CNN-LSTM Based Deep Learning Application on Jetson Nano: Estimating Electrical Energy Consumption for Future Smart Homes

A Gozuoglu, O Ozgonenel, C Gezegin - Internet of Things, 2024 - Elsevier
Smart home applications have witnessed significant advancements, expanding beyond
lighting control or remote monitoring to more sophisticated functionalities. Our study delves …

Extraction of statistical features for type-2 fuzzy NILM with IoT enabled control in a smart home

S Ghosh, A Chatterjee, D Chatterjee - Expert Systems with Applications, 2023 - Elsevier
Identification and monitoring of residential appliances are important facets for home energy
management and essential for proper functioning of the connected devices. In this paper …

Multi-objective energy management of a smart home in real time environment

A Chatterjee, S Paul, B Ganguly - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In home energy management, the occupants schedule the operating appliances to achieve
lowest optimal energy cost with minimum discomfort. Smart home energy management turns …

Multichannel spatio-temporal feature fusion method for NILM

J Feng, K Li, H Zhang, X Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The main task of noninvasive load monitoring is to disaggregate the power consumption of a
single household appliance from an electricity meter that detects the power consumption of …

Remote appliance load monitoring and identification in a modern residential system with smart meter data

S Ghosh, D Manna, A Chatterjee… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
In this article, an innovative procedure for residential electrical load monitoring applicable to
smart meters is proposed based on a modified decisive multi-objective optimization. In this …

A recent review of NILM framework: Development and challenges

MD Silva, Q Liu, OF Darteh - … and Computing, Intl Conf on Cloud …, 2022 - ieeexplore.ieee.org
Development of sustainable energy management solution is a promising research area with
the energy crisis in the world. Many studies have been conducted to implement an electricity …

An intelligent system for domestic appliance identification using deep dense 1-D convolutional neural network

S Paul, N Upadhyay, A Jain… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Domestic appliance identification is a crucial step for the successful implementation of
demand-side management in the smart grid. Traditionally, load identification is performed …

Analysis of a self-excited induction generator with fuzzy PI controller for supporting domestic loads in a microgrid

A Chatterjee - Journal of Fuzzy Systems and Control, 2023 - ejournal.ptti.web.id
This study provides a technical analysis of integrating a microgrid structure for power
generation with a wind energy conversion system. This study's primary objective is to identify …

[PDF][PDF] Grid-secluded Induction Generator with ANN and Interval Type-2 Fuzzy based Controller for Wind Power Generation with Smart Load Control

A Chatterjee, B Banerjee - Qeios, 2023 - researchgate.net
Three-phase Induction generators are widely used to extract power from wind both in grid-
connected and isolated conditions. This paper proposes an induction generator-based …

A Smart Residential Load Control Technique with Internet of Things and Pattern Recognition Based Load Identification

S Datta, S Bhowmick, S Datta… - 2023 IEEE 3rd …, 2023 - ieeexplore.ieee.org
This paper presents a design of a smart home automation system (HAS) for non-intrusive
load monitoring (NILM) with load identification. The proposed framework aims to develop an …