Smart Agriculture Market Size, Share, Trends, Growth, and Industry Analysis, By Agriculture Type (Precision Farming, Livestock Monitoring, Smart Greenhouse, and Others), By Offering (Hardware, Software, and Services), By Application (Precision Farming Application, Livestock Monitoring Application, Smart Greenhouse Application, and Others), and Regional Insights and Forecast to 2031
global smart agriculture market size was USD 19.75 billion in 2022 and to is predicted reach USD 45.07 billion in 2031, exhibiting at a CAGR of 9.6% during the forecast period.
Smart agriculture, also called precision agriculture, involves incorporating modern technologies into traditional farming methods to improve productivity, efficiency, and sustainability. It encompasses the utilization of advanced sensors, data analytics, and automation to monitor and optimize different aspects of agricultural processes. Through smart agriculture, farmers can make informed decisions based on data regarding irrigation, fertilization, pest control, and crop management. By employing Internet of Things (IoT) devices and remote sensing technologies, farmers can gather real-time data on soil moisture, weather conditions, crop health, and livestock monitoring. This data enables them to optimize resource allocation, reduce waste, minimize environmental impact, and increase yields.
SMART AGRICULTURE MARKET: REPORT SCOPE & SEGMENTATION
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Report Attribute |
Details |
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Estimated Market Value (2022) |
19.75 Bn |
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Projected Market Value (2031) |
45.07 Bn |
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Base Year |
2022 |
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Forecast Years |
2023 - 2031 |
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Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment- By Agriculture Type, By Offering, By Application, & Region |
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Segments Covered |
By Agriculture Type, By Offering, By Application, & Region |
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Forecast Units |
Value (USD Billion or Million), and Volume (Units) |
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Quantitative Units |
Revenue in USD million/billion and CAGR from 2023 to 2031 |
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Regions Covered |
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, and Rest of World |
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Countries Covered |
U.S., Canada, Mexico, U.K., Germany, France, Italy, Spain, China, India, Japan, South Korea, Brazil, Argentina, GCC Countries, and South Africa, among others |
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Report Coverage |
Market growth drivers, restraints, opportunities, Porter’s five forces analysis, PEST analysis, value chain analysis, regulatory landscape, market attractiveness analysis by segments and region, company market share analysis, and COVID-19 impact analysis. |
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Delivery Format |
Delivered as an attached PDF and Excel through email, according to the purchase option. |
Global Smart Agriculture Market Dynamics
Several key factors drive the growth of the smart agriculture market. The escalating global population and increasing demand for food necessitate heightened agricultural productivity, compelling farmers to embrace advanced technologies to maximize crop yields. The imperative for resource optimization fuels the adoption of smart solutions that enable precise management of water and fertilizers, thereby reducing waste and minimizing environmental impact. The burgeoning trend of IoT and interconnected devices facilitates the real-time collection of data on weather conditions, soil moisture levels, and crop health. This wealth of information empowers farmers to make informed decisions based on data and enhance overall farm management practices. Furthermore, government initiatives and policies that promote sustainable agricultural practices and the integration of technology in farming act as significant drivers for market growth.
Global Smart Agriculture Market Drivers
The increasing global population puts pressure on the agricultural sector to enhance food production. Smart agriculture offers the potential to achieve higher yields, mitigate resource scarcity, and ensure sustainable food production to meet the growing demand.
Restraints:
Limited awareness and understanding of smart agriculture technologies among farmers, particularly in developing regions, pose a challenge. Additionally, the lack of necessary skills and technical expertise to implement and utilize these technologies can hinder adoption rates.
Opportunities:
The growing consumer demand for sustainably produced food creates opportunities for smart agriculture solutions. Consumers are increasingly concerned about the environmental impact of agriculture and seek products from farms implementing eco-friendly practices.
Segment Overview
By Agriculture Type
Based on the agriculture type, the global smart agriculture market is segmented into precision farming, livestock monitoring, smart greenhouse, and others. The livestock monitoring segment is dominating the market with the largest revenue share of around 20.5% in 2022. Efficient livestock management is critical for farmers to guarantee animal health, production, and overall farm profitability. Integrating livestock monitoring systems with IoT devices and sensors enables real-time surveillance and analysis of critical factors such as animal behavior, health, and feeding habits. This enables farmers to identify and solve concerns quickly, lowering the risk of disease outbreaks, optimizing feed utilization, and enhancing breeding and reproduction practices. Furthermore, livestock monitoring technologies improve operational efficiency by automating duties such as estrus detection and health monitoring, reducing labor expenses.
By Offering Type
Based on offering type, the global smart agriculture market is segmented into hardware, software, and services. The software segment is anticipated to grow at a higher CAGR of 10.8% during the forecast period. The growth in this area can be credited to multiple factors. One factor is the rising demand for advanced software solutions that enable farmers to effectively analyze and interpret the extensive amount of data gathered from various smart agriculture technologies. These software platforms offer valuable insights, actionable recommendations, and data visualization, empowering farmers to make well-informed decisions to optimize their farm operations. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) algorithms into smart agriculture software significantly enhance its capabilities in predictive analytics, crop modeling, and risk assessment, further augmenting its potential.
By Material Type
Based on the material type, the global smart agriculture market is segmented into precision farming application, livestock monitoring application, smart greenhouse application, and others. The yield monitoring segment is dominating the market with the largest revenue share of around 41.6% in 2022. Accurate monitoring of crop yield is of paramount importance for farmers seeking to optimize crop production, resource allocation, and overall farm profitability. By utilizing yield monitoring solutions, which incorporate advanced sensors and data analytics, farmers gain access to real-time data on crop yield variability across their fields. This valuable information allows them to identify areas with high or low productivity, evaluate the effectiveness of various farming practices, and make informed decisions based on data to enhance both yield and efficiency.
Global Smart Agriculture Market Overview by Region
By Region, the global smart agriculture market has been divided into North America, Europe, Asia-Pacific, and the Rest of the World. North America dominated the market with around 40.2%, of the global market in 2022. The adoption of smart agriculture solutions is facilitated by the region's robust technological infrastructure and advanced farming practices. North America possesses a considerable number of tech-savvy farmers who readily embrace novel technologies and innovations to enhance their agricultural activities. Furthermore, the region benefits from favorable government initiatives and policies that promote sustainable agriculture and the utilization of advanced technologies, thereby bolstering the market. Moreover, the presence of prominent players within the smart agriculture industry and substantial investments in research and development further drives the market growth in the region.
Global Smart Agriculture Market Competitive Landscape
The global smart agriculture market is characterized by the dominance of a few prominent players who have established a strong regional presence and hold significant market share. These key participants are deeply committed to ongoing research and development initiatives, driving innovation in the industry. Moreover, they actively pursue strategic growth endeavors such as product development, launches, joint ventures, and partnerships. Through these strategies, these companies aim to strengthen their market position and expand their customer base, capturing a substantial share of the market.
Some of the major players in the global smart agriculture market include Ag Leader Technology, AGCO Corporation, AgJunction, Inc., AgEagle Aerial Systems Inc., Autonomous Solutions, Inc., Argus Control Systems Ltd, BouMatic Robotic B.V., CropMetrics LLC, CLAAS KGaA GmbH, CropZilla, Deere & Company, DICKEY-john, DroneDeploy, DeLaval Inc., Farmers Edge Inc., Grownetics, Inc., Granular, Inc., Gamaya, GEA Group Aktiengesellschaft, Raven Industries, Trimble Inc., and various other key industry players.
Global Smart Agriculture Market Recent Developments
In October 2022, Trimble Inc. has released the GFX-1060 and GFX-1260 monitors, which are particularly built for precision agriculture applications. These enhanced displays enable farmers to carry out numerous in-field operations more efficiently and successfully. Farmers can accurately capture and analyse field data on the fly thanks to real-time mapping and monitoring capabilities. Next-generation displays improve overall productivity by enabling quick decision-making by giving accurate and up-to-date information.
Scope of the Global Smart Agriculture Market Report
Smart Agriculture Market Report Segmentation
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ATTRIBUTE |
DETAILS |
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By Agriculture Type |
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By Offering |
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By Application |
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By Geography |
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Customization Scope |
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Pricing |
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Objectives of the Study
The objectives of the study are summarized in 5 stages. They are as mentioned below:
To identify and estimate the market size for the global smart agriculture market segmented by agriculture type, by offering, by application, region, and by value (in U.S. dollars). Also, to understand the consumption/ demand created by consumers of Smart Agriculture between 2019 and 2031.
To identify and infer the drivers, restraints, opportunities, and challenges for the global smart agriculture market
To find out the factors which are affecting the sales of smart agriculture among consumers
To identify and understand the various factors involved in the global smart agriculture market affected by the pandemic
To provide a detailed insight into the major companies operating in the market. The profiling will include the financial health of the company's past 2-3 years with segmental and regional revenue breakup, product offering, recent developments, SWOT analysis, and key strategies.
Intended Audience
Research Methodology
Our research methodology has always been the key differentiating reason which sets us apart in comparison from the competing organizations in the industry. Our organization believes in consistency along with quality and establishing a new level with every new report we generate; our methods are acclaimed and the data/information inside the report is coveted. Our research methodology involves a combination of primary and secondary research methods. Data procurement is one of the most extensive stages in our research process. Our organization helps in assisting the clients to find the opportunities by examining the market across the globe coupled with providing economic statistics for each and every region. The reports generated and published are based on primary & secondary research. In secondary research, we gather data for global Market through white papers, case studies, blogs, reference customers, news, articles, press releases, white papers, and research studies. We also have our paid data applications which includes hoovers, Bloomberg business week, Avention, and others.
Data Collection
Data collection is the process of gathering, measuring, and analyzing accurate and relevant data from a variety of sources to analyze market and forecast trends. Raw market data is obtained on a broad front. Data is continuously extracted and filtered to ensure only validated and authenticated sources are considered. Data is mined from a varied host of sources including secondary and primary sources.
Primary Research
After the secondary research process, we initiate the primary research phase in which we interact with companies operating within the market space. We interact with related industries to understand the factors that can drive or hamper a market. Exhaustive primary interviews are conducted. Various sources from both the supply and demand sides are interviewed to obtain qualitative and quantitative information for a report which includes suppliers, product providers, domain experts, CEOs, vice presidents, marketing & sales directors, Type & innovation directors, and related key executives from various key companies to ensure a holistic and unbiased picture of the market.
Secondary Research
A secondary research process is conducted to identify and collect information useful for the extensive, technical, market-oriented, and comprehensive study of the market. Secondary sources include published market studies, competitive information, white papers, analyst reports, government agencies, industry and trade associations, media sources, chambers of commerce, newsletters, trade publications, magazines, Bloomberg BusinessWeek, Factiva, D&B, annual reports, company house documents, investor presentations, articles, journals, blogs, and SEC filings of companies, newspapers, and so on. We have assigned weights to these parameters and quantified their market impacts using the weighted average analysis to derive the expected market growth rate.
Top-Down Approach & Bottom-Up Approach
In the top – down approach, the Global Batteries for Solar Energy Storage Market was further divided into various segments on the basis of the percentage share of each segment. This approach helped in arriving at the market size of each segment globally. The segments market size was further broken down in the regional market size of each segment and sub-segments. The sub-segments were further broken down to country level market. The market size arrived using this approach was then crosschecked with the market size arrived by using bottom-up approach.
In the bottom-up approach, we arrived at the country market size by identifying the revenues and market shares of the key market players. The country market sizes then were added up to arrive at regional market size of the decorated apparel, which eventually added up to arrive at global market size.
This is one of the most reliable methods as the information is directly obtained from the key players in the market and is based on the primary interviews from the key opinion leaders associated with the firms considered in the research. Furthermore, the data obtained from the company sources and the primary respondents was validated through secondary sources including government publications and Bloomberg.
Market Analysis & size Estimation
Post the data mining stage, we gather our findings and analyze them, filtering out relevant insights. These are evaluated across research teams and industry experts. All this data is collected and evaluated by our analysts. The key players in the industry or markets are identified through extensive primary and secondary research. All percentage share splits, and breakdowns have been determined using secondary sources and verified through primary sources. The market size, in terms of value and volume, is determined through primary and secondary research processes, and forecasting models including the time series model, econometric model, judgmental forecasting model, the Delphi method, among Flywheel Energy Storage. Gathered information for market analysis, competitive landscape, growth trends, product development, and pricing trends is fed into the model and analyzed simultaneously.
Quality Checking & Final Review
The analysis done by the research team is further reviewed to check for the accuracy of the data provided to ensure the clients’ requirements. This approach provides essential checks and balances which facilitate the production of quality data. This Type of revision was done in two phases for the authenticity of the data and negligible errors in the report. After quality checking, the report is reviewed to look after the presentation, Type and to recheck if all the requirements of the clients were addressed.
