Precision agriculture is an approach to farm management that uses information and technology to identify, analyze, and manage variability in fields by implementing crop production activities at the right location, time, and in the correct procedure for maximum profitability, sustainability, and protect land resources.
Precision agriculture typically entails complex operations that can only be carried out by machines, like:
- Repetitive tasks
- Intensive data collection
- Awareness and Prediction
- Protection and security
Robots are now performing many operations in agriculture. Precision agriculture robotic systems assist in the automation of the farming activities and may have positive impacts in terms of energy, time, and cost savings and an improvement in overall production. Robots are equipped with a range of sensors that allow for collecting important production data like humidity, temperature, soil quality, irrigation, and photos and video of the entire plantation.
Machine vision technology is used in many precision agriculture robotic systems to minimize risks, recognize crops, and even decide when they are ready to be harvested. It allows robots to do weeding, growth monitoring, harvesting, sorting, and packing tasks. Several cameras transmit information to the robot, allowing it to locate and access the crops surrounding it.
Precision agriculture robotic systems are majorly used for:
- Harvesting and picking
- Weed control
- Autonomous mowing, pruning, seeding, spraying and thinning
- Sorting and packing
- Utility platforms
Robotic systems can perform practically anything, from simple monitoring to intelligently adapting to changing environments. As a result, the complexity of their platforms varies.
Level 1: Sensing
They can observe and monitor their environment.
Level 2: Comprehension
They can assess a situation by observing it and applying their knowledge.
Level 3: Execution
They can decipher what they perceive and take the appropriate action.
Level 4: Learning
They can understand, learn, and increase their accuracy.
Market overview of Precision Agricultural Robotic Systems:
The global precision agricultural robotic systems market is estimated to be US$ 8,012.9 Mn in 2022 and is expected to reach US$ 21,875.8 Mn by 2031 at a CAGR of 11.8%.
Key Market Insights:
- Market Share by Component: The hardware segment is estimated to be the most lucrative segment. It is estimated to account for US$ 5,429.5 Mn in 2022 and is expected to register a CAGR of 12.6% during the forecast period.
- Market Share by Type: The outdoor farming segment is estimated to dominate the market. It is projected to account for a revenue share of 77.4% by 2031, with a CAGR of 12.5%.
- Market Share by Application: The field farming segment is estimated to be the most lucrative segment. It is estimated to account for a 36.1% revenue share in 2022 and is expected to register a CAGR of 14.8% during the forecast period.
- Market Share by Region: North America is estimated to be the most lucrative market. It is estimated to contribute 43.7% revenue share in 2022 and is expected to register a CAGR of 10.9% during the forecast period.
Factors driving the growth of this market:
- Labor shortages for farming.
- Rising interest in precision agriculture.
- Rising urbanization and increasing demand for food worldwide.
Benefits of Precision Agricultural Robotic Systems?
- Job Variation: Farming robots can do weeding, sowing, fertilising, and spraying, among other repetitive tasks. Navigation with numerous sensors and AI aids in the faster and more efficient completion of nonlinear tasks.
- Reduced Errors: Programmed Robots make fewer errors than humans. Furthermore, robots can reduce work that is potentially hazardous to people.
- Increased Productivity
- Lower labour costs: Agricultural robots can easily undertake all of the key farming chores, removing the need for human labour. Farmers become more self-sufficient due to not having to rely on manual labour.
- Increased Return on Investment: Agricultural robots boost the return on investment by increasing output yields, making farming a profitable endeavour.
Challenges to adopting robotic systems:
- Requirements for service and maintenance
- Power source requirements
- Specialised skills required to operate the system
- Data management
- Cyber-security threat
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