Farm intelligent temperature control system based on graphene heating

Abstract

The invention discloses a farm intelligent temperature control system based on graphene heating. The farm intelligent temperature control system comprises a graphene electrothermal film heating unit, an environment sensing network, an intelligent central controller, a partition power control module, a man-machine interaction and remote monitoring terminal and a safety protection module. The graphene electrothermal film heating units are laid in designated areas of the farm ground in a partitioned mode and serve as main heat sources of the system. And the environment sensing network is used for acquiring environment parameters and animal related information in the breeding farm and transmitting the acquired data to the intelligent central controller. According to the invention, the environment data is acquired through the distributed temperature sensor array (covering different heights and functional areas of the breeding house); and by combining an artificial intelligence algorithm (fuzzy control, PID optimization and the like) of the intelligent central controller, the temperature of the ground layer and each functional area can be highly uniform and stable, and the problems that a traditional temperature control system is large in temperature fluctuation and obvious in area temperature difference are solved.

Description

Technical Field

[0001] This invention belongs to the field of animal husbandry technology, and in particular relates to an intelligent temperature control system for livestock farms based on graphene heating. Background Technology

[0002] In the field of livestock breeding equipment technology, especially in the area of ​​floor heating and temperature control for farms (such as poultry houses, pig houses, and nursery pens), existing technologies have developed into several common solutions. Currently, farms mainly use equipment such as hot air furnaces, radiators, and infrared lamps for environmental heating. Hot air furnaces raise the temperature inside the shed by heating and circulating air, radiators rely on hot water or steam for heat dissipation, and infrared lamps heat localized areas through radiation. These three technologies are widely used in small and medium-sized farms. At the same time, common floor heating technologies such as water-based heating and cable-based heating are also gradually being used for floor heating in farms. Water-based heating transfers heat through the circulation of hot water in pipes, while cable-based heating uses electrically powered cables to generate heat. Existing temperature control systems are mostly equipped with basic controllers, which can achieve basic monitoring of temperature and humidity inside the shed and control the start and stop of heating equipment according to preset thresholds. Some systems also support simple manual parameter setting, providing a basic guarantee for temperature regulation in farms.

[0003] While existing technologies can meet the basic heating needs of farms, they have significant shortcomings compared to the beneficial effects of this system: In terms of temperature control, existing equipment struggles to achieve uniform and stable floor temperatures and cannot precisely control temperatures in different functional areas such as brooding and activity areas, or at different growth stages of animals; regarding energy consumption, traditional hot air furnaces and radiators have low heat conversion efficiency, and cable underfloor heating and water heating involve ineffective energy consumption, with the unified heating mode for the entire farm further exacerbating energy waste; in terms of response speed, water heating and cable underfloor heating have high thermal inertia, and hot air furnaces heat up slowly, making rapid repairs difficult. Positive temperature deviation; weak intelligent management capabilities, lacking remote monitoring and data recording and analysis functions, unable to automatically adapt to the temperature control needs of different aquaculture scenarios, relying on frequent manual inspections and adjustments; insufficient safety protection, water heating is prone to leakage, cable floor heating is prone to ground cracking, and some systems lack fault warning mechanisms; limited environmental improvement effect, hot air furnaces and infrared lamps are prone to causing dry air and suspended dust, and lack linkage control of harmful gases; large limitations in scenario adaptability, making it difficult to meet the differentiated needs of constant temperature in aquaculture, zoned temperature control in special aquaculture, and clean heating in cold northern pastures. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an intelligent temperature control system for aquaculture farms based on graphene heating, which solves the problems of temperature difference, high energy consumption, low intelligence, weak safety and narrow compatibility in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A smart temperature control system for aquaculture farms based on graphene heating includes a graphene electric heating film heating unit, an environmental sensing network, an intelligent central controller, a zoned power control module, a human-machine interaction and remote monitoring terminal, and a safety protection module. The graphene electrothermal film heating units are laid in designated areas on the ground of the farm, serving as the main heat source for the system. The environmental sensing network is used to collect environmental parameters and animal-related information within the farm and transmit the collected data to the intelligent central controller. The intelligent central controller receives and processes the data transmitted by the environmental sensing network, calculates the heating power required for each area by combining preset breeding parameters and artificial intelligence algorithms, sends the zone power command to the zone power control module, and identifies abnormal system conditions. The partition power control module corresponds to the partitioned laying of the graphene electric heating film heating unit, receives partition power instructions from the intelligent central controller, and independently adjusts the power of the graphene electric heating film in different areas. The human-computer interaction and remote monitoring terminal is used for parameter setting, status display, alarm confirmation and remote monitoring. The security protection module is used to implement multiple security protections for the system.

[0006] Preferably, the environmental sensing network includes a temperature sensor array and a humidity sensor, and may also be equipped with an ammonia concentration sensor and an animal behavior monitoring unit; The temperature sensor array is distributed throughout the breeding house, including different heights and functional areas such as the near-ground animal activity layer. The animal behavior monitoring unit uses infrared thermal imaging equipment or sound analysis equipment to indirectly sense the animal's thermal comfort. The output of the animal behavior monitoring unit is electrically connected to the intelligent central controller, and the animal behavior data it collects is transmitted to the intelligent central controller for use by the artificial intelligence algorithm module. The output of the ammonia concentration sensor is electrically connected to the intelligent central controller, and the ammonia concentration data it collects is transmitted to the intelligent central controller to trigger air quality linkage control.

[0007] Preferably, the intelligent central controller has a built-in or connected breeding management database, which stores the optimal temperature curves, humidity ranges and ammonia thresholds for different livestock species and different growth stages. The intelligent central controller also includes an artificial intelligence algorithm module, which comprises at least one of fuzzy control algorithm, PID optimization algorithm, and machine learning model, and is used for: Based on current environmental parameters, target settings, and animal behavior feedback, the required heating power for each functional area is dynamically calculated. The target settings are obtained from the breeding management database or manually entered. Predict temperature change trends and adjust power output in advance; It can identify abnormal conditions such as sudden temperature drops, sensor malfunctions, and excessive ammonia levels.

[0008] Preferably, the partitioned power control module includes a multi-channel thyristor voltage regulator or a solid-state relay, which can realize stepless or graded power regulation of the graphene electrothermal film in different functional areas through voltage regulation or duty cycle control.

[0009] Preferably, the human-computer interaction and remote monitoring terminal includes a local touch screen or control panel and a remote monitoring platform; The local touchscreen or control panel is used for parameter setting, status display, and alarm confirmation. The remote monitoring platform is a mobile APP or cloud platform, used to realize remote monitoring, parameter setting, alarm push, and data recording and analysis.

[0010] Preferably, the safety protection module includes an overheat protection unit, a leakage protection unit, a short circuit protection unit, and a communication fault protection unit; The overheat protection unit employs a dual protection method of temperature fuse and software over-temperature limit; When communication is interrupted, the communication fault protection unit automatically puts the system into a default safe state, which is to cut off the power supply to the graphene electric heating film or maintain a minimum heating power not lower than the safety threshold for the corresponding livestock growth stage.

[0011] Preferably, the working process of this system includes the following steps: S1: System initialization, setting the species and growth stage of the aquaculture, or directly setting the target temperature curve; S2: The environmental sensing network collects environmental parameters such as temperature, humidity, and ammonia concentration, as well as animal behavior information in real time, and uploads them to the intelligent central controller. S3: The intelligent central controller combines preset targets, real-time data, and artificial intelligence algorithms to calculate the optimal power required by each heat-generating area. S4: The zone power control module adjusts the power supply of the graphene electrothermal film in the corresponding functional area according to the instruction. S5: The system continuously executes S2 to S4 in a loop to maintain the environment of each functional area within the set target range; S6: When the intelligent central controller detects an abnormal situation, it triggers an alarm and notifies the management personnel through human-machine interaction and remote monitoring terminal.

[0012] Preferably, the abnormal conditions described in step S6 include sudden temperature drop, sensor failure, excessive ammonia concentration, and relay failure.

[0013] Preferably, the graphene electric heating film heating unit is waterproof and encapsulated, making it suitable for constant temperature aquaculture ponds, and can achieve precise control of water temperature within ±0.5℃.

[0014] Preferably, when the ammonia concentration sensor detects that the ammonia concentration exceeds the ammonia threshold in the aquaculture management database, the intelligent central controller will activate the aquaculture farm's ventilation equipment to reduce the ammonia concentration in the shed and improve air quality.

[0015] The technical effects and advantages of the intelligent temperature control system for livestock farms based on graphene heating, as described in this invention: 1. This invention collects environmental data through a distributed temperature sensor array (covering different heights and functional areas of the breeding shed), and combines it with the artificial intelligence algorithms (fuzzy control, PID optimization, etc.) of the intelligent central controller to achieve highly uniform and stable temperature in the ground layer and each functional area, avoiding the problems of large temperature fluctuations and significant regional temperature differences in traditional temperature control systems; at the same time, relying on the independent adjustment of the graphene electric heating film by the zoned power control module, it can provide suitable temperatures for different functional areas (such as brooding area, activity area, rest area) as needed, effectively meeting the differentiated temperature control needs of different livestock species and different growth stages, and reducing ineffective temperature control consumption.

[0016] 2. This invention uses a graphene electrothermal film, which has high electrothermal conversion efficiency and avoids the energy loss of traditional heating equipment (hot air furnace, water heating); combined with the dynamic power calculation and zoned on-demand heating design of the intelligent central controller, it can accurately match the actual temperature control needs of each area, eliminate the energy waste caused by uniform heating of the whole shed, and significantly reduce the daily power consumption and operating costs of the temperature control link of the farm, which is superior to the high energy consumption of traditional temperature control systems.

[0017] 3. The graphene electric heating film of this invention has low thermal inertia and fast heating and cooling speed. Combined with the temperature trend prediction and advance adjustment function of the intelligent central controller, it can quickly respond to changes in ambient temperature and correct temperature control deviations in a timely manner. Compared with the slow response of traditional heating equipment (such as hot air furnaces and cable floor heating), it can effectively avoid cold stress and heat stress caused by sudden temperature changes in livestock and poultry, and ensure the stability of the physiological state of livestock and poultry.

[0018] 4. This invention uses ground heating to reduce air convection, thereby reducing the amount of suspended dust in the shed and improving the respiratory environment for livestock and poultry. If an ammonia concentration sensor is installed, the intelligent central controller can link the ventilation equipment when the ammonia concentration exceeds the limit, so as to reduce the concentration of harmful gases in the shed in time and solve the problem of poor air quality caused by unreasonable heating methods or lack of gas linkage control in traditional farms.

[0019] 5. This invention relies on a human-computer interaction and remote monitoring terminal (local touch screen + remote APP / cloud platform). Managers can view the temperature control status of each area in real time, modify target parameters, and receive abnormal alarm push notifications (such as temperature exceeding the standard or sensor failure), eliminating the need for frequent manual inspections. At the same time, the system can automatically store temperature control data and support analysis. Combined with the aquaculture management database, it can automatically adapt to the temperature control curves of different growth stages, significantly reducing manual operation and maintenance costs, improving management efficiency, and avoiding the drawbacks of traditional temperature control systems that rely on manual operation and are cumbersome to manage.

[0020] 6. The safety protection module of this invention integrates overheat protection (temperature fuse + software over-temperature limit), leakage protection, short circuit protection and communication failure protection (triggers default safety state), which can effectively cope with the risk of equipment failure in harsh environments such as high temperature and humidity and electromagnetic interference in farms; the graphene electric heating film has good waterproof and corrosion resistance after encapsulation treatment. Compared with the problems of easy leakage of traditional water heating and easy cracking of cable floor heating, the equipment has better stability and service life and is suitable for complex use scenarios in farms.

[0021] 7. This invention achieves precise water temperature control by adapting to constant temperature pools for aquaculture through waterproof encapsulation; the zoned temperature control design can meet the multi-zone temperature control needs of special aquaculture (such as snake egg-laying areas and activity areas); the low-temperature resistant graphene electric heating film and low energy consumption characteristics can also be adapted to the clean heating needs of "coal-to-electricity" conversion in cold northern pastures, solving the problem of limited application scenarios of traditional temperature control systems. Attached Figure Description

[0022] Figure 1 This is a simplified flowchart of an intelligent temperature control system for livestock farms based on graphene heating, as proposed in this invention. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0025] Example 1 refer to Figure 1 This paper presents a smart temperature control system for livestock farms based on graphene heating, suitable for piglet nurseries. The specific implementation details include: Scenario requirements: Piglets aged 1-28 days are sensitive to temperature. During the brooding period, the ground temperature needs to be maintained at 33-35℃ (1-7 days), 30-32℃ (8-14 days), and 28-30℃ (15-28 days). Traditional warm air blowers can easily cause a ground temperature difference of more than ±3℃, which can cause cold stress or dehydration in piglets. It is necessary to solve the problems of precise and stable temperature, zoned adaptation to age requirements, and low energy consumption.

[0026] System Configuration: Graphene heating film heating unit: 0.3mm thick polyimide-encapsulated graphene heating film is used, and it is laid in sections of 15 square meters for the piglet feeding area, 20 square meters for the rest area, and 10 square meters for the activity area. The total power is 3kW, and each area is independently wired to the section power control module.

[0027] Environmental sensing network: a total of 6 DS18B20 temperature sensors, 2 in the feeding area (1 at 5cm and 1 at 30cm above the ground), 2 in the rest area and 2 in the activity area, distributed in a distributed manner; 1 SHT30 humidity sensor, installed in the middle of the house at a height of 1.5m; 1 MQ137 ammonia concentration sensor, installed 0.8m above the rest area.

[0028] Intelligent central controller: It adopts an STM32H743 microprocessor, with a built-in breeding management database (pre-stored target temperature curves, humidity range of 45%-65%, and ammonia threshold of ≤20ppm for piglets aged 1-28 days), and integrates a fuzzy PID algorithm module.

[0029] Zoned power control module: includes 3 thyristor voltage regulators (model BT136), corresponding to 3 functional zones, supporting stepless voltage adjustment from 0-220V.

[0030] Human-computer interaction and remote monitoring terminal: Locally configured with a 7-inch touch screen (displaying real-time temperature and power output of each area), and remotely via the aquaculture temperature control cloud platform APP (supporting temperature curve viewing, parameter modification, and alarm push notifications).

[0031] Safety protection module: series 10A thermal fuse (overheating threshold 60℃), equipped with leakage protection switch (operating current ≤30mA), automatically cuts off power supply to the heating film in case of communication failure (default safe state).

[0032] Work process: S1: System initialization. Select the piglet nursery mode via the touchscreen and automatically load the target temperature curve for piglets aged 1-28 days. S2: The environmental sensing network collects data every 30 seconds, transmitting temperature, humidity, and ammonia concentration data to the intelligent central controller; S3: The controller combines real-time data (such as the real-time temperature of the 1-day-old nursing area being 32℃, which is lower than the target temperature of 33℃) with a fuzzy PID algorithm to calculate that the power of the nursing area needs to be increased to 800W (original power 600W), while the rest area and activity area are maintained at 600W and 400W respectively. S4: The zone power control module receives the instruction and adjusts the output voltage of the SCR in the nursing zone to 180V, increasing the power to 800W; S5: Continuous cycle monitoring. When piglets grow to 8 days old, the controller automatically lowers the target temperature of the nursing area to 31°C and simultaneously reduces the power to 700W. S6: If the ammonia concentration is detected at 22ppm (exceeding the threshold of 20ppm), the controller will trigger a local audible and visual alarm, and simultaneously push an ammonia exceedance notification through the APP, and activate the ventilation fan in the dormitory (to reduce the ammonia concentration to 18ppm and then turn it off).

[0033] Technical effects: The ground temperature difference is controlled within ±0.5℃, reducing the mortality rate of piglets by 15% compared to traditional air heaters, and the average daily power consumption is 0.25 kWh / ㎡ (compared to 0.8 kWh / ㎡ for traditional air heaters), achieving the design goals of precise temperature control and energy efficiency.

[0034] Example 2 A graphene-based intelligent temperature control system for aquaculture farms is provided, suitable for intelligent temperature control systems in constant temperature ponds for aquaculture. Specific implementation details include: Scenario requirements: Freshwater fish fry (bass fry from a certain area) require a water temperature maintained at 28±0.5℃ for cultivation. Traditional coal-fired boilers have a temperature control accuracy of only ±2℃, which can easily lead to metabolic disorders in the fry. It is necessary to solve the problems of precise underwater temperature control, waterproofing and corrosion resistance, and low energy consumption.

[0035] System Configuration: Graphene electric heating film heating unit: It adopts epoxy resin full-wrap waterproof encapsulation (waterproof rating IP68), the electric heating film size is 1m×2m, a total of 5 pieces, which are laid flat on the bottom of a 10m×5m×1.5m constant temperature pool (each piece corresponds to a 10㎡ area), with a total power of 5kW.

[0036] Environmental sensing network: 3 underwater temperature sensors (DS18B20 waterproof type) are installed in the middle and at both ends of the pool bottom (10cm from the bottom of the pool), and 1 water surface humidity sensor (to monitor water vapor on the pool surface).

[0037] Intelligent central controller: Built-in aquatic seedling database (target water temperature of perch fry in a certain area is 28℃, fluctuation threshold ±0.5℃), integrated temperature prediction algorithm (adjust power in advance based on the temperature change trend of the previous hour).

[0038] Other components: The zoned power control module includes 5 solid-state relays (model SSR-25DA), the remote APP supports exporting historical water temperature data, and the safety protection module adds water level monitoring (power is cut off when the water level is below 1m).

[0039] Work process: S1: Select a bass fry breeding mode in a certain area, and set the target water temperature to 28℃; S2: The underwater sensor collects water temperature data once every minute and transmits the data to the controller; S3: If the water temperature in the middle of the pool is 27.3℃ (0.7℃ lower than the target), the controller predicts that the water temperature will drop to 27.1℃ in 10 minutes, and calculates that 3 electric heating films (each with a power of 1000W) need to be turned on. S4: The zone power control module connects 3 solid-state relays, and the electric heating film in 3 areas at the bottom of the pool starts. After 15 minutes, the water temperature rises to 27.9℃, and the controller reduces the power to 800W / piece. S5: Continuous circulation keeps the water temperature stable at 27.8-28.2℃ (±0.4℃), meeting the aquaculture's need for precise temperature control of ±0.5℃.

[0040] Technical effects: The survival rate of fish fry is 20% higher than that of traditional boilers, and the daily power consumption is 0.3 kWh / ㎡ (compared to 0.9 kWh / ㎡ for traditional boilers). The electric heating film is waterproof and leak-proof, making it perfectly suited for underwater aquaculture environments.

[0041] Example 3 A graphene-based intelligent temperature control system for livestock farms is provided, suitable for specialized snake farming. Specific implementation details include: Scenario requirements: Cobra farming requires dual-zone temperature control: 35°C for the egg-laying area and 28°C for the activity area. Traditional infrared lamps cannot achieve precise zone adjustment, so it is necessary to solve the problems of independent temperature control in multiple areas and the linkage of animal behavior, and to find a solution that addresses the pain points of special breeding environments.

[0042] System Configuration: Graphene electric heating film heating unit: 2 pieces of 1m×1m electric heating film (total power 1kW) are laid in the 5 square meter egg-laying area, and 4 pieces of 1m×1.5m electric heating film (total power 2.4kW) are laid in the 15 square meter activity area, with independent wiring for each zone.

[0043] Environmental sensing network: 2 temperature sensors each in the egg-laying area and the activity area, 1 infrared thermal imager (installed on the roof of the enclosure to monitor snake behavior), and an ammonia-free sensor (to address the issue of excessive ammonia levels in snake farming and meet the needs of the scenario).

[0044] Intelligent central controller: Built-in snake breeding database (egg-laying area 35℃, activity area 28℃), integrated machine learning algorithm (adjusting temperature based on snake huddling behavior monitored by infrared thermal imager - if huddling occurs, the temperature is determined to be too low and power needs to be increased).

[0045] Zoned power control module: Includes 2-channel thyristor voltage regulators, supporting stepless adjustment of 0-500W in the spawning zone and 0-1200W in the active zone.

[0046] Work process: S1: Select the cobra breeding mode and set the target temperatures as follows: 35℃ for the egg-laying area and 28℃ for the activity area. S2: The infrared thermal imager detected that snakes were clustered together in the egg-laying area (indicating insufficient temperature), and the synchronous temperature sensor showed 34℃ (1℃ lower than the target). S3: The controller uses machine learning algorithms to calculate that the power in the spawning area needs to be increased to 450W (originally 300W), while the active area should be maintained at 800W; S4: The zone power control module adjusts the output of the thyristor in the spawning zone, and the power is increased to 450W. After 10 minutes, the snake swarm disperses, the temperature rises to 35℃, and the power is reduced back to 350W. S5: Continuous circulation, with dual-zone temperatures stabilized at the target value ±0.5℃, meeting the needs of precise temperature control in special aquaculture zones.

[0047] Technical effects: The hatching rate of snake eggs has increased by 12%, eliminating the need for manual inspection and adjustment, and achieving "behavior linkage - automatic temperature control".

[0048] Example 4 A smart temperature control system for livestock farms based on graphene heating is provided, suitable for intelligent temperature control systems in beef cattle sheds in cold northern pastures. Specific implementation details include: Scenario requirements: In northern winters (-20℃ to -5℃), cattle sheds need to maintain a ground temperature of 15±2℃. Traditional electric heaters consume an average of 0.8 kWh / m² per day. It is necessary to solve the problems of rapid heating in low-temperature environments, energy saving, and adapting to the "coal-to-electricity" policy in northern regions, and to provide solutions that address the pain points of cold-weather pastures in northern regions.

[0049] System Configuration: Graphene electric heating film heating unit: Low-temperature resistant electric heating film (operating temperature -30℃ to 80℃) is selected and laid in sections of 30 square meters for the beef cattle feeding area and 50 square meters for the resting area, with a total power of 8kW.

[0050] Environmental sensing network: 6 temperature sensors (2 in the feeding area and 4 in the resting area, 10cm above the ground) and 1 ammonia concentration sensor (1m above the resting area).

[0051] Intelligent central controller: Built-in database for winter heating of beef cattle (ground temperature 15℃, ammonia threshold ≤30ppm), integrated PID optimization algorithm (improves power response speed in low temperature environment).

[0052] Safety protection module: An outdoor temperature sensor is added. When the outdoor temperature is below -25℃, the overheat threshold is automatically raised to 70℃ (to avoid false triggering of protection). In case of communication failure, the minimum power is maintained at 3kW (to prevent beef cattle from freezing).

[0053] Work process: S1: Start the heating mode for beef cattle sheds in winter, with a target ground temperature of 15℃; S2: Outdoor temperature -22℃, real-time temperature in the pen area is 13℃ (2℃ lower than the target). The controller calculates the required power for the pen area using a PID algorithm: 6000W (4000W for the feeding area). S3: The zone power control module adjusts the voltage of the sleeping area to 200V, and the power increases to 6000W. After 15 minutes, the temperature rises to 15℃, and the power drops to 5000W. S4: If communication is interrupted (e.g., 4G signal is lost), the system will automatically enter the default safe state, maintaining 3000W in the pen area and 2000W in the feeding area (ground temperature 12℃, meeting the basic needs of beef cattle). S5: When the ammonia concentration reaches 32ppm, the skylight will be opened for ventilation, and the power of the sleeping area will be increased to 5500W (to offset the ventilation and cooling).

[0054] Technical effects: The average daily power consumption is 0.22 kWh / m² (compared to 0.8 kWh / m² for traditional electric heaters), which complies with the "coal-to-electricity" policy in northern China. In low-temperature environments, the heating speed is twice as fast as traditional equipment.

[0055] Example 5 A smart temperature control system for livestock farms based on graphene heating is provided, suitable for intelligent temperature control systems in chick brooding houses. Specific implementation details include: Scenario requirements: For chicks aged 1-42 days, the target temperature needs to be gradually reduced from 35℃ to 24℃. Traditional hot air furnaces require manual temperature adjustment every day. It is necessary to solve the problems of automatic temperature curve adaptation and remote management, and to find a solution that addresses the pain points of livestock and poultry nurseries.

[0056] System Configuration: Graphene electric heating film heating unit: It is laid in sections of 40 square meters for the chick brooding cage area and 10 square meters for the aisle area, with a total power of 5kW. The electric heating film in the brooding cage area covers the bottom of the cage (directly heating the chick activity layer).

[0057] Environmental sensing network: 4 temperature sensors in the brooding cage area (5cm from the bottom of the cage), 1 temperature sensor in the aisle area, and 1 humidity sensor (monitoring humidity in the house from 40% to 60%).

[0058] Human-computer interaction and remote monitoring terminal: The local touch screen supports the selection of chick age (1-42 days), and the remote APP supports one-click modification of target temperature and export of historical temperature reports (generating energy consumption analysis once a week).

[0059] Intelligent central controller: Built-in chick brooding temperature curve (35℃ at 1 day old, decreasing by 3℃ every 7 days old, 24℃ at 42 days old), automatically adjusting the target value according to age.

[0060] Work process: S1: Select the chicks at 1 day old via remote APP, and the system will automatically load the target temperature of 35℃; S2: The temperature of the brooding cage area is collected every 20 seconds, and the real-time data (34.2℃) is transmitted to the controller; S3: The controller calculates that the power in the brooding cage area needs to be increased to 4000W (1000W in the aisle area), and the zone power control module executes the instruction; S4: When the chicks grow to 7 days old, the controller automatically lowers the target temperature to 32℃ and simultaneously reduces the power of the brooding cage area to 3500W; S5: If the administrator adjusts the target temperature for 10-day-old chicks from 30℃ to 31℃ via the APP (because the chicks are growing weakly), the controller will update the parameters in real time and adjust the power to 3600W.

[0061] Technical effects: No need for daily manual temperature adjustments, remote management efficiency is improved by 80%, and chick uniformity is improved by 10% compared to traditional hot air furnaces.

[0062] Comparative Example 1 This comparative example provides a traditional farm temperature control system, including the following: System Configuration: It uses a hot air furnace with an 8-bit microcontroller controller. The hot air furnace has a power of 15kW. The controller only supports temperature and humidity monitoring (no ammonia or animal behavior monitoring), no zone control (the whole shed is heated uniformly), no remote monitoring (only local display), and safety protection only includes a leakage circuit breaker.

[0063] Work process: The temperature range is manually set (e.g., 33-35℃). The hot air furnace starts when the temperature is below 33℃ and shuts down when it is above 35℃. The temperature needs to be manually checked and the parameters adjusted daily. Ventilation needs to be manually turned on when the ammonia concentration exceeds the standard.

[0064] Performance comparison with this system: Regarding the ground temperature difference, the traditional system measures ±3℃, while this system measures ±0.5℃. The difference is due to the fact that this system includes distributed temperature sensors and artificial intelligence algorithms, which can achieve accurate temperature acquisition and dynamic adjustment in multiple areas.

[0065] In terms of daily power consumption, the traditional system consumes 0.8 kWh per square meter, while this system consumes 0.25 kWh per square meter. The difference is due to the fact that this system adopts a zoned temperature control design and graphene has high electrothermal conversion efficiency, which can avoid wasting energy by heating ineffective areas.

[0066] Regarding temperature regulation response time, the traditional system takes 30 minutes, while this system takes 5 minutes. The difference is due to the fact that the graphene electric heating film used in this system has low thermal inertia and integrates a PID optimization algorithm, which can quickly respond to temperature change requirements.

[0067] In dealing with excessive ammonia levels, traditional systems require manual intervention to activate ventilation, while this system can automatically trigger an alarm and activate ventilation equipment, thus improving indoor air quality in a timely manner.

[0068] In terms of remote management, traditional systems lack remote management functionality, while this system supports remote monitoring and parameter modification via a mobile app, which can improve the efficiency of aquaculture management.

[0069] In terms of safety protection, traditional systems only have leakage protection functions, while this system has multiple safety protection designs including overheat protection, leakage protection and communication failure protection, which can reduce the risk of equipment operation.

[0070] Comparing Examples 1-5 with Comparative Example 1, Examples 1-5 respectively target five core farming scenarios: piglet nursery, aquaculture constant temperature pool, snake breeding, northern cold-region beef cattle shed, and chick brooding shed, employing an intelligent temperature control system based on graphene heating. Comparative Example 1, on the other hand, uses a traditional farm temperature control system (hot air furnace + 8-bit microcontroller). The two differ significantly in core performance and adaptability, as detailed below: In terms of temperature control accuracy, Examples 1-5 rely on a distributed temperature sensor array and artificial intelligence algorithms (fuzzy PID, machine learning, etc.), combined with a graphene electric heating film zonal laying design, to achieve precise temperature control: the ground temperature difference in the piglet nursery is controlled within ±0.5℃, the water temperature fluctuation in the aquaculture constant temperature pool is ±0.4℃ (meeting the ±0.5℃ requirement), and the temperature in the snake breeding egg-laying area and activity area is stable at the target value of ±0.5℃; while Comparative Example 1 has no zonal control, the entire house is uniformly heated, the ground temperature difference reaches ±3℃, and the water temperature fluctuation of the traditional coal-fired boiler is ±2℃, which cannot meet the needs of temperature-sensitive groups such as young livestock and fish fry.

[0071] In terms of energy consumption, Examples 1-5 significantly reduce energy consumption by leveraging the high electrothermal conversion efficiency of graphene and the zoned on-demand heating design: the average daily power consumption of piglet nurseries is 0.25 kWh / m², aquaculture is 0.3 kWh / m², and beef cattle sheds in cold northern regions are 0.22 kWh / m². In contrast, the average daily power consumption of a traditional hot air furnace in Comparative Example 1 is 0.8 kWh / m², and that of a traditional coal-fired boiler is 0.9 kWh / m². The energy consumption of the Examples is only 1 / 3 to 1 / 4 of that of the Comparative Example, significantly reducing the operating costs of livestock farming.

[0072] Regarding the temperature regulation response speed, in Examples 1-5, due to the low thermal inertia of the graphene electric heating film, combined with the PID optimization algorithm, the regulation efficiency is much higher than that of the comparative example: the temperature of the pens in the cold northern beef cattle shed can be raised to the target value within 15 minutes, and the power can be quickly adjusted when the temperature deviation of the chick brooding shed is 0.8℃; in Comparative Example 1, the hot air furnace takes 30 minutes to respond to temperature changes, which can easily lead to cold stress and heat stress in livestock and poultry.

[0073] In terms of intelligent management capabilities, Examples 1-5 have a built-in breeding management database (storing temperature curves, ammonia thresholds, etc. for different livestock species and growth stages), support remote APP monitoring (parameter modification, alarm push, data export), and can automatically adapt to temperature requirements (e.g., automatically reducing the temperature from 35℃ to 24℃ for 42-day-old chicks). When ammonia exceeds the standard, it will trigger the ventilation equipment. In contrast, Comparative Example 1 only supports local display of basic temperature and humidity, has no remote function, and relies entirely on manual inspection for temperature adjustment and ammonia treatment, resulting in low management efficiency.

[0074] In terms of safety protection, Examples 1-5 have multiple protections: overheat protection (temperature fuse + software over-temperature limit), leakage protection, and communication failure protection (such as maintaining minimum safe power when communication is interrupted in the beef cattle shed); Comparative Example 1 is only equipped with leakage protection, without overheat and communication failure protection, and the equipment operation risk is higher.

[0075] In summary, Comparative Example 1 suffers from drawbacks such as uneven temperature, high energy consumption, slow response, reliance on manual labor, and insufficient safety protection. In contrast, Examples 1-5, through core designs such as graphene heating units, zoned control, multi-sensor perception, and artificial intelligence algorithms, comprehensively solve the pain points of traditional systems, perfectly adapt to the differentiated needs of different aquaculture scenarios, and meet the core objective of intelligent temperature control in aquaculture farms.

[0076] The above embodiments can be implemented in whole or in part by software, hardware, firmware or other arbitrary combinations. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0077] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0078] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

[0080] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart temperature control system for livestock farms based on graphene heating, characterized in that, It includes a graphene electric heating film heating unit, an environmental sensing network, an intelligent central controller, a zoned power control module, a human-machine interaction and remote monitoring terminal, and a safety protection module; The graphene electrothermal film heating units are laid in designated areas on the ground of the farm, serving as the main heat source for the system. The environmental sensing network is used to collect environmental parameters and animal-related information within the farm and transmit the collected data to the intelligent central controller. The intelligent central controller receives and processes the data transmitted by the environmental sensing network, calculates the heating power required for each area by combining preset breeding parameters and artificial intelligence algorithms, sends the zone power command to the zone power control module, and identifies abnormal system conditions. The partition power control module corresponds to the partitioned laying of the graphene electric heating film heating unit, receives partition power instructions from the intelligent central controller, and independently adjusts the power of the graphene electric heating film in different areas. The human-computer interaction and remote monitoring terminal is used for parameter setting, status display, alarm confirmation and remote monitoring. The security protection module is used to implement multiple security protections for the system.

2. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The environmental sensing network includes a temperature sensor array, a humidity sensor, and may also be equipped with an ammonia concentration sensor and an animal behavior monitoring unit. The temperature sensor array is distributed throughout the breeding house, including different heights and functional areas such as the near-ground animal activity layer. The animal behavior monitoring unit uses infrared thermal imaging equipment or sound analysis equipment to indirectly sense the animal's thermal comfort. The output of the animal behavior monitoring unit is electrically connected to the intelligent central controller, and the animal behavior data it collects is transmitted to the intelligent central controller for use by the artificial intelligence algorithm module. The output of the ammonia concentration sensor is electrically connected to the intelligent central controller, and the ammonia concentration data it collects is transmitted to the intelligent central controller to trigger air quality linkage control.

3. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The intelligent central controller has a built-in or connected breeding management database, which stores the optimal temperature curves, humidity ranges and ammonia thresholds for different livestock species and different growth stages. The intelligent central controller also includes an artificial intelligence algorithm module, which comprises at least one of fuzzy control algorithm, PID optimization algorithm, and machine learning model, and is used for: Based on current environmental parameters, target settings, and animal behavior feedback, the required heating power for each functional area is dynamically calculated. The target settings are obtained from the breeding management database or manually entered. Predict temperature change trends and adjust power output in advance; It can identify abnormal conditions such as sudden temperature drops, sensor malfunctions, and excessive ammonia levels.

4. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The partitioned power control module includes a multi-channel thyristor voltage regulator or solid-state relay, which can achieve stepless or graded power adjustment of the graphene electrothermal film in different functional areas through voltage regulation or duty cycle control.

5. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The human-computer interaction and remote monitoring terminal includes a local touch screen or control panel and a remote monitoring platform. The local touchscreen or control panel is used for parameter setting, status display, and alarm confirmation. The remote monitoring platform is a mobile APP or cloud platform, used to realize remote monitoring, parameter setting, alarm push, and data recording and analysis.

6. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The safety protection module includes an overheat protection unit, a leakage protection unit, a short circuit protection unit, and a communication fault protection unit; The overheat protection unit employs a dual protection method of temperature fuse and software over-temperature limit; When communication is interrupted, the communication fault protection unit automatically puts the system into a default safe state, which is to cut off the power supply to the graphene electric heating film or maintain a minimum heating power not lower than the safety threshold for the corresponding livestock growth stage.

7. A smart temperature control system for livestock farms based on graphene heating as described in any one of claims 1-6, characterized in that, The system's operation process includes the following steps: S1: System initialization, setting the species and growth stage of the aquaculture, or directly setting the target temperature curve; S2: The environmental sensing network collects environmental parameters such as temperature, humidity, and ammonia concentration, as well as animal behavior information in real time, and uploads them to the intelligent central controller. S3: The intelligent central controller combines preset targets, real-time data, and artificial intelligence algorithms to calculate the optimal power required by each heat-generating area. S4: The zone power control module adjusts the power supply of the graphene electrothermal film in the corresponding functional area according to the instruction. S5: The system continuously executes S2 to S4 in a loop to maintain the environment of each functional area within the set target range; S6: When the intelligent central controller detects an abnormal situation, it triggers an alarm and notifies the management personnel through human-machine interaction and remote monitoring terminal.

8. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 7, characterized in that, The abnormal conditions described in step S6 include sudden temperature drop, sensor failure, excessive ammonia concentration, and relay failure.

9. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 1, characterized in that, The graphene electric heating film heating unit is waterproof and can be used in constant temperature aquaculture tanks to achieve precise control of water temperature within ±0.5℃.

10. The intelligent temperature control system for livestock farms based on graphene heating as described in claim 2, characterized in that, When the ammonia concentration sensor detects that the ammonia concentration exceeds the ammonia threshold in the aquaculture management database, the intelligent central controller will activate the farm's ventilation equipment to reduce the ammonia concentration in the shed and improve air quality.

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