Fecha de publicación: 25/09/2020
Fuente: WIPO Agriculture Portada
Many countries like India are dependent on agriculture as their primary source of livelihood. India has high proportion of agricultural lands, diverse agro- climate conditions and farming legacy, which encourages cultivation of different crops.Governments have taken many initiatives for the development of agriculture sector and encouraged the farmers to adopt the emerging technologies. In spite of rising demand, emerging technologies and Govt support, no significant improvement in agriculture sector in terms of financial conditions and efficiency. Many research works have been conducted for crop yield prediction based on weather conditions, soil parameters, and previous statistics. These efforts partially succeeded in increasing the crop yield rate but could not give any insight into the crop selection based on market demands. The solution seems to be direct integration with the market and awareness on demand -supply analysis. In this context, we propose a sustainable agriculture model for crop selection, yield prediction and supply chain management using cutting edge technologies like IoT, machine learning and cloud computing. The idea is to bring all the stake holders of agriculture sector into one global platform to maintain the accurate database of agriculture production, their demand, requirements, Govt facilities and export opportunities. In the proposed model, every farmer has to create a user account in the cloud portal and fill the crop details such as crop type and area of the land, water sources etc. before seeding. Soil and weather indicators will be extracted using sensors and uploaded to cloud using IoT. Crop registration helps to estimate the total crop production, expected requirement of fertilizers, pesticides, and other necessities. Local traders, global buyers, experts, and other extension services are also directly integrated into this platform to bring transparency; which will also help in doing market survey. The major outcomes of the proposed model will be: recommendations on crop selection, price estimation, crop yield prediction and expert suggestions on fertilizers, pesticides and new methodologies.