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http://dspace.univ-tiaret.dz:80/handle/123456789/17038| Titre: | Development of an Integrated IoT and Machine Learning System for the Management of a Photovoltaic-Powered Aquaponic Greenhouse |
| Auteur(s): | KHIAL, Ilyes MEGHEZI, Mohamed |
| Mots-clés: | Smart agriculture aquaponics IoT Raspberry Pi |
| Date de publication: | jui-2025 |
| Editeur: | ibn khaldoun university-Tiaret |
| Résumé: | This project introduces a Smart Aquaponics System that combines aquaculture and hydroponics into a unified smart farming approach, leveraging modern technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), drones, and embedded systems like Raspberry Pi. The system employs sensors and actuators to maintain optimal conditions for both fish and plants, while an AI model based on Convolutional Neural Networks (CNNs) detects diseases in lettuce crops. A custom-built drone supports aerial monitoring by capturing highresolution images to assess plant health. This integrated solution promotes sustainable, automated, and resource-efficient agriculture. |
| URI/URL: | http://dspace.univ-tiaret.dz:80/handle/123456789/17038 |
| Collection(s) : | Master |
Fichier(s) constituant ce document :
| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| TH.M.GE.2025.22.pdf | 5,54 MB | Adobe PDF | Voir/Ouvrir |
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