An IOT Irrigation System using machine Learning
An IOT Irrigation System using machine Learning
| dc.contributor.author | Belharizi Nesrine | |
| dc.date.accessioned | 2025-11-02T09:55:31Z | |
| dc.date.available | 2025-11-02T09:55:31Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | This master thesis presents a smart irrigation system for small farmer communities (SFCs) designed to optimize water use in agriculture through advanced sensor technologies and machine learning (ML) techniques. The system employs Internet of Things (IoT) components, including low-cost sensors such as the capacitive gravity SEN0308, water tension irrometer watermark, and DHT22. An Arduino Uno collects sensor data and transmits it via LoRa communication to an Arduino Mega 2560, which controls a valve and water flow sensor. ML integration enables real-time analysis and decision-making to prevent over-irrigation by considering soil moisture, temperature, humidity, and historical patterns. The system enhances water efficiency, reduces labor costs, and improves crop yields, thereby contributing to sustainable agricultural practices. | |
| dc.identifier.uri | https://dspace.univ-oran1.dz/handle/123456789/4787 | |
| dc.language.iso | en | |
| dc.subject | Internet of Things, Irrigation, Low-Cost sensors, Machine Learning, Smart Farming | |
| dc.title | An IOT Irrigation System using machine Learning | |
| dc.type | Thesis | |
| grade.Co-rapporteur | CHERIET Amine, MCA, Satellite Développent Center (SDC) | |
| grade.Examinateur | GOURBI Abdelkader, MCA, University of Oran, ISTA | |
| grade.Examinateur | DIF Aicha, MCA, University of Oran, ISTA | |
| grade.Grade | Master | |
| grade.Invite | TIGHZERT Kamel, Director, Agriculture of Oran | |
| grade.Président | KAYIL Fatiha ,Professeur, University of Oran, ISTA | |
| grade.Rapporteur | DAHANE Amine, MCA, University of Oran, ISTA | |
| la.Spécialité | Instrumentation and Metrology | |
| la.cote | MV01 |
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