APPLICATION OF ARTIFICIAL INTELLIGENCE (AI ) FOR LIVESTOCK & POULTRY FARM MONITORING
by-DR. RAJESH KUMAR SINGH, (LIVESTOCK & POULTRY CONSULTANT), JAMSHEDPUR, JHARKHAND,INDIA 9431309542, rajeshsinghvet@gmail.com
Businessmen looking to invest in the Livestock industry have noted the increased spending power of the consumers and their willingness to pay a premium in order to have fresh and hygienic livestock products like milk delivered to their doorsteps. As a result, it is expected that there will be investments made in this sector which will aid the introduction of technological advancements both in logistics and farm management. AI is one such technology which needs immediate implementation in the livestock industry. AI will help livestock farms accumulate and analyze data to accurately predict consumer behaviour, like buying patterns, leading trends, etc. With increased investments, farms will be enabled to automate processes, reduce major costs and improve the quality of livestock products like milk.
Artificial Intelligence, will be a disrupting inclusion into this industry. Today local farmers and large dairy farms use fodder without much understanding of its impact on the milk. Changes in the fodder content and lifestyle of the animal, the weather and atmosphere, all of it have an impact on the production of milk and the quality as well.
As Artificial intelligence and machine learning become more common and easily available, it is expected in 2019, that the use of such technology in the dairy industry will automate most of the farm processes while at the same time produce information based on the farm’s operational history.
With the enormous growth in the world population, the farmers are switching to smarter techniques that can aid in regulating the proper use of land, water, and energy to feed the planet and evade the global food crisis. Researchers believe that the answer lies in sensors, robots and artificial intelligence (AI). The AI technology has been successfully adopted by several industries, and now it is set to revolutionize the future of farming with drones, robots and intelligent monitoring systems.
A technique for monitoring the health of farm animals / dairy cattle with a high degree of accuracy uses a camera and artificial intelligence (AI) to achieve a “smart” cowhouse. Detailed observation by AI-powered image analysis could enable early detection of injuries and illnesses that could impact the quantity and quality of milk production.
Have you ever thought how emerging technologies will affect agriculture in the long run to optimize management and profitability? We have seen the implementation of robotic milking machines, brushes for added cow comfort, and automatic calf feeders on dairy farms across the country and world. But, imagine a data system that monitors your cows’ activities 24 hours a day, 7 days a week from lameness and estrous detection to dry matter intake (DMI). With a new technology that recognizes each cow in the barn, this dairy farmer’s dream becomes a reality.
Cainthus is the technology company that created the cow facial recognition system that monitors cattle via cameras located on the roof of the barn. The data is then sent to a server on the farm. The main goals are to utilize the data to maximize production and limit stress levels on the cows.
There are many uses for the artificial intelligence system that can be customized for the dairy farm’s needs. This system is just one example of hundreds of new tools that dairy farms are using to adapt to this technological era and ultimately improve their operations.
Why is artificial intelligence advantageous for farmers?
In the recent times, with requirements of the better yield of farm animals , AI has emerged as a tool that empowers farmers in monitoring, forecasting, as well as optimizing the farm animal growth. Tackling parasits, biosecurity, and diseases, monitoring farm animal along with farm management are some of the thrust areas in livestock industry where the use of AI technology can pay rich dividends. At present AI is being used in:
Animal husbandry is an integral branch of agriculture concerned with the care and management of the livestock. It deals with all the tools and technologies involved in managing and ensuring optimum health of farm animals, including genetic qualities and behavior. Generating and leveraging useful information through AI will help farmers to manage their livestock efficiently with minimum supervision.
The automated milking booth is a section of animal husbandry which has an increasing application of artificial intelligence system. With AI enabled smart sensors, the automated milking units can analyze the milk quality and flag for abnormalities in the product.
A glaring gap for dairy farmers is data. Farms, especially large ones, don’t know how much an individual cow eats, how much she drinks, how much she moves, her body temperature, stress levels, sickness, etc. Even individual milk production isn’t always recorded in a consistent manner.
How can farmers manage cow comfort, select the best animals for breeding and retaining, judge true profitability, meet prosumer demands for animal welfare and sustainability and raise the bar in terms of milk production? Without precise, real-time, smart data, the task of managing individual cows is nearly impossible. But emerging digital technologies could fill that data gap.
AI promises precision livestock farming; however, if farmers can’t interpret the data and use it to take action, the data is useless. Artificial intelligence allows producers to analyze the data collected by sensors and other hardware technologies and can provide interpretations and solutions by mimicking human decision-making — potentially transforming how a dairy farm operates.
latest Dairy is implementing cow, milk and herd intelligence through their sensors and artificial intelligence technologies. They offer sensors ranging from heat detection and calving to health monitoring sensors — including the SenseTime Solution sensor, which detects and charts a cow’s daily activities, such as ruminating, eating and walking patterns. When paired with artificial intelligence software, this sensor provides users with early, proactive solutions to problems. Along with the capability to record information about reproduction, health and nutrition, the sensor also provides farmers with solutions for each individual cow.
- Artificial Intelligence for Health monitoring
The Intelligent Dairy Farm Assistant (IDA) is a result of a combination of two advanced technologies – AI and motion sensors. The IDA system comprises a motion sensor tied to the cow’s neck to transmit data about the cow’s movement. The motion-sensing device transmits movements of the cow to the AI program. The sensor data is stored and aligned with the cow’s real-world behavior. After the collection of enough data, the AI can determine the activity of the cow by reading the data alone. The fresh data from motion sensors and its comparison enables the AI to determine whether the cow is ill, ready to breed or has become less productive. The AI also sends alerts to the farmer about the change in the cow’s behavior allowing human intervention where needed. Without AI, it would be almost impossible for the farmer to keep a watchful eye on every cow in the herd.
- Artificial Intelligence for Detection of Estrus
Accurate detection of heat (Estrus) is an important factor in the success of dairy farms. The advancement in AI technology and its applications has enabled farmers to prevent losses caused by incorrect detection of Estrus. The collar (with motion sensors) tied to
the cow’s neck collects all types of data related to cow 24 hours a day. Artificial Intelligence components of the dairy automation system process the collected data to provide insights on the heat stress, change in feeding efficiency and the estrus of the cow. The occurrence of estrus cycle results in the release of special hormones that affect the cow’s behavior and movement. For example, a cow in standing heat is more likely to stand still for a long time allowing others to mount her. The AI component compares the recently collected data (about movements) with stored data and can predict the ovulation period of the cow in advance. Since the ovulation period starts after 24 to 32 hours of the onset of “Standing heat,” the farmer has enough time to prepare for artificial insemination of the cow in heat.
- Robotic System to Deliver Vaccines
Today farmers are required to give hundreds of vaccines and reproductive medicines to animals in dairy farm. If you plan to deliver vaccines manually, each dairy farm would be required to invest heavily in labor and training. For a sustainable economic future of
dairy farms and to achieve 100% compliance rate, modern dairy farms use a robotic injection system to deliver vaccines and reproductive medicines to domestic animals on the dairy farm. The robotic system is integrated with a dairy automation system. The robotic injection system reads the RFID tags attached to the cow’s ear and gets health-related information and vaccination record for the cow. If the cow requires an injection, it is directed towards the injection site and the injection mechanism position itself to deliver the medication in the cow’s neck.
Facial recognition
Facial recognition is nothing new, however this is now extending beyond humans into the world of domestic cattle. Whilst ‘smart’ cattle monitoring is more commonplace, existing systems largely require the use of physical tracking devices. Facial recognition technology will eliminate the stress of fitting these devices, allowing easy monitoring of an entire heard with minimal interaction. This is set to enable individual monitoring of group behaviour, early detection of lameness and accurate recording of feeding habits.
Although hailed as the future of farming, the extent to which AI will change the daily operations of the traditional family farm is yet to be seen. However, with new Agritech companies producing increasingly accessible technology, the ‘digital farm’ of the future may be closer than we think.
That’s the way tech is changing the dairy industry……
Aided by lasers, sensors, and data collection, automation has helped dairy farm owners overcome difficulties of finding workers ready to do manual labor at dairy farms. One good thing about automation is that animals seem to have adjusted to this new technology trend and they seem to like robots better.
1.Drones
There are opportunities for drones in the dairy industry, but they often require additional technologies. Drones can be used to generally inspect the herd or fences or to aid in herding cows from fields to barns.
The inclusion of other technologies presents greater opportunities. Visual sensors have proven to be instrumental in surveying land and measuring pasture growth. Modern dairy is using drones to map, inspect and photograph pastures in order to detect growth.
Algorithms enable drones to identify cows specifically and avoid confusing them with deer or similar animals. When combined with thermal imaging, the opportunities to locate and track cows increases dramatically, particularly in fields spotted with trees or dense foliage. Temperature detection would allow farmers to identify abnormal behavior in the cow, such as lameness, illness or calving. Drones may become more useful in these areas, particularly if battery life is prolonged and autonomous flying ability is improved.
2.Robots
Robotic milking machines are probably the most well-known application for robots in the dairy industry, increasing efficiencies and replacing expensive or unavailable labor. Lely’s Astronaut A5 and DeLaval’s Voluntary Milking System not only cut labor costs, they also allow cows to decide when they want to be milked. Robotic milkers (milkbots) clean the udders, identify the cow’s teats and milk automatically.
DeLaval offers other robotic milking technologies, such as the rotary platform, which allows farmers to maximize a herd’s milking performance while providing a comfortable and safe environment for both cows and operators. miRobot provides a milking system also designed for larger operations. Both companies offer multi-stall, automated milking operations to milk cows simultaneously, completing full parlors with only one operator. This new technology has allowed farmers to cut back on labor costs and achieve more milkings per day.
The Lely Grazeway system acts as a gateway to the pasture that only allows cows to graze after they have been milked. The cows step into the selection box, and the Lely Qwes cow-recognition system determines whether or not the cow can be let out to graze.
Before robots, cows were typically milked twice a day because of labor and time constraints. Now, cows can be milked three times a day or more, greatly increasing production and profits. In addition, while the cows are stationary for several minutes during milking, there is also an opportunity for medical and health assessments using transponders or sensors — which can not only analyze the speed, amount and quality of milk produced but also how much the cow has eaten, its heat cycle and more.
Another possible use for robots includes cleaning and sanitizing the barn, allowing for better biosecurity measures that will lead to healthier conditions for the cows. There might also be a place for robots in the calving process. While this might not be as useful for an outdoor herd, there is the potential for robotic assistance for cows kept indoors.
3. 3D printing
There are multitudinous applications for 3D printing in the dairy industry. A primary application of 3D printing is for machine parts, which may be of particular interest to rural farmers, saving valuable time and even possibly money, depending on the part needed.
In some ways, 3D printing is already challenging the dairy industry, through 3D-printed foods. Cheese is one of the easier foods to duplicate through 3D printing, due to its easily changeable state from solid to liquid. Studies suggest that printed cheese is less sticky, softer and has better meltability than non-printed cheese. The concept of printed food may not appeal to all consumers, though, so the challenge is to produce food that offers an advantage, such as lower cost, improved taste or better nutritional content.
Such is the case with “Perfect Day,” a startup company from San Francisco using 3D printing combined with gene sequencing to create a yeast fermentation product that looks and tastes like milk. The product is portrayed as a non-dairy alternative for vegans or dairy-intolerant individuals.
4. Augmented reality
Augmented reality (AR) can be defined as the integration of digital information with the user’s environment in real time
Studies have found that AR can be used to make food more visually appealing or to effectively estimate proper serving sizes. Apple’s ARKit can also be used to provide consumers with nutritional knowledge, as this video demonstrates. Should this technology become more common, these applications could affect the dairy industry, as certain aspects of food products — both good and bad — would be more readily available to the consumer.
Outside of the consumer focus, augmented reality can be used to allow producers an alternative way to monitor and evaluate cows. This video demonstrates how AR can allow a farmer to immediately see stats relating to the farm through the use of goggles. Information relating to each individual cow is overlaid through the glasses into the farmer’s field of vision. He can see information on everything in the facility and even evaluate the quality of the milk.
Could this technology not also be used in the veterinary field for inspection and observation? Perhaps if combined with reliable sensor data, the vet could be able to deliver appropriate recommendations for disease management and reduce the need for direct farm call visits, thus lowering costs.
5. Virtual reality
Virtual reality (VR) is defined as a digital environment that can be interacted with in a seemingly real way through electronic equipment. Applications in the dairy industry vary from farm tours to veterinary training, with positive impacts on safety and efficiency.
New Zealand dairy cooperative Fonterra and solutions company Beca have partnered to develop a virtual reality health and safety training technology that allows employees to navigate the manufacturing and distribution sites without actually setting foot on the physical site, thus reducing onboarding times. Fonterra employees learn to identify potential hazards and experience hazardous situations in a realistic simulated environment, enhancing learning experiences without the risk of being in harm’s way. This technology also reduces labor costs by replacing a number of hands-on health and safety training positions.
Virtual reality is being used to teach veterinary students about the reproductive and rectal tracts of the cow. Created by former vet Sarah Baillie, the Haptic Cow is a fiberglass model of the rear of a cow that combines virtual reality with robotics. The VR aspect is provided by a computer that allows students to visualize an object within the cow — virtually enabling them to practice fertility examinations, such as pregnancy detection, or determine reproductive concerns without putting them in a situation that could be dangerous for both the cow and the student.
DeLaval is creating virtual reality films of farms available in 360 degrees, allowing viewers to scroll from side to side to view the entirety of the dairy barn. The Hamra Farm in Sweden, for instance, showcases the innovative techniques they implement on their farm, such as robotic milking machines, robotic brushes, robotic cleaners and more, in their VR film. These “farm tours” will allow consumers to better understand where their dairy comes from. There is much discussion about animal welfare, and giving consumers an opportunity to experience firsthand how a dairy farm operates is an important component of influencing perception the industry.
6. Blockchain
It is well known that consumers are increasingly becoming interested in where their food comes from and how it is produced. Blockchaincan connect all aspects of the supply chain from producer to consumer and allow for food traceability and safety. From an agriculture and food perspective, offering this type of information to consumers will become a competitive advantage and may not prove as challenging in dairy as in other areas of agriculture, such as beef, which exchanges ownership more frequently.
7. Internet of Things
Together these eight technologies are creating opportunities within the dairy industry for increased efficiencies, profitability and production. The connectivity of these technologies is made possible through the Internet of Things (IoT).
Agriwebb is a company using IoT for full farm recordkeeping, including field management, inventory, operations, grazing and even biosecurity. Stellapps in India leverages IoT to offer all manner of products, from general herd management to milk evaluation, payment processing and cold chain monitoring. Dell Technologies is also heavily involved in IoT applications and is working with dairy producer Chitale.
Cargill is working with SCiO (Consumer Physics) to create Reveal, an app designed to deliver content of feed within minutes. Previously, this type of technology was either time-intensive (waiting on lab results) or expensive (specialized equipment cost thousands of dollars). Using a micro spectrometer with NIR calibrations, Cargill and SCiO offer this simple service using producers’ own devices, and results are available in a minute’s time.
IoT technology is how the KEENAN InTouch system is able to provide farmers with the nutritional information they need to ensure the best formulation possible. KEENAN’s feed mixers are designed to give uniformity to feed, allowing for improved digestion in the ruminant and creating rations that are both chemically and physically balanced. The cloud-based system enables producers to monitor feed waste and make necessary changes to improve efficiencies and decrease costs.
Using the data
In the past, farm management applications have allowed farmers to make strategic management decisions based on the collection of farm data. Inevitably once nutritional decisions are being made, sciences such as nutrigenomics and decisions about smart nutrition are critical to taking advantage of this enhanced data and management information systems. Nutrigenomics research has shown that specific nutrients and inclusion of enzymes can greatly impact milk yield.
Previously, collected data was generalized for an entire dairy farm. Through the use of sensors, AI and other technologies, farm management apps like FarmWizard can provide individual data for each cow, allowing farmers to improve precision and accuracy when making managerial decisions.
Artificial intelligence in poultry(AI)
Growth in poultry farming has been relentless, and rising to meet that growth are digital technologies that can offer producers an enormous efficiency advantage.
AI technologies have become the backbone of many other technologies. Robots, for example, use AI in the processing plant to improve efficiencies. Automating procedures such as chicken deboning require recognition of the shape and size of each chicken and individual adaptation. Artificial intelligence is the perfect technology for this application. By combining technologies, robots perform the work that AI instructs them to do based on the data that sensors collect.
Artificial intelligence can monitor and control the environment of the house. Sensors collect the information, software tracks it and AI adjusts the conditions of the house or alerts the farmer if there is a potential issue, such as an ill bird. All of this information can then be transferred to the farmer’s smartphone or tablet.
Drones in Poultry————
Although there is concern that drones could make flock nervous and stress, yet it is a better solution for free-range or yard farms where birds are allowed to roam freely. They work as nannies for these domestic fowls.Constant monitoring of aviculture with the help of drones is beneficial to increase yield. Drones take pictures of the bird throughout the day at designated pace and send it instantly to the systems and build the database for analysing the behaviour of the flock.
How is this data used?
Developers use the data sent by drones to train computer vision models to understand the behaviour of the domesticated birds.
Training models to detect bird flu or avian diseases
The infected birds have symptoms like nasal and saliva secretions apart from high temperature. Pictures sent from drone are annotated and fed to the machines to recognise the disease at an early stage as the infection is contagious and leads to reduced production. It also helps farmers in saving the life of chicks as clogging blocks the nose of the bird leading to death.
By annotating the nasal or oral secretion on the beak of chicken with polygon tool, machines can be trained to identify the difference between a healthy bird and influenced bird. Polygon tool helps the developer to annotate precisely the target shape and texture of the secretion.
Training models to detect nutritional deficiencies in chicks.
Like human’s domestic fowl also suffers with nutritional deficiencies and young chicks die due to immobility and suffocation. A farmer can avoid such loss by early detection. Developing machines that detect bone deformities and decreased growth of young chickens need appropriate data annotation tools.
By drawing a box over the bird with box annotating tool, machines can be trained to identify the bone deformities and reduced growth of the birds. The machine is trained to understand the difference between a healthy and defected birds.
Training models to detect Behavioural diseases like cannibalism (or aggressive pecking).
Pecking behaviour often leads to the plumage of laying hens and this can lead to health and welfare conditions of the flock. Death occurs within 10 minutes of pecking, so early detection becomes the need of the hour. Building machine which gives alerts to the farmers regarding cannibalization within the timeframe of destruction will enhance the productivity of the poultry.
By Using box annotating tool, machines can be trained to detect the behaviour of feather pecking in birds and its severity. It also enables to identify the injured birds.
It is estimated that world poultry production will increase 120 percent from 2010 to 2050, and in order to meet this demand, feed conversion ratios and other production efficiencies must continue to improve. The incorporation of digital technologies, such as those listed above, will greatly aid in these efficiencies and help poultry producers to rise to the demands and meet the increasing needs of a global population.
Changes are happening so fast that the connected farm is likely to be the norm within the next 10 years. By implementing the eight technologies described here, along with the interconnectivity of IoT, farmers will be able to capture and have direct access to individual cow data, both current and historical. This will enable farmers to bridge the data gap and improve dairy production through digitization. The winners will be those who embrace this disrupted digital dairy landscape.
Artificial intelligence is the future of the livestock farming , but unfortunately, it also has some challenges on its back. This is why the new and existing players in the global AI technology market will need the customary assurances before taking the leap into the agricultural sector. With drones, robots and intelligent monitoring systems now successfully being used in research and field trials, artificial intelligence, or machine learning, is set to revolutionise the future of farming as the next phase of ‘ultra-precision’ livestock farming is on the horizon.
