reuters.com
Can AI-Powered Agriculture Robots Disrupt
the $78 Billion Pesticide Industry?
Curated by
cdteliot
5 min read
141
According to recent reports, AI-powered agricultural robots equipped with advanced technologies like laser weed elimination and precision spraying are emerging as potential disruptors to the $78 billion pesticide industry. These intelligent machines use artificial intelligence and computer vision to identify and target weeds with unprecedented accuracy, potentially reducing the need for widespread chemical herbicide use on farms.
AI Robots Revolutionize Farming
mindy-support.com
In California, the scent of burnt weeds rose through the air as more than 200 farmers, engineers, and researchers gathered to witness something unprecedented. The "Weed Spider" and "Mantis" flew over rows of romaine lettuce with ease, revealing the power of what is possible with the combination of AI and robotics
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. One of the larger agricultural robots, a 9,500-pound robot that relies on deep learning called "LaserWeeder", explored a crop identifying weeds in real-time and then eliminating them with 30+ powerful lasers. It's so precise that so far it's doing wonders to keep the crops safe and healthy3
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. According to Tim Mahoney, one of the reps for the Seattle-based company Carbon Robotics is more than certain their robot is a game changer. "It's a hurdle for people to get over, but the numbers don't lie…this is the future."2
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A Deep Dive Into How AI and Robotics Work in the Fields
futurefarming.com
The integration of AI and robotics in the world of agriculture is driven by a handful of key components that work together to enhance its efficiency, speed, and overall sustainability. This includes advanced AI algorithms that work in tandem with robotic platforms that are tied to sensors and actuators that live on a robot
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. The "Weed Spider" and "LaserWeeder" are AI robots that have been actualized thanks to vast amounts of data that have been collected within the crops they've been training in. The data is captured by a mix of cameras and sensors. The images are processed by computer vision algorithms so they can identify various types of plants, weeds, pests, animals, and other materials found along the way3
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. Deep learning models are continually trained on extensive datasets, which enables the robots to see specific patterns and objects that may change over time within a specific crop. Like all AI models, they will improve over time. Then, in real-time, the robots can make precise interventions, including weed removal. Furthermore, robots may even be able to identify diseases and pest infestations within the crops and help farmers take timely action5
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Another key in this scenario is data analytics, which can lead to even further optimizing crops. For example, the robots can do things like measuring moisture levels, letting farmers know what crop yields will be, forecasting when the next pest outbreak will be, and so much more7
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. As data and insights are presented to the AI model, farmers can make more proactive decisions, save money over time, and inspire healthier plants.8 sources
How AI Robots Sensors and Actuators Work
realpars.com
A growing number of sensor and actuator types are being currently released to the market, including LIDAR and RADAR sensors. They have the power to offer 3D mapping of the environment they are exposed to, which gives ai-equipped robots the ability to work within complex environments and terrains with ease
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. They also help render field maps that are accurate and essential for the robots delivering a body of work with minimal errors. GPS and RTK (Real-Time Kinematic) systems are also at work providing positing data and revealing whether robots can navigate to various locations within an environment3
. For example, when a robot works to pull weeds or seed a crop, it's quite obvious that they must be precise or risk failure. As mentioned above, environmental sensors are also important so that robots can measure important data like temperature, humidity, and soil moisture4
. In doing so, the data gathered will help robots make the right decisions at the right times. And finally, AI robotics relies on connectivity and data management. This means that they have to communicate with centralized systems and data centers. Failure to connect to the cloud can be disastrous, which is why Edge computing plays a vital role, as it reduces latency and enables real-time decision-making as the robots work throughout the day5
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Can We Say Goodbye to Harmful Chemicals Altogether?
therobotreport.com
California is leading the way with AI and robotics for farming because of the state's desire to look deeper into health hazards related to herbicides and pesticides. This includes working to rid crops of glyphosate (i.e. RoundUp), paraquat, dacthal, and other agents used to control weeds and insects and is linked to some pretty scary health risks, including cancer, kidney issues, Parkinson's, asthma, birth defects, and more
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. Assembly Bill 1963 is an attempt to ban paraquat in the State of California. Additionally, the California Department of Pesticide Regulation has released a roadmap that began in 2022 and will continue through 2050 that will result in healthier alternatives for pest management and eventually ban harmful chemicals altogether1
. Another reason AI-based robotics are becoming more of a reality is that there are very few new, more healthy pesticide options being brought to the market. Strict regulations and high costs have halted innovation, inspiring other options that may be more effective in the long run. A growing number of farms are showing interest in LaserWeeder, as Carbon Robotics are moving on average one unit per week for $1.4 million per unit. So far, it's been reported that the robot can take out up to 200k weeds every hour, which also outpaces manual labor2
. This, of course, is causing concerns for the labor market. "This weeder is an example of replacing human labor with mechanical labor," said Barbara Meister of Salinas Inclusive Economic Development Initiative. "So for us, we're thinking about, does this technology enhance labor, replace labor, or create new job opportunities? The answer to this question for a growing number of farms, think tanks and government officials is that AI and Robotics in farming can be likened to the mechanical tomato harvester and other similar tools introduced in the 1950s. They displaced thousands of farm jobs, but then also worked to help the food industry progress for the greater good of humanity. "We need more efficiencies in agriculture to improve profit margins and be able to pay workers in the field more, but it's ultimately going to displace some people," said Chris Benner, director of the Institute for Social Transformation at US Santa Cruz. "What do we do, in that context, to support people who need new training for other types of jobs?"2 sources
The Path Forward
futurefarming.com
As California moves toward robotics in agriculture, there is a mix of optimism and concern for what will become of it all. On one hand, robotics may help pave the way for a healthier way for human beings to consume food, and on the other, they may displace workers who desperately need jobs.
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Where AI technology and intelligent robots are concerned, they are already showing signs of being viable. Of course, numerous hoops need to be jumped through, machine learning improvements, and pricing adjustments for there to be mass adoption.2
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As for the pesticide industry, they too are looking into how robots can help better distribute their products within crops, both speeding up the spraying process and applying them to plants with more precision. They assert that while pesticides may be on the chopping block in California, many other states will continue to welcome their products with open arms.3
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Related
How will robotics impact the future of pesticide use in agriculture
What are the potential job losses in agriculture due to robotics adoption
How do robotics improve the efficiency of crop spraying
What are the main challenges in implementing agricultural robotics
How does machine learning enhance the capabilities of agricultural robots
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