Results 91 to 100 of about 19,887 (247)

Smart Tree: An Architectural, Greening and ICT Multidisciplinary Approach to Smart Campus Environments. [PDF]

Sensors (Basel), 2021
Fortes S, Hidalgo-Triana N, Sánchez-la-Chica JM, García-Ceballos ML, Cantizani-Estepa J, Pérez-Latorre AV, Baena E, Pineda A, Barrios-Corpa J, García-Marín A.   +9 more
europepmc   +1 more source

Environment Friendly Sustainable End‐Of‐Life Solutions for Plastic Components in Indian Automotive Industries

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Growing concerns about the environmental and social consequences of plastics around the world, manufacturing industries are associated with business are focusing on sustainable end‐of‐life options‐based solutions which aim at increasing the product life cycle.
Sivakumar Kirupanandan, Deepak Mathivathanan, Jayakrishna Kandasamy, Michele Mosca   +3 more
wiley   +1 more source

On exploiting Data Visualization and IoT for Increasing Sustainability and Safety in a Smart Campus. [PDF]

Mob Netw Appl, 2021
Ceccarini C, Mirri S, Salomoni P, Prandi C.   +3 more
europepmc   +1 more source

Cobalt‐Free Single‐Crystal Cathodes for Next‐Generation Lithium‐Ion Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Cobalt‐free single‐crystal cathodes enhance lithium‐ion battery stability by mitigating fracture, degradation, and phase transitions. This review highlights Ni‐rich layered, Li‐Mn‐rich, spinel, and olivine frameworks, synthesis strategies enabling morphology and defect control, and structural tuning via doping and coatings, offering pathways toward ...
Srinivasan Alagar, Rakesh Saroha, Jun Kim, Hyung Do Kim, Jung Sang Cho, Sang Mun Jeong   +5 more
wiley   +1 more source

Smart Sprinkler System on Smart Campus

Sensors and Materials, 2023
Pan, Shin-Hung, Chen, Whai-En, Chen, Wei-Sung, Lin, Hsin-Hung, Chen, Ching-Hui   +4 more
openaire   +1 more source

Magneto‐Electrochemical Effect on La‐Doped GaFeO3 as a Supercapacitor Electrode for Energy Storage

Electron, EarlyView.
The electrochemical performance of La‐doped Gallium Ferrite (La‐doped GaFeO3 ${\text{GaFeO}}_{3}$) synthesizes via a conventional solid‐state reaction method; this has been studied by the application of an external magnetic fields. ABSTRACT The electrochemical performance of La‐doped GaFeO3 ${\text{GaFeO}}_{3}$ synthesizes via a conventional solid ...
Biswajit Sahoo, Anuradha Yadav, Khusboo Agrawal, Piyush R. Das, Chandra Sekhar Rout, Banarji Behera   +5 more
wiley   +1 more source

A video summarization framework based on activity attention modeling using deep features for smart campus surveillance system. [PDF]

PeerJ Comput Sci, 2022
Muhammad W, Ahmed I, Ahmad J, Nawaz M, Alabdulkreem E, Ghadi Y.   +5 more
europepmc   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

Energy Science &Engineering, EarlyView.
A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti, Jamal Dabbagh, Jhila Nasiri Reveshti, Karim Farajeyan Bonab, Farid Hosseini Mansoub   +4 more
wiley   +1 more source

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source