| Titre : | Smart Poultry GreenHouse |
| Auteurs : | Ben becha , Mohamed Bader Eddine, Auteur ; Taha Guenfoud, Auteur ; Laïd Kahloul, Directeur de thèse |
| Type de document : | Monographie imprimée |
| Editeur : | Biskra [Algérie] : Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie, Université Mohamed Khider, 2024 |
| Format : | 1 vol. (94 p.) / ill., couv. ill. en coul / 30 cm |
| Langues: | Français |
| Mots-clés: | Internet of Things (IoT), Artificial intelligence (AI) , Smart Poultry Greenhouse |
| Résumé : |
The agricultural sector is a fundamental pillar of the Algerian economy and a cornerstone of food security, with poultry farming playing a significant role in supplying locally sourced animal protein. However, poultry farming faces various challenge that limit its productivity and sustainable growth. A survey conducted among 28poultry farmers revealed that most farms still rely on traditional practices that requiresignificant manual labor and lack modern technologies, leading to inefficientresource management and slow responses to environmental changes. Notably, 85.7%of farmers showed interest in modern technologies, and 82.1% expressed willingness to implement them in their farms. Based on the survey results, we developed an intelligent care system tailored for poultry farms. This system integrates an AI model designed to predict egg production accurately, enabling proactive decision-making and resource planning. Additionally, the IoT system includes sensors that monitor key environmental parameters such astemperature, humidity, and gas levels, while automating control of essential features like ventilators, pumps, and feeders through motorized mechanisms. These innovations help farmers optimize conditions, improve productivity, and enhance resource management efficiency, contributing to the sustainable growth of poultry farming |
| Sommaire : |
Abstract ix
General Introduction A I Enhancing Poultry Farming through IoT and AI: A Technological Overview 1 I.1 Introduction . . . . . . . 1 I.2 Broiler chicken . . . . . . . . . . . . 2 I.2.1 Basic Life cycle of broiler chickens . . . . . . . . .. . 2 I.2.2 Traditional Poultry Farming . . . . . . . . . 4 I.2.3 Challenges in Traditional Poultry Farming . . . . .. . 5 I.2.4 Smart farming . . . . . . . . . . . 7 I.3 Internet of things . . . . . . . . . . . . 7 I.3.1 IOT Architecture . . . . . . . . . . . . . . . . . 9 I.3.2 IOT Architecture layers . . . . . . . . .. . . . 9 I.3.3 Characteristics of IoT . . . . . . . . . . . . . . 11 I.3.4 Components of IoT in Poultry Farming . . . . . . . . . . . . . 13 I.3.5 Artificial Intelligence (AI) . . . . . . . . . . . . . 16 I.3.6 MachI.3.6.1 Machine learning life cycle: . . . . . . . . . . . . . . 17 I.3.6.2 Machine learning classes: . . . . . . . . . . . . . . . . 20 I.3.6.3 Supervised Machine Learning Categories . . . . . . . 23 I.3.6.4 Classification Algorithms in Machine Learning . . . . 26 I.4 Conclusion . . . . . . . . . . . . . . . . . . . . . .30 II State of the Art .....................32 II.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 II.2 Smart Chicken Poultry Farm Using IoT . . . . . . . . . . . . . . . . . 32 II.3 IoT-Based Smart Poultry Management System . . . . . . . . . . . . . 33 II.4 IoT-Based Smart Agriculture Monitoring System . . . . . . . . . . . 34 II.5 IoT in Greenhouse Agriculture: A Survey . . . . . . . . . . . . . . . . 35 II.6 Intelligent Control Shed Poultry Farm System Using Machine Learning 36 II.7 Discussion . . . . . . . . . . . . . . . . . . 38 II.8 Conclusion . . . . . . . . . . . . . . .. . . . . 39 III Design ....................................40 III.1 Introduction . . . . . . . . .. . . . . 40 III.2 Detailed System Architecture . . . . . . . . . . . . 41 III.3 Diagrams of System . . . . . . . . . . . . . . . . . . 43 III.3.1 Use case Diagrame . . . . . . . . . . .. . . . . . . 45 III.3.2 Sequence diagram . . . . . . . . . . . . . . . . . 46 III.3.3 Class Diagrame . . . . . . . . . . . . . . . . . . . . 47 III.4 The Egg Production Prediction Model . . . . . . . . . . . . . . . 47 III.5 Data Preparation and Feature Selection . . . . . . . . . . . . . 48 III.5.1 Data Splitting . . . . . . . . . . . . . . . 48 ivine Learning . . . . . . . . . . . . . 16 I.3.6.1 Machine learning life cycle: . . . . . . . . . . . . . . 17 I.3.6.2 Machine learning classes: . . . . . . . . . . . . . . . . 20 I.3.6.3 Supervised Machine Learning Categories . . . . . . . 23 I.3.6.4 Classification Algorithms in Machine Learning . . . . 26 I.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 II State of the Art 32 II.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 II.2 Smart Chicken Poultry Farm Using IoT . . . . . . . . . . . . . . . . . 32 II.3 IoT-Based Smart Poultry Management System . . . . . . . . . . . . . 33 II.4 IoT-Based Smart Agriculture Monitoring System . . . . . . . . . . . 34 II.5 IoT in Greenhouse Agriculture: A Survey . . . . . . . . . . . . . . . . 35 II.6 Intelligent Control Shed Poultry Farm System Using Machine Learning 36 II.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 II.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . 39 III Design 40 III.1 Introduction . . . . . . . . . . . . . . . . . . . 40 III.2 Detailed System Architecture . . . . . . . . . . . . 41 III.3 Diagrams of System . . . . . . . . . . . . . . . . . . 43 III.3.1 Use case Diagrame . . . . . . . . . . . . . . .. . 45 III.3.2 Sequence diagram . . . . . . . . . . . . . . . .. . . 46 III.3.3 Class Diagrame . . . . . . . . . . . . . . . . . . . . . 47 III.4 The Egg Production Prediction Model . . . . . . . . . . .. 47 III.5 Data Preparation and Feature Selection . . . . . . . . . . . 48 III.5.1 Data Splitting . . . . . . . . . . . . . . . . . . . .. . 48 III.5.2 Feature Standardization . . . . . . . . . . . . . . . 49 III.5.3 Model Choice: Random Forest Regressor . . . . . . . . . . . . 50 III.5.4 Model Evaluation . . . . . . . . . . . . . . . . .. . 50 III.5.5 User Interaction . . . . . . . . . . . . . 51 III.5.6 Conclusion . . . . . . . . . . .. . . . 51 IV Implementation ...............52 IV.1 Introduction . . . . . . . . . .. . . . . . 52 IV.2 Environment and Software Tools . . . . . . . . . . . . 52 IV.3 Hardware Implementation . . . . . . . . . . . . . . . 55 IV.3.1 Schematic Diagram . . . . . . . . . . . . . . .. 59 IV.3.2 Connection of the Circuit Diagram . . . . . . . . . . . . . . . 59 IV.4 Software Implementation . . . . . . . . . . . . .. . . . 61 IV.4.1 Admin interface . . . . . . . . . . . . . . . . . 61 IV.4.2 User Interface . . . . . . . . . . . . . . . . .. . . 63 IV.4.3 Firebase Interface . . . . . . . . . . . . . 76 IV.4.4 Conclusion . . . . . . . . . . . . .. . . . 78 V General Conclusion ..............79 |
| Type de document : | Mémoire master |
Disponibilité (1)
| Cote | Support | Localisation | Statut |
|---|---|---|---|
| MINFI908 | Mémoire master | bibliothèque sciences exactes | Consultable |
