| 1 | Automation and digitization of agriculture using artificial intelligence and internet of things显示文摘The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity.In most of the countries where the expansion of cropland is merely impossible,agriculture automation has become the only option and is the need of the hour.Internet of things and Artificial intelligence have already started capitalizing across all the industries including agriculture.Advancement in these digital technologies has made revolutionary changes in agriculture by providing smart systems that can monitor,control,and visualize various farmoperations in real-time andwith comparable intelligence of human experts.The potential applications of IoT and AI in the development of smart farmmachinery,irrigation systems,weed and pest control,fertilizer application,greenhouse cultivation,storage structures,drones for plant protection,crop health monitoring,etc.are discussed in the paper.The main objective of the paper is to provide an overview of recent research in the area of digital technology-driven agriculture and identification of the most prominent applications in the field of agriculture engineering using artificial intelligence and internet of things.The research work done in the areas during the last 10 years has been reviewed from the scientific databases including PubMed,Web of Science,and Scopus.It has been observed that the digitization of agriculture using AI and IoT hasmatured fromtheir nascent conceptual stage and reached the execution phase.The technical details of artificial intelligence,IoT,and challenges related to the adoption of these digital technologies are also discussed.This will help in understanding how digital technologies can be integrated into agriculture practices and pave the way for the implementation of AI and IoT-based solutions in the farms. | A.Subeesh C.R.Mehta | 2021 | Artificial Intelligence in Agriculture2021，，1： | 4 |
| 2 | A fuzzy logic algorithm derived mechatronic concept prototype for crop damage avoidance during eco-friendly eradication of intra-row weeds显示文摘Crop damage during the intra-row weed eradiation is one of the biggest challenges in intercultural agricultural operations.Several available mechanical systems provide effective weeding but result in excess crop damage.On the other hand,chemical based systems have been raising serious environmental and food concerns.This study presents development of a cost-effectivemechatronic prototype for intra-rowweeding operation.The primary focus was on incurring minimal crop damage.The system integrates time of flight and inductive sensing into fuzzy logic algorithm for electronic control of a four-bar linkage mechanism(FBLM).The crank of FBLM was connected to the vertical rotary weed control shaft with weeding blades.The crop sensing triggers the electronic control to laterally shift the control shaft away from crop,proportional to the forward speed and soil conditions.The developed algorithm incorporates varied conditions of soil,forward speed,and plant spacing to calculate dynamic lateral shift speed(SRPM).The prototype was evaluated to determine the relationships between the operating conditions and electronic control parameters.Moreover,the plant damage was assessed under varied conditions of plant spacing,forward speeds,soil cone index,operational depth and electronic control parameters.The derived SRPM was established as the ultimate governing factor for avoiding crop damage that varied significantlywith electronic response time and soil strength(P<0.05).Plant damage increased significantly under higher forward speeds and lower plant spacing(P<0.05).Preliminary field evaluation of the developed prototype showed a significant potential of this system for effective control on weeds(>65%)and crop damage(<25%). | Satya Prakash Kumar V.K.Tewari Abhilash K.Chandel C.R.Mehta Brajesh Nare C.R.Chethan Kaustubh Mundhada Prateek Shrivastava Chanchal Gupta Smrutilipi Hota | 2020 | Artificial Intelligence in Agriculture2020，，1： | 1 |
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