Challenges and Opportunities for Deep Learning Applications in Industry 4.0

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

DOI: 10.2174/9789815036060122010011

Applications of AI in Agriculture

Pp: 181-203 (23)

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Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

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.

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