AI-Driven Plant Disease Detection System

The original patent, 'Detection of plant diseases with multi-stage, multi-scale deep learning', demonstrated the effectiveness of deep learning in plant disease classification. However, it had limitations in terms of real-time data integration, secure data sharing, and adaptive decision support. The new invention addresses these limitations by synergistically combining the patented deep learning approach with IoT-based sensor networks, blockchain-based secure data sharing, AI-driven decision support, and new material-based sensors, enabling a more powerful and comprehensive plant disease detection and management system.

The new invention's novelty lies in the synergistic combination of multiple distinct technologies, including IoT, blockchain, AI, and new materials, with the patented deep learning approach. This integration enables real-time data-driven decision making, secure data sharing, and adaptive disease management, which is not obvious from the original patent.

Alternative embodiments of the invention could include integrating the deep learning model with other types of sensors, such as drones or satellite imaging, or using different blockchain protocols for secure data sharing. Variations of the invention could also include applying the system to other types of crops or diseases, or integrating it with other agricultural systems, such as precision irrigation or autonomous farming.

The Synergistic Plant Disease Detection and Management System has significant commercial potential in the agricultural industry, particularly in precision agriculture, crop protection, and sustainable farming practices. The system's ability to minimize environmental impact and optimize treatment strategies aligns with the growing demand for sustainable and environmentally-friendly agricultural practices. The target market includes farmers, researchers, and agricultural companies seeking to improve crop yields and reduce disease-related losses.