3results about How to "Protect private data" patented technology

This invention provides an AI-powered companion robot control system and method based on mobile communication devices, relating to the field of intelligent robot control technology. It collects multi-dimensional behavioral data of users using mobile communication devices and extracts behavioral feature vectors. Based on the behavioral feature vectors, it matches them with historical behavioral patterns to generate clone commands containing predicted actions and their confidence levels, emotional state values, and their confidence levels. The robot itself can execute the predicted actions based on these clone commands, providing proactive reminders and companionship to the user. Furthermore, by dynamically evaluating the computing power contribution level using the operating status parameters of the mobile communication device, it performs differentiated task scheduling, achieving the coordinated utilization of three levels of computing resources. This protects user privacy data, reduces the hardware cost of the robot itself, and organically unifies the high intelligence of cloud-based large-scale models with low-latency, secure local control, improving resource utilization, saving computing power, and achieving a three-in-one collaborative system.

Embodiments of the present application relate to the field of data security, and provide a face image processing method, related device and storage medium, the method comprising: a business server acquiring a target face image to be processed; inputting the target face image into a target model to obtain a target adversarial sample, wherein the target model is obtained based on unsupervised learning, and the similarity between the target adversarial sample and the target face image is lower than a preset threshold; publishing the target adversarial sample, or updating the target face image to the target adversarial sample. The present scheme can improve the generation efficiency of adversarial samples and protect user privacy data.

The invention relates to the technical field of optimal scheduling of an integrated energy system, and discloses a fully-distributed combined heat and power optimal scheduling method, device and equipment and a medium. In order to solve the problems of linear convergence, low calculation efficiency, dependence on a coordination center and the like of a traditional distributed optimization algorithm in electric heating system scheduling, on the basis of reserving an original electric heating coupling model core architecture, a distributed collaborative interior point conjugate gradient method is introduced as an optimization algorithm, and fully-distributed scheduling with efficient convergence is achieved. According to the method, an electric heating comprehensive energy system optimization model is converted into a convex optimization problem, a correction equation is decoupled, a coefficient matrix is ensured to be symmetrical and positive definite, a distributed conjugate gradient method is adopted for solving, and collaborative optimization of an electric power system and a thermodynamic system can be achieved without a coordination center. Simulation verification shows that the calculation efficiency is improved by more than 90% on the premise of ensuring that the optimization precision is consistent with a centralized algorithm, the privacy of each energy main body can be protected, and the method is suitable for real-time scheduling of electric heating comprehensive systems of different scales.