Fecha de publicación:
Fuente: WIPO Agriculture Portada
When agriculture lands are converted for domestic purposes, it is necessary to revamp the field with the latest technological developments. An ever-growing population is a worrying sign for the industry to meet out the future food requirements. Smart and efficient farming would be the appropriate solution to attain future needs.In Agriculture farming, crop monitoring is a critical phase in the development of the crops cultivated in the experimental land. There may be several issues such as insufficient nutrients, diseases, insects and weeds which can affect the growth of the crop. Timely application of fertilisers will improve productivity and avoid the failure of crop development.The proposed Al-driven unmanned aerial device aims at providing necessary alerts and decisions for the development of the crop cultivated in the agriculture land. The unmanned aerial vehicle is attached with optical sensors which will monitor the crops in the agriculture land. The sensors will provide details about the diseases, weeds, insects that affect the crop and also crop nutrient deficiency. The data will be collected in the cloud environment which will be processed by the web-based Al-driven tool; also it will offer its recommendation for applying fertilisers to the farmers such as the type of fertiliser and amount of fertiliser necessary to grow a particular type of crop. Consequently, each crop needs a different amount and proportion of fertiliser to improve the nutrients for their growth. The proposed tool will provide this information to the farmers on a timely basis. It also provides information about the development phases of the crops cultivated in the agriculture land such as Vegetative, reproductive and ripening.The various information that affects the growth of the crop such as insects, seeds, crop nutrient information will be collected from the sensors as the past history of data. Also, the appropriate decision for the issues like the type of fertiliser and amount of fertiliser for various crops will be taken as training dataset to train the recommender system for various possible issues. The results will be taken into consideration for providing appropriate recommendations to farmers. This tool is expected to provide maximum accuracy on the selected objective and will sure revamp the agriculture industry.