AI In Agriculture: How Robotics Have Helped Innovate This Industry

The agricultural industry is quick to adopt AI solutions. The agriculture industry is only second to Defense in adopting and using AI-driven robotics technology. By 2050, the average farm will be generating up to 4.1 million data points every day, on average, enabling farmers to make informed decisions and improve farming efficiency.

Let us explore the various areas in agriculture where AI and robots are making a difference.

Application of AI in Agriculture

 

Spraying of chemicals

Modern farms generate thousands of data points every day. Temperature, soil, water, and weather can be monitored and processed by artificial intelligence and machine learning models to detect pests, poor nutrition, or weeds and determine the herbicide to spray. The herbicide is then delivered using artificial intelligence and drones for precision spraying, which can eliminate up to 80% of the chemicals usually sprayed.

Harvesting

Robots can harvest with more accuracy and speed in bulk quantities while improving yield size and reducing wastage.

The underlying technologies are sensor fusion, machine vision, and artificial intelligence that together locate harvestable produce and pick the right fruits.

Managing livestock

AI is leading to autonomous livestock farming by a network of robots that analyze milk data in real time, adjust feeding rations, and clean the manure. The generated data can be further analyzed to detect inefficiencies due to illness. Farmers can simply maintain oversight through remote monitoring.

Technology Trends in Agriculture

Blockchain

Blockchain technologies append the plant information to an auditable, decentralized database, allowing farm owners to track the food at every stage of the supply chain. In this way, the technology helps regulate the shelf life and quality of food, helping retail stores detect spoiled food in real-time.

Indoor/urban farming

Robotics have enabled indoor farming for greenhouses to maximize the use of available space in urban areas, with a 10x increase in yields per square foot compared to traditional farming. These farms work 24x7 with artificial light from LEDs, precise nutrient application, and automated harvesting. It comes with the added advantage of reduced need for transportation.

Farm Automation & IoT

Many farmers today are equipped with drones to monitor the crops and advanced sensors telling them the precise amount of water or fertilizer required. The increasing level of automation can reduce the need for manual labor at farms through watering, seeding, and harvesting.

IoT can further help realize smart farming through constant crop monitoring and tracking soil moisture, crop health, or livestock conditions using LiDAR sensors.

Predictive analytics

Profitability in farming could primarily be a matter of predicting the best time to sow to obtain maximum yield through analysis of the soil health and fertilizer recommendations along with a week's weather forecast.

It is also possible to predict crop yield predictions and price forecasts for a season. With big data, AI, and machine learning, farmers can predict future price patterns, demand levels, and recommendations of what crop to sow for maximum benefit.

Challenges in the Adoption of Robotics

For the successful application of robotics and AI, there are several challenges that need to be addressed. Let us take a look at a few of them:

Smallholders: For innovations to reach their potential, we need to create a fostering environment, not just for giants but also the smallholders. Every attempt should be made to educate these smallholders about relevant technologies. Providing access to technology without the knowledge would be an exercise in futility.

Energy supply: Robotics needs electricity to function, and some agricultural robots are power-hungry. Countries must provide provisions for a continuous supply of energy. Many forms of renewable energy, such as solar or wind energy, can be tapped depending on the climate.

Connectivity: Connectivity is not always available in rural areas. Without a suitable connectivity infrastructure in place, none of this is possible. The devices need to be on a network for effective automation. The farmers must have access to weather forecasts, pricing, and other information to make informed decisions. On top of that, the network's cybersecurity is also a concern.

Impact of AI on Agriculture

AI-based technologies enable farmers to produce more output with less input, improve quality, and go to market faster. Robotic agriculture is necessary today to account for the world's population, shrinking of cultivable space, and labor shortage in the agricultural industry. Robotic agriculture can bring about a sustainable change in the system.

Agricultural robots can drive sustainability, reduce carbon footprint, and lower costs but only with the right set of sensors.

At Hokuyo, we provide high-quality sensors to equip agricultural robots with the ability to generate and track relevant data about plant health, soil moisture, or the need for fertilizers.

Contact us to find the best-fit sensor products for your agricultural robot.