home Appliance Control Research Articles

Artificial neural network-based home energy management system for smart homes

<p>Energy efficiency is widely recognized as one of the most significant and economical ways to lower greenhouse gas (GHG) emissions. The aims and goals are that smart meters can evaluate and communicate in-depth real-time electricity usage, enable remote real-time monitoring and management of power consumption, and provide consumers with real-time pricing and analyzed usage information. The house energy management controller decides which loads will be powered based on the real home energy demands and the predefined load priorities. Artificial intelligence (AI) is being used increasingly in control applications due to its great effectiveness and efficiency. As a result, in this work, the author designed, simulated, and optimized an artificial neural network-based model simulation framework that simulates a home with a variety of home appliances and optimizes the total energy consumption of the home realistically through intelligent control of home appliances. The MATLAB application was used to model and examine the performance of four common household appliances: the water heater (WH), washing machine (WM), air conditioner (AC), and refrigerator (RG). The result shows a considerable reduction and savings in energy consumption without a decrease in consumer comfort.<strong></strong></p>

Intelligent multi-sensor control system based on innovative technology integration via ZigBee and Wi-Fi networks

Data transmission network integration is one of the most difficult problems to solve in wireless sensor network systems. ZigBee and Wi-Fi belong to different network protocols. If a network system must use both ZigBee and Wi-Fi at the same time to transmit data a considerable challenge is presented. This paper introduces a novel hardware method that integrates ZigBee and Wi-Fi. The proposed method is based on the Arduino wearable module ZigBee and Ethernet concept. This study builds an intelligent home appliance control system using the ZigBee network. This intelligent control system uses an integrated ZigBee and Wi-Fi network architecture in the house. Our study sends the ZigBee sensor messages to a cloud database through the TCP/IP protocol network containing the physical network and wireless network device lines. Control management access is achieved using smart phones. The proposed method is very simple and easy to implement using Arduino circuits. The effectiveness of the proposed method is verified by the simulation and experimental results. The hardware components include the Arduino controller, XBee Series 2 wireless communication module and end device sensors. The Android and Java programming languages are used to write the smart phone and Server recognition programs.

3C intelligent home appliance control system – Example with refrigerator

This study is a creative and initial work focused on designing an intelligently automatic detecting and sensor system for home appliances being smartly interactive with mankind with speech in the living space. Since the tide of automation flowed over the industry, manufacturing business, even the living space of mankind resulting from shifting and highly developing of computer technique such as office-automation (OA), home-automation (HA), and Manufacture-automation (MA) etc. Though automation spread throughout the manufacturing in last decade, there seemed no such equal attention with home appliance. In this paper, the automation developed into the place where we spend most of our time becomes a brand-new thinking. There are so many home appliances in our living space, and how to make them intelligent so as to let our life more safety, convenient, and comfortable will be a challenge to our knowledge. In this study, some technique and skills especially related 3C (computer, communication, content) were developed to make our home appliances intelligent such as radio remote control, sensors invented by researchers, auto-dialing system, and image analysis with CCD (charged-coupled device) image-fetched. Through linking the sub-systems’ function, the main function of the home appliance worked smartly – in this case, we use a refrigerator as the center of all home appliances in a family, the refrigerator could sense the lack of the food, drinks, even irregular shape fruits through all designed sensors and CCD images analysis system, and it also could auto-dial the vendors to deliver the thing those were sensed insufficient. In addition to detect capability, the refrigerator could assign works to other appliance through inter-net or wireless radio remote control system, for example, supposing that we forgot to turn off the gas oven after we had reached far away our home, we could dial cell phone or phone into the refrigerator to generate command code to turn off the fire through remote control module set up both on refrigerator and oven. This design can insure our life saved and convenience.

INTELLIGENT MODELING AND CONTROL OF WASHING MACHINE USING LOCALLY LINEAR NEURO‐FUZZY (LLNF) MODELING AND MODIFIED BRAIN EMOTIONAL LEARNING BASED INTELLIGENT CONTROLLER (BELBIC)

ABSTRACTIntelligent control of home appliances has, in recent years, attracted much theoretical attention, as well as becoming a major factor for industrial and economic success and rapid market penetration. Washing Machines represent an important market. Intelligent control techniques are capable of providing useful means for both easier use and energy and water conservation. In this paper, the authors use two techniques that have successfully been used in other intelligent modeling and control applications. Firstly, the authors use a neuro‐fuzzy locally linear model tree system for data driven modeling of the machine. Secondly, the authors use a neural computing technique, based on a mathematical model of amygdala and the limbic system, for emotional control of the washing machine. The obtained results indicate the applicability of the proposed techniques in this important business sector.