{"version":"1","article":{"id":"egypt-ai-solar-irrigation-simulation-2026","slug":"egypt-ai-solar-irrigation-simulation-2026","language":"en","url":"https://haberpaper.com/en/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=en","title":"Solar-powered LSTM irrigation system for Egypt tested in simulation","summary":"A Scientific Reports study built a MATLAB smart-irrigation simulation for Egypt’s New Delta using NASA POWER environmental data. It classified pump states with 96.11% accuracy; water and energy savings are model estimates, not field measurements.","category":"agriculture","region":"world","topics":["ai"],"published_at":"2026-10-13T20:11:52+03:00","modified_at":"2026-10-13T20:11:52+03:00","publication_basis":"publication-record","event_period":"2026-10-12","event_period_basis":"event-or-reference-period","sources":[{"name":"Scientific Reports, A MATLAB-based AI-IoT simulation framework for LSTM-driven smart solar irrigation and renewable energy management","url":"https://www.nature.com/articles/s41598-026-74935-0","checkedAt":"2026-10-13","publishedAt":"2026-10-12"}],"translations":[{"language":"tr","url":"https://haberpaper.com/tr/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=tr"},{"language":"en","url":"https://haberpaper.com/en/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=en"},{"language":"ar","url":"https://haberpaper.com/ar/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=ar"},{"language":"fr","url":"https://haberpaper.com/fr/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=fr"},{"language":"es","url":"https://haberpaper.com/es/news/egypt-ai-solar-irrigation-simulation-2026","api_url":"https://haberpaper.com/api/v1/articles/egypt-ai-solar-irrigation-simulation-2026?lang=es"}],"data_types":[],"data":null,"data_compilations":[],"data_downloads":[],"content":{"paragraphs":["Researchers affiliated with Mansoura National University and Kafrelsheikh University published a study in Scientific Reports on 12 October modelling a smart-irrigation system for Egypt’s New Delta that combines AI, an IoT architecture and solar power in MATLAB. The team used NASA POWER data for environmental inputs. The design links LSTM-based irrigation-pump state classification with photovoltaic generation, battery state-of-charge management, maximum-power-point tracking and adaptive pump-speed control.","The paper reports 96.11% accuracy for classifying pump operating states with the LSTM model. Against an assumed fixed-schedule irrigation baseline, the simulation estimated 28.57% annual water savings; adaptive pump-speed control reduced modeled motor energy use by 74.74%. These are outputs of a MATLAB scenario using real environmental inputs, not savings measured with sensors in a field. The authors identify hardware implementation and long-term real-world trials as future work."],"key_points":[],"sections":[]},"text":"A Scientific Reports study built a MATLAB smart-irrigation simulation for Egypt’s New Delta using NASA POWER environmental data. It classified pump states with 96.11% accuracy; water and energy savings are model estimates, not field measurements.\n\nResearchers affiliated with Mansoura National University and Kafrelsheikh University published a study in Scientific Reports on 12 October modelling a smart-irrigation system for Egypt’s New Delta that combines AI, an IoT architecture and solar power in MATLAB. The team used NASA POWER data for environmental inputs. The design links LSTM-based irrigation-pump state classification with photovoltaic generation, battery state-of-charge management, maximum-power-point tracking and adaptive pump-speed control.\n\nThe paper reports 96.11% accuracy for classifying pump operating states with the LSTM model. Against an assumed fixed-schedule irrigation baseline, the simulation estimated 28.57% annual water savings; adaptive pump-speed control reduced modeled motor energy use by 74.74%. These are outputs of a MATLAB scenario using real environmental inputs, not savings measured with sensors in a field. The authors identify hardware implementation and long-term real-world trials as future work.","corrections":[],"editorial_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"agriculture","url":"https://haberpaper.com/assets/illustrations/agriculture-1536.webp","width":1536,"height":1024,"alt":"Symbolic agricultural landscape with wheat, olive trees and irrigation channels.","language":"en"},"section_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"agriculture","url":"https://haberpaper.com/assets/illustrations/agriculture-1536.webp","width":1536,"height":1024,"alt":"Symbolic agricultural landscape with wheat, olive trees and irrigation channels.","language":"en"}}}