Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities

V Papastefanopoulos, P Linardatos… - Smart Cities, 2023 - mdpi.com
Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …

Towards Smart Farming: Fog-enabled intelligent irrigation system using deep neural networks

M Cordeiro, C Markert, SS Araújo, NGS Campos… - Future Generation …, 2022 - Elsevier
The most amount of withdrawn freshwater in the world is used for agriculture activities to
extract essential products for human survival. Smart Farming can manage and optimize the …

A multihead LSTM technique for prognostic prediction of soil moisture

P Datta, SA Faroughi - Geoderma, 2023 - Elsevier
Prognostic prediction of soil moisture is a critical step in various fields such as geotechnical
engineering, agriculture, geology, hydrology, and climatology. For example, in agricultural …

Using multimodal remote sensing data to estimate regional-scale soil moisture content: A case study of Beijing, China

M Cheng, B Li, X Jiao, X Huang, H Fan, R Lin… - Agricultural Water …, 2022 - Elsevier
An accurate regional estimate of soil moisture content (SMC) is important for water
management and drought monitoring. Traditional ground measurement methods of SMC are …

[HTML][HTML] Digitalization of Analysis of a Concrete Block Layer Using Machine Learning as a Sustainable Approach

P Narimani, MD Abyaneh, M Golabchi, B Golchin… - Sustainability, 2024 - mdpi.com
The concrete block pavement (CBP) system has a surface layer consisting of concrete block
pavers and joint sand over a bedding sand layer. The non-homogeneous nature of the …

Artificial neural networks and noncontact microwave NDT for evaluation of polypropylene fiber concrete

H Nimer, R Ismail, H Al-Mattarneh, M Khodier… - Asian Journal of Civil …, 2024 - Springer
Polypropylene fibers are extensively incorporated into reinforced concrete to enhance
performance aspects such as crack resistance, flexural and tensile strength, fire resistance …

Machine learning applications in vadose zone hydrology: A review

X Li, JL Nieber, V Kumar - Vadose Zone Journal, 2024 - Wiley Online Library
Abstract Machine learning (ML) has been broadly applied for vadose zone applications in
recent years. This article provides a comprehensive review of such developments. ML …

Water information extraction based on multi-model RF algorithm and Sentinel-2 image data

Z Jiang, Y Wen, G Zhang, X Wu - Sustainability, 2022 - mdpi.com
For the Sentinel-2 multispectral satellite image remote sensing data, due to the rich spatial
information, the traditional water body extraction methods cannot meet the needs of practical …

Estimating soil moisture content in citrus orchards using multi-temporal sentinel-1A data-based LSTM and PSO-LSTM models

Z Wu, N Cui, W Zhang, C Liu, X Jin, D Gong, L Xing… - Journal of …, 2024 - Elsevier
Soil moisture content is a vital variable in agricultural, hydrological, ecological and
climatological processes. However, susceptible to soil type, soil structure, topography …

Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation

LP Sánchez-Fernández, DA Flores-Carrillo… - Mathematics, 2024 - mdpi.com
In this paper, an intelligent weather conditions fuzzy adjustment based on spatial features
(IWeCASF) is developed. It is indispensable for our regional soil moisture estimation …