Global Artificial Intelligence (AI) in Agriculture Market 2019-2024 - Agricultural Drones Set to Drive the Market

DUBLIN, Dec. 2, 2019 /PRNewswire/ -- The "Artificial Intelligence (AI) Market in Agriculture - Growth, Trends, and Forecast (2019 - 2024)" report has been added to ResearchAndMarkets.com's offering.

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The artificial intelligence (AI) market in agriculture is expected to register a CAGR of over 21.52%, during the forecast period of 2019-2024.

Driverless tractor is trending in market as these tractor can steer automatically using GPS-based technology, lift tools from the ground, recognize the boundaries of a farm, and can be operated remotely using a tablet. A fleet of smaller automated tractors could lift farmer revenue by more than 10 percent and can reduce farm labor costs.

Key Highlights

    --  Maximize crop yield using machine learning technique is driving the
        market. Species selection is a tedious process of searching for specific
        genes that determine the effectiveness of water and nutrients use,
        adaptation to climate change, disease resistance, as well as nutrients
        content or a better taste. Machine learning, in particular, deep
        learning algorithms, take decades of field data to analyze crops
        performance in various climates and based on this data one can build a
        probability model that would predict which genes will most likely
        contribute a beneficial trait to a plant.
    --  Increase in the adoption of cattle face recognition technology is
        driving the market. Through the application of advanced metrics,
        including cattle facial recognition programs and image classification
        incorporated with body condition score and feeding patterns, dairy farms
        are now being able to individually monitor all behavioral aspects in a
        group of cattle.
    --  Increase use of Unmanned Aerial Vehicles (UAVs) across agricultural
        farms is driving the market as the use of drones in the agriculture
        industry can be use in crop field scanning with compact multispectral
        imaging sensors, GPS map creation through onboard cameras, heavy payload
        transportation, and livestock monitoring with thermal-imaging
        camera-equipped drones, which increases the demand of UAVs.
    --  However, lack of standardization is restraining the market growth as
        lack of standards in data collection, and lack of data sharing is high,
        and machine learning and artificial intelligence and advanced algorithm
        design have moved so fast, but the collection of well-tagged, meaningful
        agricultural data is way behind.

Market Trends

Agricultural Drones to Drive the Growth of Market

    --  As global population projected to reach over 9 billion by 2050,
        agricultural consumption is expected to increase by a massive 70%, where
        drones have now been mainstreamed for smart farming assisting farmers in
        a range of tasks from analysis and planning to the actual planting of
        crops, and the subsequent monitoring of fields to ascertain health and
        growth.
    --  Drones equipped with hyperspectral, multispectral, or thermal sensors
        are able to identify areas that require changes in irrigation. Once
        crops have started growing, these sensors are able to calculate their
        vegetation index, and indicator of health through AI, by measuring the
        crop's heat signature.
    --  No one likes the idea of chemical spraying, but, for the time being,
        it's a necessary part of large-scale agriculture. Fortunately, smart
        farming drones are helping reduce its environmental impact. Specialized
        UAVs (Unmanned aerial vehicle) are equipped with sprayers, with various
        kinds of technology, like ultrasonic echoing devices and lasers, which
        can measure distance with extreme precision. The result is a massive
        reduction in overall spray and a much lower chemical level reaching the
        groundwater.
    --  Agrobotix LLC is a drone enabled software company that provides quality
        imaging and data analysis for sustainable and precision agriculture, and
        is supporting over more than 53 crops, including corn, grape, apple,
        sugarcane, and so on for sustainable and precision farming across 50
        countries. AgEagle Aerial Systems (firm who acquired Agrobotix LLC) is
        planning to develop new products with new technologies, such as weather
        data, advanced image recognition, and precise analysis, to provide
        better recommendation to the farmers/consumers using it.

Europe Expected to Account for the Largest Market Growth

    --  Farmers manage almost half of the European land area, making agriculture
        a dominant industry in Europe. Trend in monitoring and reporting tools
        for indoor and outdoor farms, and providing a visualization of the
        farmer's entire production using computer vision and artificial
        intelligence is increasing the AI market in agriculture.
    --  Row crop cultivation is done by AI in various countries in Europe, where
        robot uses 20x less herbicide due to its accuracy for weeding of row
        crops.
    --  The European Soil Data Centre (ESDAC) is the thematic centre for soil
        related data in Europe, where its ambition is to be the single reference
        point for and to host all relevant soil data and information at European
        level. AI firms are managing 'Internet of the Soil', which is a software
        and hardware solution for monitoring soil conditions like humidity,
        temperature, electrical conductivity, and more in European countries.
        Their sensors connect wirelessly to a cloud-based platform where it can
        be accessed by any internet-connected device.
    --  Berlin-based InFarm has developed a vertical indoor farming system using
        IoT, Big Data, and cloud analytics, that can be implemented in
        supermarkets, restaurants, local distribution warehouses, or even
        schools, allowing businesses to grow their own fresh produce on site to
        deliver to customers. It is already opening indoor farms in 1,000
        locations in Germany, and expanding in other European markets, which
        increases the AI in agriculture market.

Competitive Landscape

The AI market in agriculture is fragmented, as a number of players supplying same product on lower-cost make market competition stiff. Also technological advancements by players and high presence of local and regional players pose a major threat in a price-sensitive market. Key players are Microsoft Corp., IBM Corp. (NITI Aayog), Agribotix LLC, etc.

Recent developments in the market are:

    --  June 2019 - XAG, a Chinese firm, presented its innovative solutions of
        combining drones with AI and IoT technology to achieve precision
        agriculture and induce transformational changes to the food system in
        3rd AI for Good Global Summit, in Geneva. XAG is driving AI-powered
        intelligent devices such as drones and sensors to establish digital
        farming infrastructure in rural areas and enable precision agriculture
        which, for example, accurately target pesticides, seeds, fertilizers and
        water to wherever it is needed.
    --  April 2019 - Yara and IBM Services joined forces to innovate and
        commercialize digital agricultural solutions that will help increase
        global food production. Yara and IBM will develop digital solutions that
        empower professional and smallholder farmers to optimize farming
        practices to increase yields, crop quality, and incomes in a sustainable
        way. The partnership will focus on all aspects of farm optimization and
        apply AI, machine learning, and in-field data to unlock new insights for
        farmers, specifically in the area of weather data, where weather company
        will provide hyperlocal weather forecasts with real-time actionable
        recommendations tailored to the specific needs of individual
        fields/crops.

Key Topics Covered

1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Maximize Crop Yield Using Machine Learning technique
4.3.2 Increase in the Adoption of Cattle Face Recognition Technology
4.3.3 Increase Use of Unmanned Aerial Vehicles (UAVs) Across Agricultural Farms
4.4 Market Restraints
4.4.1 Lack of Standardization in Data Collection
4.5 Value Chain Analysis
4.6 Industry Attractiveness - Porter's Five Force Analysis

5 TECHNOLOGY SNAPSHOTS

6 MARKET SEGMENTATION
6.1 By Application
6.1.1 Weather Tracking
6.1.2 Precision Farming
6.1.3 Drone Analytics
6.2 By Deployment
6.2.1 Cloud
6.2.2 On-premise
6.2.3 Hybrid
6.3 Geography
6.3.1 North America
6.3.2 Europe
6.3.3 Asia-Pacific
6.3.4 Rest of the World

7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 Microsoft Corporation
7.1.2 IBM Corporation
7.1.3 Granular Inc.
7.1.4 aWhere Inc.
7.1.5 Prospera Technologies Ltd.
7.1.6 Gamaya S.A.
7.1.7 ec2ce
7.1.8 PrecisionHawk Inc.
7.1.9 Cainthus Corp.
7.1.10 Tule Technologies Inc.

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS

For more information about this report visit https://www.researchandmarkets.com/r/c9cmiu

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