Core Insights - The "Smart Grain Core" monitoring and early warning system developed by Nanjing University of Finance and Economics won the special prize in the creative track at the 2025 National Finance Colleges Innovation and Entrepreneurship Alliance Annual Conference, providing an intelligent solution for food security [1] Group 1: Technology and Innovation - The system integrates multi-modal hardware, intelligent algorithms, and a service platform to achieve real-time perception, intelligent analysis, and proactive management of grain storage environments [1][2] - The self-developed multi-modal smart probe costs about one-fifth of imported equipment while covering more monitoring dimensions and enabling longer online operation [2] - The system employs an improved YOLOv8-seg instance segmentation model for precise identification of typical grain pests, achieving an accuracy rate exceeding 90% [2] Group 2: Application and Impact - The system allows for automatic data collection of temperature, humidity, moisture, carbon dioxide levels, and pest images, significantly enhancing safety and work efficiency compared to traditional manual methods [2] - The intelligent interaction platform translates complex data into understandable risk explanations and generates tiered response strategies, facilitating AI-assisted management for warehouse administrators [3] - The "Smart Grain Core" project has been piloted in major grain storage enterprises such as COFCO and China Grain Reserves Corporation, with plans to further promote the system to more storage companies [3]

Core Insights - The "Smart Grain Core" monitoring and early warning system developed by Nanjing University of Finance and Economics provides a new generation of intelligent solutions for food security in China, winning the special prize in the creative track at the 10th National Financial Colleges Innovation and Entrepreneurship Competition [1] Group 1: System Features - The system integrates multi-modal hardware, intelligent algorithms, and a service platform, transforming grain management from a traditional experience-based approach to a data-driven and controlled method [1] - The core device, a self-developed multi-modal intelligent probe, combines five functions: temperature, humidity, moisture, gas concentration, and pest image recognition, at a cost of approximately one-fifth of imported equipment [1] Group 2: Technical Advancements - The system employs an improved instance segmentation model for pest identification, achieving over 90% accuracy for typical grain pests, and utilizes an LSTM time series prediction model to forecast pest risks for the next five days [2] - The interactive platform based on a large language model translates data into understandable risk explanations and management strategies, facilitating "AI-assisted management" [2] Group 3: Achievements and Applications - The "Smart Grain Core" project has secured five software copyrights, two invention patents, and one high-level paper, demonstrating high technical maturity [2] - The system has been successfully piloted in major grain storage enterprises such as COFCO Group and China Grain Reserves Corporation, showcasing excellent performance [2]

Core Insights - The "Smart Grain Core" monitoring and early warning system, developed by Professor Mao Bo and his student team from Nanjing University of Finance and Economics, provides a new generation of intelligent solutions for food security in China, integrating multi-modal perception, AI recognition, and predictive decision-making [1][3]. Group 1: Technology and Innovation - The system represents a shift from traditional grain management methods, which relied on experience, to a comprehensive approach that combines multi-modal hardware, intelligent algorithms, and service platforms for real-time perception, intelligent analysis, and proactive management of grain storage environments [3][4]. - The core device, a self-developed multi-modal intelligent probe, integrates five functions: temperature, humidity, moisture, gas concentration, and pest image recognition, achieving a cost that is approximately one-fifth of imported equipment while covering more monitoring dimensions [4][6]. Group 2: Performance and Impact - The system has demonstrated significant improvements in grain storage management, allowing for real-time monitoring and early detection of pest issues, which enhances safety and efficiency [4][6]. - The algorithm employs an improved YOLOv8-seg model for high-precision pest identification, achieving over 90% accuracy even in challenging conditions, and utilizes an LSTM time-series prediction model to forecast pest risks, providing a 4-7 day intervention window [6][7]. Group 3: Achievements and Future Plans - The "Smart Grain Core" project has secured five software copyrights, two invention patents, and one high-level paper, and has been successfully piloted in major grain storage enterprises such as COFCO and China Grain Reserves Corporation [7]. - The team is working on building an integrated platform for algorithms and computing power, aiming to expand the intelligent monitoring and management capabilities to more grain storage enterprises, injecting new momentum into the traditional industry [7].