System for automated feeding of shrimp feed using drone technology

Abstract

A system for the automatic distribution of shrimp feed using drone technology, consisting of: a drone (101) configured to fly over aquaculture ponds; a food container (102) attached to the drone and configured to store crab food; a food spreading mechanism (103) operatively coupled to the food container for releasing food during flight; a flight control unit (104) operatively connected to the drone for autonomous or semi-autonomous navigation based on predefined coordinates; a sensor module (105) configured to detect the amount of feed within the container and to trigger refilling operations when it is below a threshold; and a communication interface (106) configured to send and receive operational data between the drone and a remote control station (107), the system enabling programmable feed distribution across aquaculture ponds to optimize feed utilization and reduce manual labor.

Description

Scope of the invention:

[0001] The present invention relates to the field of aquaculture automation and, more particularly, to a shrimp feeding system using unmanned aerial vehicles (UAVs), commonly known as drones, to improve feed distribution precision and operational efficiency. Background of the invention:

[0002] Shrimp aquaculture has emerged as one of the most dynamic sectors within the global seafood industry, driven by increasing demand, export potential, and its role in supporting rural livelihoods. However, one of the most persistent challenges in shrimp farming is the feeding process, which plays a critical role in determining both the economic viability and environmental sustainability of shrimp production. Traditional shrimp feeding techniques, which are predominantly manual, rely heavily on human labor and are typically inconsistent and inefficient. Farmworkers generally scatter feed by hand along pond banks without accurate knowledge of the actual amount required or the shrimp's feeding behavior.This method not only leads to overfeeding or underfeeding, but also causes significant feed waste—one of the most significant recurring costs in aquaculture.

[0003] Overfeeding can cause uneaten feed to accumulate at the pond bottom, deteriorating water quality and increasing the likelihood of disease outbreaks, thereby compromising shrimp health and survival rates. In contrast, underfeeding restricts growth, prolongs time to market, and limits yield. Irregular feeding schedules, which often depend on labor availability or environmental factors such as heavy rainfall or high temperatures, further exacerbate the problem. Feed management, therefore, is not just about delivering nutrients to the shrimp—it also involves precise decision-making regarding feeding timing, quantity, and distribution pattern. It is widely recognized that optimal feeding contributes significantly to shrimp health, survival, feed conversion ratio (FCR), and overall production costs.

[0004] In response to these challenges, numerous technological innovations have been proposed and tested. Automated pond-side feeders, for example, dispense feed at set intervals. While such systems improve consistency and reduce dependence on labor, they remain largely static, cannot cover large pond areas, and do not adjust feeding based on the shrimp's real-time behavior. Smart systems that utilize sensors and microcontrollers have also been investigated and often include environmental monitoring tools such as dissolved oxygen sensors, temperature probes, and water quality indicators. These systems, while promising, are often complex, require regular maintenance, and demand a level of technical expertise that smallholder or rural farmers may find difficult to meet.

[0005] Recent developments in aquaculture technology have also explored the integration of blockchain, Internet of Things (IoT), and human-machine interfaces (HMI) to improve transparency, traceability, and operational control. However, these advanced technologies often require significant investments in capital, infrastructure, and training, which may not be feasible or scalable for shrimp farms in developing countries. The lack of mobility in these systems also means that precise and targeted feed distribution remains out of reach.

[0006] The proposed invention is driven by the need for a simple, cost-effective, and mobile solution that enables accurate, consistent, and timely feed distribution. Drone technology, which has been rapidly adopted in various sectors such as agriculture, logistics, and surveillance, presents a compelling opportunity for aquaculture. Its ability to quickly reach remote or large areas and its automation capacity make it an ideal platform for feed delivery in shrimp tanks.

[0007] Although drones are used in agriculture for spraying pesticides, mapping crop health, and seeding, their application in aquaculture—particularly in feeding operations—remains underutilized. A drone-based feeding system offers significant advantages: It eliminates the need for labor-intensive feeding methods, ensures even feed distribution over large pond areas, and enables precise application by following programmed flight paths. Furthermore, such a system can be complemented with real-time monitoring tools, GPS navigation, and telemetry data collection, making it a smart and adaptive solution.

[0008] Furthermore, the drone-based system reduces human intervention, which is particularly important in aquaculture environments, as human presence can disrupt shrimp's natural behavior, especially during feeding times. This system also offers flexibility in operating hours, allowing feeding to occur at optimal times of day or night determined by shrimp behavior and environmental data. The integration of lightweight sensors, machine learning, or image analysis in future iterations could further enhance the system by detecting shrimp activity at the pond surface and dynamically adjusting feed amounts.

[0009] The present invention therefore aims to bridge the gap between current manual and semi-automated feeding systems and the ideal of a fully autonomous, intelligent feed distribution system. It aims to democratize technology by offering an accessible and affordable solution that can be adopted by shrimp farmers regardless of their technical background. By leveraging the strengths of drone mobility, automation, and precise delivery, this invention represents a significant step toward modernizing shrimp aquaculture, making it more efficient, profitable, and sustainable. Summary of the invention:

[0010] The invention, entitled "Feeding Shrimp Feed Using Drone Technology," represents a novel, automated solution aimed at improving the efficiency and precision of shrimp feeding operations in aquaculture. This invention is designed to replace traditional labor-intensive feeding methods with a drone-based system capable of evenly and precisely distributing shrimp feed throughout shrimp tanks. The system introduces an autonomous or semi-autonomous drone equipped with a feed hopper and a spreading mechanism that is programmable and responsive to real-time inputs. This not only ensures uniform feed distribution but also significantly reduces labor and operational inconsistencies.

[0011] The core of the system revolves around a lightweight, battery-powered drone equipped with GPS navigation, a feed storage unit, a rotating or vibrating feed dispensing mechanism, and a basic sensor module for monitoring feed levels. The drone is designed to operate either along a predefined flight path or under the guidance of a remote control system. The operating cycle begins with the loading of shrimp feed into the container at a base station. Once in the air, the drone navigates to the designated zones in the shrimp tank, distributing the feed evenly as it moves. After completing the scheduled feeding, or when the feed supply is depleted, the drone autonomously returns to the base station to refill or recharge.

[0012] This system addresses one of the most critical inefficiencies in shrimp aquaculture feed waste. Through precise and targeted feed distribution, the drone ensures that feed is distributed only where and when it is needed. Unlike static pond feeders, the drone's mobility allows it to cover large or irregularly shaped pond areas, ensuring each zone receives equal attention. The distribution mechanism, controlled by a microcontroller, regulates the amount of feed released, preventing overfeeding and reducing the accumulation of waste at the pond bottom. This contributes to improved water quality, healthier shrimp, and higher survival rates.

[0013] Another important aspect of this invention is its scalability and ease of use. The drone feeding system can be deployed in farms of varying sizes without requiring major infrastructure changes. Its modular design allows for the addition of advanced features such as environmental sensors, image recognition, and AI-assisted behavior tracking. Over time, such improvements may enable the drone to detect shrimp activity at the pond surface and adjust feeding strategies accordingly. These future possibilities point to a robust platform for intelligent aquaculture management.

[0014] Furthermore, the drone-based feeding system brings significant economic benefits. Feed accounts for a large portion of operating costs in shrimp farming. By reducing waste and optimizing feed utilization, the system directly reduces expenses. Furthermore, the automation of the feeding process minimizes labor costs and eliminates human errors. It allows farm managers to remotely schedule feeding operations, monitor results via telemetry data, and make data-driven decisions to improve productivity. The system also improves the consistency of feeding schedules, a crucial factor in promoting uniform shrimp growth and shortening harvest time.

[0015] In terms of environmental impact, the invention reduces the ecological footprint of shrimp farming by minimizing nutrient pollution in pond ecosystems. Less uneaten feed means a lower risk of algal blooms, oxygen depletion, and disease outbreaks, all of which can impact the long-term health of the pond. In regions where aquaculture coexists with fragile coastal or inland ecosystems, such innovations can play a critical role in balancing economic development with environmental protection.

[0016] In summary, this invention embodies a transformative approach to shrimp farming by integrating drone technology into one of the most fundamental aspects of aquaculture—feeding. It offers a practical, cost-effective, and technologically advanced solution to a long-standing challenge. The system combines the advantages of mobility, precision, automation, and real-time control to revolutionize feed distribution in shrimp pools. With further research and development, it has the potential to serve as the foundation for broader smart aquaculture initiatives that ensure food safety, economic growth, and environmental responsibility in the aquaculture sector. Short description of the drawing Fig. shows a block diagram of the system according to the invention. Detailed description of the invention

[0017] The present invention relates to the field of aquaculture automation and, more specifically, to a system that utilizes drone technology for the efficient, consistent, and cost-effective feeding of shrimp in aquaculture farms. It introduces a new paradigm in shrimp feeding by replacing conventional, labor-intensive, and inconsistent feeding methods with a mobile, programmable, and intelligent drone-based system that provides real-time control, precision, and adaptability. This invention is intended to serve as an accessible solution that improves feed utilization, shrimp growth, water quality, and farm economics, while reducing reliance on manual labor and minimizing environmental impact.

[0018] Shrimp aquaculture, which is growing rapidly in many parts of the world, still relies on outdated methods of feed distribution, such as hand scattering or the use of stationary feeders. These approaches often result in inefficient feed utilization because they cannot dynamically adapt to shrimp feeding behavior and environmental conditions. Traditional methods offer no form of automation or feedback mechanisms and are prone to variability caused by human error, inconsistent scheduling, and a lack of monitoring tools. This leads to the common problems of overfeeding—where excess feed sinks to the pond bottom, causing waste and deteriorating water quality—and underfeeding, which impairs shrimp growth and overall yield. Both scenarios result in suboptimal productivity and economic losses.

[0019] To solve these problems, the present invention integrates unmanned aerial vehicles (UAVs), commonly referred to as drones, into the shrimp feeding process. A key feature of the invention is the use of a drone platform equipped with an onboard feed hopper, a feed spreading system, a flight control module, navigation sensors, and a real-time communication interface. The drone is configured to fly autonomously or semi-autonomously over the shrimp pond, precisely and evenly distributing feed across the water surface. The drone's flight path, altitude, speed, and feed spreading pattern are all programmable and adjustable based on the pond design, shrimp density, time of day, and environmental parameters.

[0020] The drone used in this invention is a quadcopter or multi-rotor UAV, selected for its maneuverability, stability in flight, and ability to hover over specific pond locations to ensure precise feed distribution. The fuselage is designed to be lightweight yet strong enough to carry the required load of shrimp feed. It includes a battery-powered propulsion system that allows sufficient flight time to cover multiple feeding areas within a farm. The drone is equipped with GPS for navigation and geofencing to ensure it stays within the pond's operational boundaries. In addition, inertial measurement units (IMUs) and altimeters are employed to stabilize flight and maintain a constant altitude during feeding operations.

[0021] Mounted in the center or bottom of the drone is the feed hopper—a removable hopper that can hold a specific amount of shrimp feed pellets. The hopper is made of food-grade, lightweight materials to prevent contamination and maintain the drone's balance. At the base of the hopper is a motorized feed distribution mechanism, typically consisting of a rotary fan or auger, that evenly distributes the feed across the pond surface as the drone moves. The application rate is controlled by an embedded microcontroller, which adjusts the speed of the fan or auger based on predefined parameters or real-time commands.

[0022] A unique aspect of the invention is its real-time control and monitoring capability. The drone is connected to a ground station or mobile application via a wireless communication module, such as Wi-Fi, RF, or LTE, depending on range requirements. This interface allows operators to enter flight routes, monitor the drone's status, control feeding schedules, and receive telemetry data such as battery life, remaining feed in the hopper, GPS coordinates, and flight duration. The system can also include a feedback mechanism that alerts the operator when the feed supply is depleted during flight, prompting the drone to return to a base station for refilling.

[0023] The base station serves as a central hub for drone operations. It serves as a docking point for charging the drone batteries and refilling the feed hopper. In advanced implementations, the base station may include an automated feeding system that uses conveyor belts or pneumatic systems to refill the hopper, enabling continuous and uninterrupted feeding operations with minimal human intervention. Solar panels or grid connections can be integrated into the station to ensure power availability in remote locations.

[0024] The operational workflow begins with preloading the drone with a specified amount of shrimp feed at the base station. Using the control interface, the operator defines the coordinates and pattern of the feeding route, which can include a zigzag, spiral, or grid flight path depending on the shape and size of the pond. The drone takes off and climbs to a preset altitude, then navigates along the defined path while activating the feeding system. It maintains a consistent speed and altitude to ensure the feed is evenly distributed across the water surface. The distribution mechanism works synchronously with the flight system, adjusting the release rate as needed based on the drone's speed and the desired feed density.

[0025] Once the drone completes the feeding path or detects that the feed bin is empty, it automatically returns to the base station. The return-to-base (RTB) function is triggered either by an internal timer, a GPS waypoint, a feeding sensor signal, or a low battery warning. After landing, the drone can be manually or automatically refilled and recharged for the next feeding cycle. The frequency and timing of feeding sessions can be adjusted based on farm requirements, shrimp age, water temperature, and other parameters that affect feeding behavior.

[0026] The drone feeding system not only optimizes feed distribution but also offers enhanced potential for data collection and analysis. By integrating environmental sensors or cameras, the drone can collect real-time data on shrimp activity, water surface conditions, or anomalies such as algal blooms and debris. These data points can be analyzed to refine feeding strategies, predict shrimp growth rates, and detect problems early. Over time, machine learning algorithms can be applied to the historical data to predict optimal feeding schedules and amounts based on environmental and biological patterns.

[0027] In some embodiments of the invention, the system can be integrated with farm-wide aquaculture management software, including modules for water quality monitoring, shrimp health assessment, stock management, and harvest planning. This integration enables a holistic view of the farm's operations, enabling informed decision-making and strategic planning. For example, if oxygen levels in the water drop significantly, the system can postpone feeding to prevent stress-related mortality. Similarly, if shrimp are observed to be less active during a scheduled feeding, the drone can delay feeding or adjust the amount of feed to avoid waste.

[0028] The system's scalability is another key feature. While individual drones can serve small or medium-sized farms, multiple drones can be deployed in tandem for large-scale operations. These drones can operate independently or in coordinated swarms, with each drone assigned to a specific zone of the farm. The system supports modular expansion, allowing farms to start with a single unit and add more drones as operational needs grow. This modularity ensures affordability and accessibility, especially for small and medium-sized enterprises (SMEs), which make up a large portion of the global shrimp farming sector.

[0029] The invention also emphasizes environmental sustainability. By improving feed utilization efficiency, the drone feeding system reduces the accumulation of organic waste in ponds, which in turn reduces the risk of eutrophication and disease outbreaks. Better water quality means less reliance on antibiotics and chemical treatments, which is consistent with the goals of responsible and sustainable aquaculture. Furthermore, the reduced need for labor-intensive feeding processes reduces the carbon footprint associated with human transportation and the use of manual equipment.

[0030] From an economic perspective, the advantages of the invention are significant. Feed typically accounts for 50-70% of operating costs in shrimp farming. Any reduction in feed waste directly translates into cost savings. Furthermore, automation reduces dependence on skilled labor, a resource that is becoming increasingly scarce and expensive in many shrimp farming regions. The ability to consistently execute feeding schedules, regardless of weather or time of day, also contributes to higher shrimp growth rates and shorter production cycles.

[0031] The invention is designed with simplicity and practicality in mind to ensure that it can be assembled, operated, and maintained by users with minimal technical expertise. Instruction manuals, mobile apps with user-friendly interfaces, and remote support for troubleshooting can promote widespread adoption. Maintenance requirements are minimal and typically include replacing batteries, cleaning the feed hopper, and occasional calibration of the dispensing mechanism.

[0032] In summary, the detailed design and implementation of this drone-based shrimp feeding system reflect a deep understanding of the practical challenges in modern aquaculture. By leveraging the core principles of mobility, automation, real-time control, and adaptability, the invention provides an innovative solution that not only improves feed efficiency and shrimp health but also aligns with the overarching goals of technological inclusivity, economic sustainability, and environmental responsibility. It represents a critical advancement in aquaculture technology and paves the way for future developments in smart agriculture and digital aquaculture ecosystems. List of reference symbols 101 Drone 102 feed containers 103 Mechanism for distributing feed 104 Flight control unit 105 Sensor module 106 Communication interface 107 Remote control station

Claims

[1] A system for the automatic distribution of shrimp feed using drone technology, consisting of: a drone (101) configured to fly over aquaculture ponds; a food container (102) attached to the drone and configured to store crab food; a food spreading mechanism (103) operatively coupled to the food container for releasing food during flight; a flight control unit (104) operatively connected to the drone for autonomous or semi-autonomous navigation based on predefined coordinates; a sensor module (105) configured to detect the amount of feed within the container and to trigger refilling operations when it is below a threshold; and a communication interface (106) configured to send and receive operational data between the drone and a remote control station (107), the system enabling programmable feed distribution across aquaculture ponds to optimize feed utilization and reduce manual labor. [2] The system of claim 1, wherein the feed distribution mechanism comprises a rotary fan that distributes the feed evenly across the water surface based on drone speed and altitude. [3] The system of claim 1, wherein the drone further comprises a GPS module for real-time location tracking and flight route control over predefined pond areas with geofencing. [4] The system of claim 1, wherein the communication interface comprises a wireless module selected from Wi-Fi, LTE, or RF communication protocols. [5] The system of claim 1, wherein the drone is configured to automatically return to a designated base station when a low charge level or low battery status is detected. [6] The system of claim 1, wherein the drone is operable via a mobile or web-based application that enables scheduling of feeding times, setting of application rates, and real-time monitoring of feeding operations.

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