7results about How to "Improve welfare" patented technology

This utility model discloses a three-dimensional cage device for raising and displaying squirrels and monkeys, including a feeding cage, a first resting platform, a second resting platform, a first passageway, a second passageway, a third passageway, and a feeding passageway. The feeding cage is the main habitat for the animals. The first, second, and third passageways are suspended, allowing the animals to move freely within them. Resting platforms are provided within the passageways for the animals to rest temporarily. The device also includes a feeding passageway for visitors to observe, raise, and feed the animals, thereby increasing interactivity. This design solves the problem of limited space in traditional single-cell cages; it not only increases the explorable three-dimensional space, allowing squirrels / monkeys to run, chase, and climb, satisfying their naturally high activity levels, but also avoids the limitations and monotony of traditional cage-based activity spaces. Furthermore, it addresses the key shortcomings of traditional display methods in terms of interactivity.

This application discloses a digital twin control method for facility poultry farming environments based on deep spatiotemporal data fusion, relating to the field of poultry farming technology. It proposes a spatiotemporal sequence prediction model for environmental parameters using a bidirectional long short-term memory network (VMD-Attention-BiLSTM) that integrates variational mode decomposition and attention mechanisms, effectively overcoming the system's large time lag. A digital twin decision engine based on nonlinear model predictive control is constructed, and the optimal control sequence for energy consumption and environmental quality is solved under multiple constraints by establishing a joint state equation for thermodynamics and gas diffusion. Specifically, for complex winter conditions, a ventilation-heating collaborative game strategy based on real-time heat loss compensation is designed. Adaptive sliding mode control with radial basis function neural network compensation is introduced into the underlying execution unit, significantly enhancing the system's anti-disturbance capability. This achieves precise environmental control under complex conditions, improving poultry welfare and energy efficiency.

The invention relates to the technical field of livestock breeding intellectualization, and discloses an intelligent breeding system and method for full-barn feeding cashmere goats. The method comprises the following steps: collecting position coordinates and attitude information of down producing goats in a breeding house, and collecting environmental parameters of a plurality of position points; identifying a sheep flock subset with a local aggregation situation according to the position coordinates, and synchronously obtaining environmental parameters associated with the geographic position of the subset; deducing an expected behavior evolution trend of the sheep flock subset under the action of the environmental parameters in combination with the attitude information and the associated environmental parameters; judging whether the distribution of the whole cashmere goats needs to be subjected to global intervention or not according to the trend; when it is judged that intervention is needed, the movement guiding priority of each cashmere goat is calculated; and generating a differentiated path guide strategy for each goat based on the priority and executing the strategy to adjust the distribution state of the down producing goats in the shed. According to the invention, active prediction and personalized accurate guidance of sheep flock behaviors are realized, and the intelligent level of breeding management and animal welfare are improved.

An unmanned livestock farming system and method based on air-ground collaboration is proposed. This invention constructs a multi-agent collaborative perception and intervention system in the air and on the ground, relying on an improved artificial potential field method to achieve precise autonomous farming planning. It also innovatively integrates UAV-based active noise reduction technology to specifically eliminate auditory stressors in livestock caused by rotor noise during operations. A comprehensive stress index is calculated by fusing thermal imaging temperature measurement with herd movement entropy values, establishing a real-time stress closed-loop control mechanism. In captivity scenarios, a three-level perception system is constructed using fixed RGB-infrared binocular cameras and a track-based inspection robot to achieve early health warnings and estrus monitoring of individual feeding, rumination, body temperature, and behavioral abnormalities. This invention also introduces reinforcement learning and proximal policy optimization algorithms based on human feedback. Using professional feedback from farm workers as optimization signals, the system performs online fine-tuning and iteration of core parameters in parallel in the background, achieving continuous adaptive evolution of farming and captivity management strategies. Simultaneously, it incorporates a computing power / network degradation mode and a federated learning privacy protection architecture to balance system robustness, data security, and low-stress farming effects. This invention solves the industry problems of traditional unmanned livestock technology, such as large stress interference, poor adaptability, rigid models, and inability to iterate and optimize autonomously. It realizes intelligent unmanned breeding and pen management with high efficiency, low stress, high adaptability, and sustainable optimization.

The invention relates to the technical field of animal health monitoring, and discloses an animal individual health monitoring system based on real-time data. According to the system physiological data acquisition assembly, vital sign original data flow of an animal individual is synchronously obtained through an implantable biosensor and a non-contact optical sensor, and the data flow comprises a cortex temperature change curve, a microcirculation blood flow frequency spectrum and a three-dimensional motion acceleration sequence; the multi-modal fusion analysis component is used for carrying out space-time alignment and feature level fusion processing on the original data stream to generate a comprehensive physiological state map; the health state evaluation component is used for performing multi-scale pattern recognition on the atlas by adopting a deep neural network model and outputting a health risk probability value and a potential pathological region mark; the dynamic self-adaptive compensation component is used for carrying out individualized calibration on the risk probability value according to the animal variety physiological constant database; and the real-time feedback execution component is used for generating a health intervention instruction set based on the pathological region marks.

The invention discloses a precise feeding device, and relates to the technical field of automatic breeding of animal husbandry. The device comprises a biological characteristic acquisition module used for constructing a multi-dimensional biological characteristic model comprising facial texture, body condition three-dimensional point cloud and infrared thermal imaging; the dynamic nutrition reconstruction module comprises a main material bin and a plurality of trace element adding bins, and milligram-level nutrient blending is achieved through a high-precision spiral metering pump; the environment perception feedback assembly is used for monitoring feeding environment parameters in real time and correcting the energy supply model; and a self-cleaning residue prevention mechanism. The technical problems that in the prior art, loss is prone to occurring due to the fact that only single radio frequency identification is relied on, nutritional requirement changes of individuals in the sub-health state cannot be responded in real time, and cross contamination is caused by drug and feed residues are solved. And through a multi-source data fusion algorithm, dynamic precise feeding of one pig with one strategy and one meal with one match is realized, and the feed conversion rate and the group health level are remarkably improved.

A method for slaughtering large yellow croaker, which is completed through temporary cultivation, fish selection, loss of consciousness in saturated CO2 environment at 20 DEG C, bloodletting, removal of viscera and gills, ion water flushing, packaging and cold storage. The method for losing consciousness in saturated CO2 environment is applied to slaughtering, which can effectively reduce the adverse effects of fish muscle activity and ATP degradation in fish meat caused by slaughtering stress on the texture, color and shelf life of fish fillets. Meanwhile, the animal welfare is greatly improved, and it is a valuable slaughtering method which can be popularized.