Challenges and Opportunities for Deep Learning Applications in Industry 4.0

Applications of AI in Agriculture

Author(s): Taranjeet Singh*, Harshit Bhadwaj, Lalita Verma, Nipun R Navadia, Devendra Singh, Aditi Sakalle and Arpit Bhardwaj

Pp: 181-203 (23)

DOI: 10.2174/9789815036060122010011

* (Excluding Mailing and Handling)

Abstract

AI based applications are used for farm-based advisories regarding sprays, forecasting, usage of drones within the farms, infrastructure for humidity and temperature updates to the farmers, etc. Thanks to this, the losses of farmers have begun to decline. Therefore, considering the aims of the government regarding doubling the farmers’ income, the losses of the farmers must be minimized using AI practices. AI intervention has the potential to boost the social and economic well-being of farmers within the medium to long run. The adoption of AI is useful in agriculture as it can bring industrial revolution and explosion in agriculture to feed the growing human population of the world. The study highlights that AI based farm advisory systems are playing an immense role in solving the problems of the farmers by enabling them to require proactive decisions on their respective farms. Various applications of Artificial Intelligence (AI in harvesting, plant disease detection, pesticide usage, AI based mobile applications for farmer support etc.) have been discussed in this survey in detail. Finally, the overview of Deep Learning and its application in agriculture is given.


Keywords: Agriculture, Artificial Intelligence, Deep Learning, Machine Learning, Pretrained Models, Transfer Learning.

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