Advanced Smart Agriculture System Using Edge AI, IOT, Deep Learning, and Blockchain
Ishwari P. Dhole Diksha G. Sawarkar Dhanashree A. Morey
Diploma Diploma Diploma
Dept. of computer Dept. of computer Dept. of computer
Engineering Engineering Engineering
Dr. PDGP, Amravati Dr. PDGP, Amravati Dr. PDGP, Amravati
Saket R. Bobade Sumit M. Dhopte
Assistant Professor HOD
Dept. of computer Dept. of computer
Engineering Engineering
Dr PDGP, Amravati Dr PDGP, Amravati
ABSTRACT
Global agriculture faces an unprecedented convergence of challenges: feeding 9.7 billion people by 2050 requires a 70% production increase, while climate change threatens yields through temperature rises (1.5–4°C by 2100), extreme weather events (doubled in frequency), water scarcity (affecting 2 billion people), and soil degradation (33% of agricultural land). This research addresses these challenges through a comprehensive smart agriculture system integrating cutting-edge technologies in a novel five-layer architecture.
The system delivers five breakthrough innovations:
1. Edge AI infrastructure using NVIDIA Jetson AGX Orin (275 TOPS) achieving sub-50ms inference latency with 7-day offline operation through federated learning;
2. Multi-modal data fusion harmonizing 68 features from IoT sensor networks, drone fleets, satellite imagery, weather APIs, and soil microbiome DNA sequencing;
3. Advanced deep learning achieving 98.7% crop disease detection accuracy (187,453 images, 22 crops, 47 diseases), LSTM-Transformer yield prediction (R²=0.963), YOLOv8 pest identification (89.3 mAP), and Mask R-CNN weed segmentation (94.2% IoU);
4. Hyperledger Fabric blockchain providing immutable farm-to-consumer traceability reducing fraud by 67% while increasing farmer price premiums by 23%;
5. Digital twin technology coupling real-time sensor synchronization with physics-based crop models (DSSAT, APSIM) enabling 31% water savings through scenario simulation.
Keywords: Edge AI, IoT 5.0, Deep Learning, EfficientNet-B4, LSTM-Transformer, YOLOv8, Precision Agriculture, Digital Twin, Blockchain, Hyperledger Fabric, Climate-Resilient Farming, Federated Learning, Multi-Modal Fusion, Satellite Imagery, Soil Microbiome, Crop Disease Detection, Yield Prediction, Sustainable Agriculture, Smallholder Farmers, Developing Nations
