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Increasing Adoption of Precision Agriculture to Spur the Global Geo Analytics AI Market

Geospatial artificial intelligence or GEO AI is considered as a new form of machine learning

HYDERABAD, TELANGANA, INDIA, August 7, 2018 / -- Geospatial Analytics have seamlessly found their applications in a number of applications across governmental, industrial and commercial sectors. The Agriculture sector in particular has been an early adopter of geospatial analytics as an increasing need for improved yield drives the adoption of Geospatial AI.

Critical challenges faced by the agriculture industry include increased demand for agricultural produce, and resource (Land, water) constraints among others. Global population is projected to exceed 9.6 billion by 2050, it will be critical to optimize agricultural production and food supply chains to more efficiently produce and deliver food, fiber and fuel, to meet the growing demand. Factors such as high population growth and major changes in political, economic and social systems have resulted in the increased food demands, which created an urgent need to develop new agricultural technologies and modernize many existing agricultural systems and practices. In such conditions, Geospatial Analytics have found their application in the agriculture industry.

Precision agriculture, also known as precision farming can meet the challenges mentioned above. It is the recent farming technology which utilizes the geographical information for obtaining higher production efficiency, sustainable profitability and better quality products, while minimizing environmental impact. It is a methodology of farm management that relies on data, and data analysis to support the farmer’s decision-making process to yield higher production and profit. Various technologies being used in precision agriculture includes satellite navigation and positioning technology, remote sensing, variable-rate application machinery, and the Internet of Things (IOT) among others. The geospatial analytics market generated revenue of over $40 billion in 2017, as rising integration with business analytics tools drives their adoption. With the rising expanse of big data, there is increasing need for AI tools to generate usable insights from the prevalent data. Thus, there is significant penetration forecast in geospatial analytics for AI tools over the next few years, driven by improving technology.

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The rising integration of technology in the agriculture sector to improve crop yields has led to the increasing deployment of precision farming. This farming is particularly prevalent in the U.S, Mexico and Western European regions, with growth forecast in Australia, China and India over the next few years. Geospatial analytics has been increasingly used for yield estimation, food and security analysis, and other applications in precision farming, in recent years.
The number of IoT units being used in the agriculture industry was observed to be 7.8 million units in 2015, and is expected to reach 16 million units in 2025. Hence, the increasing adoption of IoT technology is about to trigger the applications of geospatial analytics in this industry in the coming years

The data generated by the farms is observed to increase dramatically over the next 20 years. GIS is the tool and technology that handles various spatial databases.  This spatial information technology helps to examine and analyze a wider range of agricultural related resources such as soil, weather, and various socio-economic variables, simultaneously and accurately. This agricultural big data is an essential component of geospatial analytics, and this is about to spur the geospatial analytics AI market globally.

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The increasing adoption of various AI technologies such as deep learning and machine vision in the agriculture industry, is about to spur the growth of Geo Analytics market AI globally. Various machine vision applications in agriculture industry, which includes plant image recognition and the rising demand for continuous monitoring and analyzing crop health, is about to boost the adoption of Geo Analytics technology globally.

Increasing food demands due to high rate of population growth, and major changes in political, economic and social systems have created an urgent need to develop new, and revise many existing agricultural systems and practices. The agricultural sector is witnessing a revolution with rising use of precision farming and other tools to drive the yields. Geospatial analytics in particular, has been used as decision makers at all levels, but need an increasing amount of information to help them understand the possible outcomes of their decisions, and develop plans and policies for meeting the increasing demand of food requirements without damaging the natural resources base. Geospatial analytics AI will drive precision farming forward in the agricultural sector as technology improves, and there continues to be a growing need to feed an ever rising population.
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What can you expect from the report?
The Geospatial Analytics AI Market Report is Prepared with the Main Agenda to Cover the following 20 points:

1. Market Size by Product Categories & Application 11. Demand Analysis (Revenue & Volume)
2. Market trends & Relevant Market Data 12. Country level Analysis
3. Manufacturer Landscape 13. Competitor Analysis
4. Distributor Landscape 14. Market Shares Analysis
5. Pricing Analysis 15. Value Chain Analysis
6. Top 10 End user Analysis 16. Supply Chain Analysis
7. Product Benchmarking 17. Strategic Analysis
8. Product Developments 18. Current & Future Market Landscape Analysis
9. Mergers & Acquisition Analysis 19. Opportunity Analysis
10. Patent Analysis 20. Revenue and Volume Analysis

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1. Americas Market for Geospatial Analytics Artificial Intelligence Market (2018-2023)
2. APAC Market for Geospatial Analytics Artificial Intelligence Market (2018-2023)
3. Europe Market for Geospatial Analytics Artificial Intelligence Market (2018-2023)
4. Water Industry Market for Geospatial Analytics Artificial Intelligence Market (2018-2023)
5. Commercial Market for Geospatial Analytics Artificial Intelligence Market (2018-2023)
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