Next Article in Journal
Electrical and Physical Characteristics of WO3/Ag/WO3 Sandwich Structure Fabricated with Magnetic-Control Sputtering Metrology
Next Article in Special Issue
Void Hole Avoidance for Reliable Data Delivery in IoT Enabled Underwater Wireless Sensor Networks
Previous Article in Journal
Multi-Timescale Drowsiness Characterization Based on a Video of a Driver’s Face
Previous Article in Special Issue
IoT Hierarchical Topology Strategy and Intelligentize Evaluation System of Diesel Engine in Complexity Environment
Open AccessArticle

IoT Operating System Based Fuzzy Inference System for Home Energy Management System in Smart Buildings

1
School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
2
COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(9), 2802; https://doi.org/10.3390/s18092802
Received: 2 August 2018 / Revised: 19 August 2018 / Accepted: 20 August 2018 / Published: 25 August 2018
Energy consumption in the residential sector is 25% of all the sectors. The advent of smart appliances and intelligent sensors have increased the realization of home energy management systems. Acquiring balance between energy consumption and user comfort is in the spotlight when the performance of the smart home is evaluated. Appliances of heating, ventilation and air conditioning constitute up to 64% of energy consumption in residential buildings. A number of research works have shown that fuzzy logic system integrated with other techniques is used with the main objective of energy consumption minimization. However, user comfort is often sacrificed in these techniques. In this paper, we have proposed a Fuzzy Inference System (FIS) that uses humidity as an additional input parameter in order to maintain the thermostat set-points according to user comfort. Additionally, we have used indoor room temperature variation as a feedback to proposed FIS in order to get the better energy consumption. As the number of rules increase, the task of defining them in FIS becomes time consuming and eventually increases the chance of manual errors. We have also proposed the automatic rule base generation using the combinatorial method. The proposed techniques are evaluated using Mamdani FIS and Sugeno FIS. The proposed method provides a flexible and energy efficient decision-making system that maintains the user thermal comfort with the help of intelligent sensors. The proposed FIS system requires less memory and low processing power along with the use of sensors, making it possible to be used in the IoT operating system e.g., RIOT. Simulation results validate that the proposed technique reduces energy consumption by 28%. View Full-Text
Keywords: home energy management system; demand-side management; time-of-use; fuzzy logic; user comfort home energy management system; demand-side management; time-of-use; fuzzy logic; user comfort
Show Figures

Figure 1

MDPI and ACS Style

Ain, Q.-U.; Iqbal, S.; Khan, S.A.; Malik, A.W.; Ahmad, I.; Javaid, N. IoT Operating System Based Fuzzy Inference System for Home Energy Management System in Smart Buildings. Sensors 2018, 18, 2802.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop