Top AI & IoT-Based Smart Agriculture Project Ideas (IEEE 2026) | Best Engineering Project Maker in Nagpur
Artificial Intelligence, IoT, drones, and deep learning are revolutionizing modern agriculture by improving crop yield, disease detection, irrigation efficiency, and precision farming. This curated list of IEEE 2025 smart agriculture project ideas is ideal for engineering students searching for the best engineering project maker in Nagpur, Wardha, Amravati, Chandrapur, and nearby regions. Each project is explained in simple terms to help students select the right final-year engineering project with real-world impact.
🌱 Smart Agriculture Projects
AI-Enabled Smart Irrigation and Crop Health Monitoring System
This project uses AI and sensors to monitor soil moisture and crop health, enabling automated irrigation and reducing water wastage.
Sustainable Agriculture Through IoT-Based Plant Disease Identification and Crop Management Using Deep Learning
An eco-friendly farming solution that combines IoT sensors and deep learning to detect plant diseases early and improve crop management.
AI-Powered Crop Yield and Health Monitoring System
This system predicts crop yield and monitors plant health using AI models trained on agricultural data.
AI-Powered Precision Agriculture: Enhancing Crop Yields with Smart Analytics
A precision farming project that leverages AI analytics to optimize fertilizer usage, irrigation, and crop productivity.
Smart Crop Health Monitoring and Disease Prediction System Using IoT and Machine Learning
An intelligent agriculture system that collects real-time sensor data and predicts crop diseases using ML algorithms.
Precision Farming Redefined: IoT-Enabled Soil Monitoring and Machine Learning Approaches for Crop Recommendations
This project analyzes soil parameters and recommends suitable crops using IoT devices and machine learning models.
🚁 Drone-Based Agriculture Projects
Mung Bean Crop Health Monitoring and Disease Detection Using Drone-Based Imaging and Deep Learning
Uses drone imagery and deep learning to identify diseases and stress in mung bean crops.
Drone-Sourced Crop Segmentation and Analysis System with U-Net Deep Learning
A drone-based image segmentation system that analyzes crop patterns using the U-Net deep learning model.
Stress Segmentation of Potato Plantation from Aerial Images Using Deep Learning
Detects crop stress in potato plantations using aerial drone images and AI-based segmentation techniques.
Drone-Based Precision Agriculture Technique to Increase Crop Yield Using Machine Learning
A smart farming solution that uses drones and ML to analyze crop conditions and improve yield efficiency.
Federated Learning-Based Cotton Crop Diseases Detection Using Internet of Drones
A privacy-preserving drone network that detects cotton crop diseases using federated learning techniques.
📡 IoT-Based Agriculture Projects
A Hybrid Approach for Smart Crop Health Monitoring Using Deep Learning and IoT
Integrates IoT sensors with deep learning models for accurate crop health monitoring.
Smart Crop Monitoring and Disease Prediction Using IoT Sensors and Deep Learning Models Deployed on Edge-Cloud Architecture
An edge-cloud system that processes agricultural data locally and remotely for faster disease detection.
Remote Sensing and IoT-Based Global Crop Disease Detection and Treatment System
Uses IoT and satellite data to monitor crop diseases and suggest treatments on a global scale.
Real-Time Rice Crop Disease Monitoring: YOLOv11-Powered System with Voice Alerts and Health Scoring
A real-time rice disease detection system that provides voice alerts to farmers using YOLO-based models.
🤖 Deep Learning & Computer Vision Projects
Commercial Plant Leaf Disease Detection Using CNN, DenseNet121, and InceptionV3
Compares multiple deep learning models to identify plant leaf diseases with high accuracy.
Intelligent Pest Detection and Control in Agriculture Using Computer Vision and Deep Learning
Detects pests in crops using computer vision and deep learning to reduce pesticide misuse.
Enhancing Cotton Crop Health Monitoring by Deep Learning Models
Uses AI models to classify cotton plant and leaf diseases automatically.
AI-Driven Deep Learning for Automated Wheat Disease Detection
An automated wheat disease detection system powered by deep learning image classifiers.
Identification of Plant Diseases Using Deep Learning and Image Processing Techniques
A general-purpose AI system that identifies plant diseases using image processing and neural networks.
Deep Learning-Based Tomato Crop Health Monitoring Using ResNet101V2
Uses the ResNet101V2 model to accurately detect tomato plant diseases.
Deep Learning-Based Transfer Learning with MobileNetV2 for Crop Disease Detection
A lightweight deep learning solution suitable for mobile and edge devices in agriculture.
Potato Leaf Disease Detection Using Deep Learning
A deep learning-based approach to identify common potato leaf diseases from images.
Enhancing Crop Health Monitoring: A ResNet50 Approach to Automated Plant Disease Severity Prediction
Predicts disease severity levels using the ResNet50 deep learning architecture.
Ultrasonic Bioacoustics and Deep Learning for Early Plant Disease Prediction
An innovative project that combines sound signals and AI for early disease detection in plants.
📈 Why These Projects Are Ideal for Nagpur Engineering Students
These projects are highly suitable for students looking for:
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Best engineering project maker in Nagpur
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Final-year AI & IoT projects in Nagpur
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IEEE agriculture projects with implementation
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Mini & major projects for CSE, AI, ML, ECE, and IoT students
Nagpur and nearby agricultural regions make these projects especially relevant for real-world deployment and research-based learning.
