Core Viewpoint - The research team from Nanjing University of Technology has made significant breakthroughs in distributed filtering, control, and intelligent operation and maintenance theories for swarm intelligence systems, which have been recognized with the Jiangsu Provincial Engineer Society Science and Technology Award for 2025, enhancing the safety and efficiency of intelligent device collaboration [1] Group 1: Communication Innovations - The team developed an "event-triggered filtering" technology that activates data transmission only when critical data changes exceed a set threshold, reducing communication volume and energy consumption by 70%-80%, thus extending the operational duration of mobile platforms like drones [2] Group 2: Control Mechanisms - The introduction of "fault-tolerant control" allows swarm intelligence systems to maintain operation even in the event of equipment failure, employing a closed-loop mechanism for fault detection, estimation, and compensation, enabling systems to perform tasks continuously in urgent scenarios [2] Group 3: Intelligent Operation and Maintenance - The "remaining life prediction uncertainty quantification" technology enhances the accuracy of predicting equipment lifespan from approximately 50% to over 90%, significantly lowering maintenance costs and improving system reliability, providing businesses with more reliable decision-making data [3] Group 4: Industrial Applications - The team has integrated swarm intelligence technology into various industries, including space exploration and chemical safety production, collaborating with organizations to optimize equipment efficiency and support operations for critical applications like aerospace and planetary exploration [4]

Group 1 - The core project by Nanjing University of Technology focuses on distributed filtering, control, and intelligent operation and maintenance theories and applications for group intelligence systems, achieving significant breakthroughs and winning the Jiangsu Provincial Engineer Society Science and Technology Award [1] - The project emphasizes the importance of three core aspects: communication, control, and operation and maintenance, which are essential for the smooth operation of group intelligence systems [1] - The team developed an "event-triggered filtering" technology that reduces communication volume and energy consumption by 70%-80% by only transmitting data when key changes exceed a set threshold, thus extending the operational duration of drones and other mobile platforms [1] Group 2 - The introduction of "fault-tolerant control" into group intelligence systems allows for a closed-loop mechanism of fault detection, estimation, and compensation, ensuring stable flight and task continuity even if one rotor of a quadcopter fails [2] - The team created a technology for quantifying the uncertainty of remaining life predictions, improving the accuracy of predictions from approximately 50% to over 90%, which significantly reduces operational costs and enhances system reliability [2] - The technologies developed have been successfully applied in various fields, including space exploration, civil surveying, new energy transportation, and high-end equipment maintenance, demonstrating a comprehensive capability from laboratory to production line and from ground to space [2]

Core Viewpoint - The research team led by Professor Shi Jiantao from Nanjing University of Technology has made significant breakthroughs in distributed filtering, control, and intelligent operation and maintenance theories for group intelligence systems, addressing challenges such as high power consumption, communication delays, and unexpected failures in large-scale device collaboration [1][2]. Group 1: Key Innovations - The team developed "event-triggered filtering" technology, which reduces communication volume and energy consumption by 70%-80% by only transmitting data when key changes exceed a set threshold, thus extending the operational duration of mobile platforms like drones [2][3]. - The introduction of "fault-tolerant control" allows systems to maintain operation even when a device experiences a failure, enabling capabilities such as "flying with injuries" by redistributing power among remaining motors, which is crucial for time-sensitive applications like reconnaissance and rescue [3][4]. - The "uncertainty quantification of remaining lifespan prediction" technology enhances predictive accuracy from approximately 50% to over 90%, significantly lowering maintenance costs and improving system reliability [3][4]. Group 2: Industry Applications - The research team emphasizes a demand-driven approach, integrating real-world parameters into simulations to ensure that technological advancements meet industry needs, particularly in sectors like aerospace and civil engineering [4][5]. - Collaborations with organizations such as Jiangsu Surveying and Mapping Engineering Institute and Shanghai Huace have led to optimized efficiency in surveying equipment, while technologies have been applied in lithium-ion battery management systems and smart connected vehicles to alleviate traffic congestion [5]. - The team has extended group intelligence technology to process industries, including chemical safety production, by implementing fault diagnosis and fault-tolerant control, thereby injecting new intelligence into traditional industrial upgrades [5].