Global Journal of Computer Science and Technology, G: Interdisciplinary, Volume 23 Issue 1

Applications of Emerging Smart Technologies in Farming Systems: A Review © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue I Version I 63 ( )G Year 2023 crops, and determine which crops are best suitable for their particular parcel of land. The potential advantages and challenges have been thoroughly explained in this paper. Overall, India's current smart technology application scenario is promising. To empower farming community meaningfully, further robust research, development, and policy decisions are desperately needed to address the issues preventing the seamless adoption of smart ICT applications in farming systems. R eferences R éférences R eferencias 1. Patel R & Pate M (2013). Application of Cloud Computing in Agricultural Development of Rural India ‖ , International Journal of Computer Science and Information Technologies , Vol. 2 (6) 922-926. 2. Gill Sukhpal Singh, Chana Intervener, Buyya Rajkumar (2017). IoT based agriculture as a cloud and big data service: the beginning of digital India . Journal of Organizational and End User Computing (JOEUC) 29 (4) 1-23. 3. Choudhary Vipin Kumar, Kumar Sunil, Meena Laxman Ram, Kumar Anil, Panwar Sanjeev, Mishra Dev Raj and Thakur Bhawesh Kumar (2019). Design and Implementation of Web-based Information System for Region-Specific Synthesized Integrated Farming Models in India. International Journal of Applied Research on Information Technology and Computing (IJARITAC) 10 (1) 9-19. 4. Kumar Prakash, Kumar Anil, Panwar Sanjeev, Dash Sukanta, Sinha Kanchan, Chaudhary Vipin Kumar and Ray Mrinmoy(2018). Role of big data in agriculture - A statistical prospective. Annals of Agricultural. Research . New Series Vol. 39 (2): 210- 215. 5. Kumar Sunil, Shamim M, Panwar A.S, Bhaskar S, Naresh R.K., Singh Prem, Kashyap Poonam, Mishra Devraj, Choudhary Vipin, GhasalP.C. and Chaudhary Jairam (2018). Computational modeling for pigeon pea yield prediction in an integrated farming system Journal of Food Legumes 31(1) 58- 62. 6. Barrios Abraham Gastélum, Escamilla-García Axel, Toledano-Ayala Manuel and others (2020). Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development . Applied Sciences 10 (11) 3835. 7. Choudhary, Vipin Kumar (2016). Cloud Computing and its Applications: A Review International Journal of Emerging Trends & Technology in Computer Science. ISSN 2278-6856 5 (4) 20-27. 8. Pandia, Amit (2014). Advanced Applications of Neural Networks and Artificial Intelligence: A Review International Journal of Innovative Science, Engineering & Technology, (2) 57-61. 9. Abderahman Rejeb, Alireza Abdollahi, Karim Rejeb, Horst Treiblmaier (2022). Drones in agriculture: A review and bibliometric analysis, Computers and Electronics in Agriculture, 198 107017. 10. Kurkute S. R., Deore B. 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Kamber, Data Mining: Concepts and Techniques , (2006) 2nd ed., Morgan Kaufmann Publisher, ISBN 1-55860-901-6. 20. Bagal Yash V. Pednekar, Shivam V., Pandey Ashutosh R., Dhamdhere Tanmay B. Data Mining in Agriculture-A Novel Approach , (2020). International Journal of Engineering Research & Technology (IJERT) ISSN: 2278–0181, Vol. 9 Issue. 21. Choudhary Vipin Kumar, Thakur Bhawesh Kumar, Kumar Anil, Panwar Sanjeev (2013). An Implementation Of Preprocessing Concept On Web Log Data Files For Web Usage Mining. AARJMD Volume 1 ISSUE 16 ISSN: 2319 – 2801.