Enhancing Agricultural Efficiency with Custom Automation Solutions

Within the next two decades, the demand for food, pet food, and animal feed will increase dramatically. Conventional farming techniques won’t be able to meet the needs of humanity without improving processes, which is why farmers are increasingly turning to automated agriculture. Automation projects for the agricultural sector look to produce more while using less energy, land, manual labor, and water. In modern-day agriculture, automation projects are driven by several new technologies, including artificial intelligence (AI), data management, analytics software, the Internet of Things (IoT), machine learning algorithms (a subset of AI), robotics, and other hardware and software.

Agriculture automation projects can provide benefits that include: 

• Cutting water used to irrigate crops
• Decreasing need for humans in the workforce
• Expanding overall food production
• Heightening efficiency of operations
• Improving project management
• Increasing harvests of food crops

Today’s new technologies are driving automation within agriculture. Just as it does in food, pet food, and animal feed production, automation projects are changing how farmers grow their crops. This will, in turn, make farming more efficient and productive while also reducing the negative environmental effects often seen in industrialized agriculture.

When it comes to agriculture automation, projects for optimizing farming extend to multiple technologies and applications. Robots that sow seeds and harvest crops are only a part of the sector’s automated solutions for agriculture. Automation projects extend to soil management and monitoring plant health at scale with analytics software, mobile applications, satellite images, and data collected by IoT sensors. With AI and machine learning, farmers can monitor land and plants to use less water, pesticides, and herbicides to produce the same or higher harvests.

Much of the valuable data on land and crops relies on IoT-enabled sensors that evaluate land used for agriculture. Automation projects rely on data collected by smart sensors within soil and plants or connected to drones to enable farmers to identify physical or chemical changes affecting agricultural production. These include dielectric sensors that monitor moisture levels, electrochemical sensors to gather data on chemicals within the soil, mechanical sensors that analyze soil density, and optical sensors that measure how much light an area receives. Regarding quality control, digital imaging equipment combined with AI can identify colors, forms, and sizes while also detecting any anomalies to keep poor-quality products from making their way to consumers. 

These drones – also referred to as unmanned aerial vehicles (UAVs) – have high-resolution cameras and sensors and fly over farmland, taking photos and videos of fields where crops are produced. Farmers collect data from these images, processing it via machine learning algorithms to better fertilize their crops while ensuring that pests and weeds are kept at bay. However, these smart visual systems can also be added to tractors, where they can collect information on fields and crop yield by using specialized analytics software to evaluate the gathered data.  

The benefits of smart sensing devices paired with analytics add significantly to conventional farming processes. Farmers can use these sensors to measure nutrients in the soil, along with its moisture, pH, salinity, and temperature. Analytics software can access data stored in the cloud to compare historical data from past years and harvests to real-time data from the fields. With a better understanding of nutrient levels in the soil, farmers can add the proper amount and right kinds of fertilizers, reducing costs while limiting pollution and making their operation more sustainable.

Another way in which smart farming can help is through pest management. According to the UN Food and Agriculture Organization (FAO), as much as 40 percent of global agricultural production is lost because of pests, estimated to cost $70 billion in losses. Again, this problem can be dealt with via agriculture automation. Projects to detect pest infestations before they become problems involve IoT cameras with low-power sensors that monitor insect traps, capturing images of the types of pests attacking a crop. With computerized vision equipment supported by AI, the numbers and insect types are identified, while analytics apps help recognize patterns by comparing real-time to historical data. This information can then direct pesticides to only the infected areas.

With smart agriculture, automation projects identify pathogens and pests with: 

• AI software that distinguishes pathogens or pests, using data gathered by smart cameras with fluorescent sensors that monitor changes in chlorophyll levels within crops.
• Analytics software uses AI and machine learning algorithms to analyze data and optimize pesticide use, limiting its application while improving crop health.
• Infrared and thermal IoT sensors that spot indicators of pest and pathogen attacks, with alerts using AI, machine learning algorithms, and predictive analytics to detect anomalies.
• Sounds of pests are picked up by acoustic sensing devices that can detect large concentrations of insect pests.

Automation projects help farmers become more efficient and productive in this new iteration of agriculture. This includes automating basic tasks like inventory management of farm equipment, fertilizers, fuel, seeds, and other agricultural items. For example, automation projects within the industry could include notifications from AI chatbots that warn when inventory of certain items requires restocking.

Having greater control over these basic business functions ensures farmers have everything they need for planting, irrigation, fertilization, and harvesting of crops. This extends to supply chains for shipping harvested crops to market as well. With agriculture automation projects handling logistics, farmers can use technology to evaluate delivery times, shipping itineraries, vehicle capacities, and other variables within the supply chain. This helps reduce customer delivery times, transportation costs, and farm product waste. Good for the modern farmer is good for food, pet food, and animal feed manufacturers.

Whether known as livestock farming and ranching, animal husbandry, or animal agriculture, automation projects in this sector are also under pressure to increase food production for an increasing global population. Developed countries increasingly make laws to minimize environmental harm while respecting animals used to produce food products, with automated technology making livestock farming more sustainable. With the rise of digital technology, automation in agriculture has resulted in robotic milking systems, drones to monitor animals in the field, and automated feed manufacturing, and livestock feeding systems.

Agriculture automation projects for livestock need to consider the following: 

• Animal welfare: For animal agriculture, automation projects can help better track large flocks and herds, even when spread over a wide geographical area.
• Automated butchery: Humane slaughter techniques performed by automated systems augment efficiency and decrease labor costs of a livestock operation.
• Automated cleaning: Sanitation is often an issue with larger farms, with hygiene an important factor for animal health; robotic or automated systems using pressurized water and drain systems ensure animal living spaces are cleaned regularly.
• Automated egg collection: While robots collecting eggs and conveyor belts transporting them may seem more akin to a factory than agriculture, automation projects incorporating such labor-saving devices reduce operational costs while improving efficiency.
• Automated feeding: Such feeding systems offer farmers precise control over their livestock through the use of IoT controllers, sensors, valves, and other devices that enable feeding according to animals’ nutritional needs; animal agriculture automation projects involved in feeding livestock lead to less waste, improved rates of growth and more efficient breeding.
• Automated feed manufacturing: From automatic ingredient batching systems, to complete feed mill manufacturing control systems, automation has transformed modern feed production and will continue to do so over the next several decades to continue supporting the increasing demand for feeding our growing population.
• Automated vaccination: Systems involving robotics and sensing devices can vaccinate livestock with greater accuracy, reducing labor costs.
• Breeding: Natural animal reproduction can be dicey, so automated insemination, embryo transference, and other technologies involving animal reproduction are supported by various digital technologies.
• Climate control: Like humans, temperature extremes can stress livestock, so systems for regulating air circulation, humidity, and temperature make animals more comfortable, improving an operation’s productivity.
• Disease control: Early detection of sick animals can prevent the spread of disease, which smart sensors and AI software can augment to mitigate impact.
• Genetics: Testing for and analyzing desirable genetic traits when selecting animals for breeding helps livestock farmers increase their productivity; analytics software can help evaluate data associated with breeding animals for such characteristics as greater resistance to disease and higher adult weights.
• Labor efficiency: Automation projects need to consider all aspects of animal farming, including long hours spent caring for, feeding, and watering livestock, as well as marketing and selling them; automation must optimize a livestock farmer’s labor so that they can do more with less.
• Labor shortages: In US agriculture, automation projects need to deal with the significant challenges faced by the industry regarding the shortage of agricultural workers and high labor costs.
• Livestock monitoring: IoT sensing devices in the fields combined with data analytics software can examine breeding, grazing, and other animal behaviors and their health; these technologies work together to enable farmers to make data-driven decisions concerning breeding, disease, and feeding, among other factors affecting livestock.
• Optimizing hatcheries: An egg farm’s productivity can be improved by using near-infrared hyperspectral imaging with machine learning to detect infertile eggs and remove them earlier.   
• Robotic milking: For dairy-based agriculture, automation projects should focus on optimizing the efficiency of a milking operation while reducing labor costs, with data collected offering a window that can improve cattle genetics and breeding.   
  

As in other areas of agriculture, automation projects in livestock farming and animal feeding offer farmers savings in energy, equipment, feed, and labor costs while mitigating carbon footprints, soil degradation, and water pollution. To these ends, automated agriculture incorporates digital technologies like AI, data analytics, IoT, and others associated with what’s become known as Industry 4.0 or the digital revolution. These technologies help livestock farmers and ranchers monitor their animals’ breeding, drinking patterns, genetics, health, posture, and weight by providing insights that promote data-driven decision-making.

Sterling Systems & Controls Inc. provides electrical process controls and custom automated solutions for animal feed manufacturing, pet food production, food processing, baking, and many other industrial processes. Automation projects for farmers of all sorts can benefit from our cutting-edge technology. To learn more about our products and services, contact Sterling Systems & Controls today.