Hi Readers, welcome back to our blog. Today, we are looking at Artificial Intelligence (AI) in autonomous vehicles in Agriculture. The last few decades have brought a decline in the agricultural labour force which poses a challenge in meeting the food demand of an increasing global population. Artificial Intelligence supported Autonomous Vehicles (AVs) can replace or assist human labour and bring about higher levels of productivity and increased efficiency in farming through smart management or precision farming (TerkRecoms - Tech TV, 2021). Precision farming operates on AI, Big Data and Internet of Things (IoT) using a cloud-based planning tool to manage, operate and navigate the machines’ course on the field. From carrying out power demanding tasks like tillage to seeding, weeding, spraying and harvesting, AVs enhance productivity and reduce the need for manual labour (Vijayanand, 2018). The AGXEED AgBot is an autonomous tractor that has allowed farmers to become more efficient and sustainable in conserving natural resources. It reduces soil compaction and enhances its health and nutrient absorption. Composed of high voltage connections, load sensing hydraulics, adjustable track widths and electrical power take-off, the vehicle uses three-dimensional detective sensors, safe positioning, and a Real-Time Kinetic (RTK) steering system operated from different satellites (Racelogic, 2021). The AgroBot E-Series is an electric powered autonomous harvester that uses real-time AI to determine the ripeness of the fruit (AgroBot, 2020). The machine consists of 24 robotic arms equipped with a camera to determine whether or not the harvest matches the standard of quality expected and performs the actions of gripping of the fruit, such as strawberry, and cutting its stem with high precision to prevent damage to the produce. The AgroBot is also equipped with LiDAR to ensure safety for nearby workers and to shut off in the event of an individual crossing the machine’s perimeter. Dino, another electric powered robot, specializes in weeding, removal of large-scale unwanted plants so that crops have sufficient water and nutrients to consume while simultaneously increasing the fertility of the soil. Dino uses deep learning to detect nearby plants, it navigates itself without human intervention, and can perform U-turns using RTK and additional sensors (TerkRecoms - Tech TV, 2021). The machine can detect crops in the field and manage its tools to weed plants as thoroughly as possible. Its operation time is six to eight hours depending on soil conditions and how many tools in the machine are being used concurrently (Karad, Kumar and Shinde, 2020). FarmBot Genesis is a robot that was designed for farmers to grow food. The machine is composed of a tool mount for seed injectors, water spray nozzles and tools to bury seeds. The robot weeds the planted area by using a weed suppressor and a grid-camera which identifies weeds in the operating area. FarmBot Genesis is also used in digital designing of farms where web-based interface known as OpenFarm creates an adult-size crop virtual planting plan (TerkRecoms - Tech TV, 2021). In recent years, AI has successfully supported John Deere's Electric and Case IH tractors. While the former specializes in speed and acceleration, soil protection, manoeuvrability, noise reduction and zero emissions, the latter is intended to be a solution for the declining workforce in agricultural labour which is experiencing a lack of expertise in large farm settings. The vehicle uses an onboard radar which paths the most efficient course in the field while taking into consideration the terrain, nearby objects and machinery on the land using LiDAR and cameras to detect objects in its course along with automated braking when necessary (TerkRecoms - Tech TV, 2021). The Farmdroid FD20, powered by solar energy, has been designed to support farmers for up to 24 hours of daily operations in the control of sowing and weeding by reducing the costs of those two important agricultural processes while maintaining a carbon dioxide neutral approach. GPS technology allows Farmdroid to precisely mark the placement of the seeds during the sowing, clean the area around the plant and possibly eliminate the necessity to manage the weeds. Lastly, since it is not dependant on cameras or even sensors to detect plants, it can successfully perform the weeding even before the crop starts germinating (TerkRecoms - Tech TV, 2021). Once the crops have germinated and achieved a certain growth, DJI Agras takes on the spraying function and applies agricultural solution known as the T30 to reduce the amount of fertilizer used and increase yield while collecting important data on farmlands. With its capacity of 40 litres, the drone can spray the area of 40 acres per hour. Its dual first-person view (FPV) cameras provide the user with a clear front and rear views eliminating the need for the operator to turn the AV mid-flight. Finally, its bright searchlight that enhances the AV’s night vision facilitates its night-time operations and eventually contributes to generating of smart flight paths in the cloud-based farming (TerkRecoms - Tech TV, 2021). In conclusion, the AVs illustrated above not only enhance the precision of the executed tasks, reduce the need for chemical inputs and carbon footprint to the lowest possible levels, but compensate for the lack of an agricultural workforce and reduce drudgery in farm related tasks as well. Stay in touch for more AI in Agriculture news from Brainless Intelligence - AI on our social media channels. REFERENCES AgroBot (2020) Meet the E-Series. Available at: https://www.agrobot.com/e-series [Accessed 5 March 2022]. Karad, S.C., Kumar, P. and Shinde, G.U. (2020) A Review on Sensor Based Robotic Agriculture: Improving Traditional Agriculture Practices. Available at: https://www.researchgate.net/profile/Sachin-Karad-2/publication/357827919_1_st_African_Conference_on_Precision_Agriculture_8-10/links/61e164ac70db8b034c940f9e/1-st-African-Conference-on-Precision-Agriculture-8-10.pdf [Accessed 5 March 2022]. Naïo Technologies (2021) Move Forward With NAÏO Technologies. Available at: https://www.naio-technologies.com/en/home/ [Accessed 5 March 2022]. Racelogic (2021) How does RTK (Real-Time Kinetic) work? Available at: https://en.racelogic.support/VBOX_Automotive/01General_Information/Knowledge_Base/How_Does_RTK_(Real_Time_Kinetic)_Work%3F [Accessed 5 March 2022]. TerkRecoms - Tech TV. (2021) 10 Advanced Autonomous Tractors And Farming Machines (Modern Agricultural Machinery and Robots). Available at: https://www.youtube.com/watch?v=K-FvYZv785U [Accessed 5 March 2022]. Vijayanand, C. (2018) AI in Agriculture. Available at: https://d1wqtxts1xzle7.cloudfront.net/58075474/AI_in_Agriculture-with-cover-page-v2.pdf?Expires=1646578579&Signature=Ey6rjUKmFGXRKJjHKrKRtZKiospU201WDa~I6-vchJy0nuD54sdFqYh8qzM9Mgjpm5ZTkcRkpXeP0SE1USAV8QABn68I3BDYzUHdeIrz1gsO5EH~nqTghqJziNoSmMtHImvXK1lQ5yxi-Ryose1-WpiHlLtebfLWzgDkje8EcUqYSme-Cjb0F4iHtNK~QIJTrh3UjqxApcufUkDhUvDor2wfvijNT6JocqiO8uE1KHBjDDlDAUxDFoQGn6BUVsfqtcSxOH1KRNUVCVA4KwuKrIavZtc-ECf1Kk-GbXopaMqy6QVc1IbK58dF4xTTC5fK4LiLQDMuoPAVWONm1gGfxA__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA [Accessed 5 March 2022]. Zimmer, D., Plaščak, I., Barač, Ž., Jurišić, M. and Radočaj, D. (2021) Application of Robots and Robotic Systems in Agriculture. Available at: https://hrcak.srce.hr/file/381300 [Accessed 5 March 2022].
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