Caring for plants and producing crops for food is a demanding task. Farmers have to deal with a host of issues from disease to bad weather and poor soils. These challenges will only become greater as the global climate changes. As a result the agriculture industry is turning to new technology to provide food security in the coming century.
Drones can give growers a bird’s eye view and provide important insights about fields and crops. Drone footage can also be combined with computer vision based AI models to give farmers even more information. However, drone monitoring systems need to be reliable if they are to help improve yields. Image and video annotation adds vital information to visual data and helps AI models to learn.
This blog will look at five specific use cases for drone mounted AI in the agriculture industry. Finally we will identify how developers can get the best training datasets with the help of annotation providers, like Keymakr.
Keeping an eye on plant health
Satellite imagery is often used by farmers to assess the health of their crops. Factors like colouration can show how well crops are growing or if they are affected by disease. However, satellite images can be expensive and hard to access. Drones are comparatively much cheaper and are more convenient to deploy.
AI models use the data from these images to autonomously analyze the health of entire crops. This gives growers vital early warning of developing problems across large areas.
Monitoring field conditions
Another advantage of drones is their ability to work when there is cloud cover or poor weather. Satellites cannot see through thick clouds, further compromising their effectiveness. As a result drones have become an attractive choice for field condition monitoring.
AI systems, trained with annotated image data, can spot areas of elevation, or parts of fields with poor drainage or soil conditions. This vital information helps to protect crops and increase yields.
Planting and seeding
The next step for drone based AI is physically planting seeds autonomously. Drone planting systems could seed large areas quickly and with minimal supervision. This would reduce labor costs for farmers and in the future AI could even improve the accuracy of seeding.
Drones can also easily reach potentially inaccessible areas where larger machinery might struggle. However, for this level of automation to become a reality it is vital that AI developers have access to high quality annotated image data.
Spraying to prevent weeds and pesticides is a necessary part of the growing process. However, it can also present risks to farm workers who may be exposed to dangerous chemicals. Drones, guided by computer vision AI, could take over crop spraying. This would help to keep workers safe whilst securing crops.
AI powered pollination
Pollination is an important part of the growing cycle for many plants, particularly greenhouse plants like tomatoes. However, it can be difficult to accomplish. Traditionally bees are used but they can be hard to access and are even banned from some countries. Small robots can be used to simulate the buzzing of bees (which releases pollen) with small jets of air. AI helps these robots locate the pollen bearing parts of plants.
The data annotation difference
Drones and AI are a powerful combination that could change agriculture for the better. Keymakr supports developers in this sector by giving them access to proprietary annotation technology and a skilled in-house team of annotation professionals.
Contact a team member to book your personalized demo today.