NILM applications: Literature review of learning approaches, recent developments and challenges

GF Angelis, C Timplalexis, S Krinidis, D Ioannidis… - Energy and …, 2022 - Elsevier
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …

Construction 4.0 technologies and applications: A systematic literature review of trends and potential areas for development

L Statsenko, A Samaraweera, J Bakhshi… - Construction …, 2023 - emerald.com
Purpose Based on the systematic literature review, this paper aims to propose a framework
of Construction 4.0 (C4. 0) scenarios, identifying Industry 4.0 (I4. 0) enabling technologies …

Predicting residential energy consumption using CNN-LSTM neural networks

TY Kim, SB Cho - Energy, 2019 - Elsevier
The rapid increase in human population and development in technology have sharply
raised power consumption in today's world. Since electricity is consumed simultaneously as …

Predicting household electric power consumption using multi-step time series with convolutional LSTM

L Cascone, S Sadiq, S Ullah, S Mirjalili, HUR Siddiqui… - Big Data Research, 2023 - Elsevier
Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …

Non-invasive driver drowsiness detection system

HUR Siddiqui, AA Saleem, R Brown, B Bademci, E Lee… - Sensors, 2021 - mdpi.com
Drowsiness when in command of a vehicle leads to a decline in cognitive performance that
affects driver behavior, potentially causing accidents. Drowsiness-related road accidents …

A NILM algorithm with enhanced disaggregation scheme under harmonic current vectors

AS Bouhouras, PA Gkaidatzis, E Panagiotou… - Energy and …, 2019 - Elsevier
In the smart home context, one of the features that most users would desire is the knowledge
of the operation of each electrical appliance without the need to install expensive smart …

Respiration based non-invasive approach for emotion recognition using impulse radio ultra wide band radar and machine learning

HUR Siddiqui, HF Shahzad, AA Saleem… - Sensors, 2021 - mdpi.com
Emotion recognition gained increasingly prominent attraction from a multitude of fields
recently due to their wide use in human-computer interaction interface, therapy, and …

Footwear-integrated force sensing resistor sensors: A machine learning approach for categorizing lower limb disorders

HUR Siddiqui, S Nawaz, MN Saeed, AA Saleem… - … Applications of Artificial …, 2024 - Elsevier
Lower limb disorders are a substantial contributor to both disability and lower standards of
life. The prevalent disorders affecting the lower limbs include osteoarthritis of the knee, hip …

Residential electrical load monitoring and modeling–state of the art and future trends for smart homes and grids

X Yuan, P Han, Y Duan, RE Alden… - Electric Power …, 2020 - Taylor & Francis
Building energy consumption accounts for a large fraction of the total global energy usage,
and considerable energy savings are expected to be achieved in this respect through …

Respiration-based COPD detection using UWB radar incorporation with machine learning

HUR Siddiqui, AA Saleem, I Bashir, K Zafar, F Rustam… - Electronics, 2022 - mdpi.com
COPD is a progressive disease that may lead to death if not diagnosed and treated at an
early stage. The examination of vital signs such as respiration rate is a promising approach …