PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 29, 20240 citations

Achieving Smart Building Operation Sustainability by Utilizing AI Under Environmental Impact

View Full Paper
MNMohamed NaeemMFMohamed Mostafa Fouad

Key Points

Key points are not available for this paper at this time.

Abstract

Smart building is evolving by integrating the best of information and communication technology (ICT), the Internet of Things (IoT), and automation solutions. stability of electric energy is a major threat to its sustainability. For its negligible running cost and emission Smart buildings depend on photovoltaic PV panels for steering their appliances with electricity. However, PV has an unstable conversion rate due to environmental factors which adversely affect its efficiency. In turn, those environmental factors form a threat to smart building sustainability. This paper conducted an empirical investigation to evaluate the influence of environmental conditions on photovoltaic systems. Additionally, by forecasting PV productivity, the paper suggests an artificial intelligent approach for realizing a sustainable smart building. Through a comparison analysis with the prior solution, the simulation results demonstrated the proposed system's effectiveness.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Naeem et al. (2024) studied this question.

synapsesocial.com/papers/68e7708db6db6435876e5e59https://doi.org/10.1109/reepe60449.2024.10479728
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Artificial neural network-based output power prediction of grid-connected semitransparent photovoltaic system2021 · 87 citations
  2. 2Evaluating the causes of cost reduction in photovoltaic modules2018 · 450 citations
  3. 3Mixed-dimensional PdSe 2 /SiNWA heterostructure based photovoltaic detectors for self-driven, broadband photodetection, infrared imaging and humidity sensing2020 · 216 citations
  4. 4A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels2021 · 125 citations
  5. 5ADVANTAGES AND DISADVANTAGES OF RENEWABLE ENERGY SOURCES UTILIZATION2021 · 250 citations