Smart Farming: Big Data and Digital Agriculture
Manish Kumar
, Dr. (Prof.) Deva Prakash
Agriculture, Agriculture Industry, Precision Agriculture, Gross Domestic Product, Precision Agriculture, IOT, Smart Farming, Big Data, Big Data Analytics
The last several years have seen robust expansion in the agriculture industry. The industry, which employs the most people, contributed a significant 18.8% (2021–2022) of the country's Gross Value Added (GVA), growing by 3.6% in 2020–2021 and 3.9% in 2021–2022. The main factors influencing the sector's overall growth have been expansion in related industries including cattle, dairying, and fishing. The Indian economy's cornerstone is its agricultural sector, which accounts for 15% of the country's Gross Domestic Product (GDP). More crucially, over half of India's population depends entirely or heavily on agriculture and related industries for a living. There are already over 7 billion people on the earth, and by 2050, that number is projected to increase to 9.6 billion.1 By 2030, there may be 5 billion people in the middle class, who typically have more money to spend on food, driving up demand.2 The present world population is 7.7 billion, and the United Nations predicts that number to increase to 8.5 billion by 2030 and 9.7 billion by 2050. 3 If these figures are accurate, the world's food supply will need to double in a relatively short amount of time to keep up with demand and feed everyone on the planet.4 The good news is that cutting-edge digital technologies now make it feasible to gather and use enormous volumes of important data for little or no expense, making a farm's field activities more insight-driven and possibly more effective and productive. The ecosystem for agriculture is already beginning to invest in these digital technologies. Between 2014 and 2020, the market for digital services, also referred to as "precision agriculture," is anticipated to reach $4.55 billion, growing at a CAGR of 12.2 percent.5 Utilization of precision agricultural services is essential to meeting the growing population's food needs as well as enhancing a farm's financial performance. Although an advance over conventional approaches, the impact of precision agricultural solutions, such as variable-rate spraying, has, up until recently, been constrained by the granularity and timeliness of the data they use and the absence of operational decision support on a day-to-day basis.5 Big Data, which affects the entire supply chain, is anticipated to have a significant impact on smart farming. Smart sensors and devices provide enormous volumes of data (Big Data) that enable unprecedented decision-making capabilities. Significant changes in power dynamics between traditional and non-traditional players are anticipated as a result of big data. Big data necessitates the use of a variety of novel integration-capable techniques and technologies in order to extract insights from extremely large, diverse, and complicated information6. Big Data refers to information assets with such large volume, velocity, and variety that their conversion into value requires specialized technology and analytical techniques7.
"Smart Farming: Big Data and Digital Agriculture", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 12, page no.151 - 158, December-2017, Available :https://ijsdr.org/papers/IJSDR1712021.pdf
Volume 2
Issue 12,
December-2017
Pages : 151 - 158
Paper Reg. ID: IJSDR_203112
Published Paper Id: IJSDR1712021
Downloads: 000347040
Research Area: Engineering
Country: -, -, -
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
