A STUDY OF AUTOMATION'S IMPACT IN AGRICULTURE
DOI:
https://doi.org/10.29121/shodhkosh.v5.i4.2024.1735Keywords:
Agriculture, Automation, TechnologyAbstract [English]
Agriculture automation serves as a sole concern for every country and proves to be a vital factor for the economic development as portrayed by Mahatma Gandhi rightly as the Backbone of the country . Unlike industrial developments observed like industry 4.0 agricultural developments are claimed as Agriculture 4.0 by incorporating smart agriculture. Due to the increase in the population size need for food emerged as the primary want for people globally. The production made by the farmers through traditional means were inadequate to serve the needs of the society. Smart agricultural methods focused on two premium aspects one being agricultural production and Traditional methods practised by farmers are not adequate to aid the cumulative claim and they have to hinder the mud by using detrimental pesticides in an exaggerated way. The agricultural technology has been adopted to reduce labour intensiveness and time consuming process. Few problems related to agriculture are low productivity, volatility in the price of food, hesitation in adopting new farming trends, water management, types of pollution etc. Automation of farming practices has proved to increase the gain from the soil and also has strengthened the soil fertility. Pertaining to the need for automation and to know the impact of automation in agriculture this study was propagated. The primary data was used to collect data with the help of a well-structured questionnaire. Snowball sampling method was adopted as it was very difficult to identify the respondents who used automatised agriculture in their farms. Results of the study provided a positive sign that the respondents were satisfied in adopting the automation in agriculture.
References
Haule, J., & Michael, K. (2014). Designing and simulation of an automated irrigation management system deployed by using wireless sensor networks (WSN). IOSR Journal of Electronics and Communication Engineering, 9(5), 67–73. https://doi.org/10.9790/2834-09526773 DOI: https://doi.org/10.9790/2834-09526773
Koul, S. (2021). Machine learning and deep learning in agriculture. Smart Agriculture, 1–19. https://doi.org/10.1201/b22627-1 DOI: https://doi.org/10.1201/b22627-1
Liakos, K., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A Review. Sensors, 18(8), 2674. https://doi.org/10.3390/s18082674 DOI: https://doi.org/10.3390/s18082674
The Automation Advantage: Embrace the Future of Productivity and Improve Speed, Quality, and Customer Experience Through AI” - Bhaskar Ghosh, PhD.
“Agriculture Automation and Control” – https://www.springer.com/series/15728, www.wikipedia.com , www.investopedia.com.
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Copyright (c) 2024 M. Rajesh, Dr. M. Vidya

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