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dc.contributor.authorKHIAL, Ilyes-
dc.contributor.authorMEGHEZI, Mohamed-
dc.date.accessioned2026-03-05T09:54:15Z-
dc.date.available2026-03-05T09:54:15Z-
dc.date.issued2025-06-
dc.identifier.urihttp://dspace.univ-tiaret.dz:80/handle/123456789/17038-
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.publisheribn khaldoun university-Tiareten_US
dc.subjectSmart agricultureen_US
dc.subjectaquaponicsen_US
dc.subjectIoTen_US
dc.subjectRaspberry Pien_US
dc.titleDevelopment of an Integrated IoT and Machine Learning System for the Management of a Photovoltaic-Powered Aquaponic Greenhouseen_US
dc.typeThesisen_US
Collection(s) :Master

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