Outlook on the IoT in Agriculture Global Market to 2026 – Featuring Accenture, AgEagle and Cattle Watch Among Others

Press Releases

May 27, 2021

DUBLIN, May 27, 2021 /PRNewswire/ — The “IoT in Agriculture Market by Technology, Automation (Robots, Drones, and Smart Equipment), Sensor Types, Hardware, Software and Solutions 2021 – 2026” report has been added to ResearchAndMarkets.com’s offering.

This report assesses the technologies, companies, and solutions for IoT in agriculture. The report evaluates the overall marketplace and provides forecasts for sensors (and other devices), services, solutions, and data analytics globally, and regionally for the period 2021 to 2026. Forecasts include precision agriculture, indoor farming, livestock, and fisheries.

Forecasts cover IoT in agriculture solutions globally and regionally including: Intelligent Farm Equipment, Smart Sensor Systems, Intelligent Drones, Smart Farm Robots, and Software. Within the Smart Sensor area, the report forecasts the following: Sensors for Detecting Physical Properties, Sensors for Chemical Analysis and Applications, Sensors for General Monitoring, Sensors for Quality, Sensors for Autonomous Agriculture, and others.

Select Report Findings:

The largest IoTAg application by revenue is monitoring, which will reach $6.99 billion globally by 2026
The fastest growing IoT solution area by revenue is automation, which will grow at a CAGR of 63.8% through 2026
The market for smart sensor systems will reach $2.48 billion globally by 2026, growing at a CAGR of 66.0% through 2026
The global market for agriculture drones will reach $1.12 billion by 2026 with an average price of $1,250 per unit for UAVs
Intelligent solutions for aquaculture operations will $980 million globally by 2026, which we see as a significantly underserved market
The implementation of combined AI and IoT solutions for agriculture will provide a substantial lift for both operational efficiency and effectiveness

There is currently an acute need for greater agricultural efficiency and effectiveness in the week of the recent pandemic. Many agricultural commodities such as corn, soy, and cotton are in backwardation as of the publication of this report, which means that the current price of an underlying asset is higher than prices trading in the futures market. This is atypical for commodities as inflation generally tends to make their price increase over time.

However, recent labor shortages due to the COVID-19 pandemic, coupled with an uptick in economic activity associated with economies reopening after the initial pandemic shut-downs, has led to supply chain discontinuities and resulting unbalanced supply and demand dynamics. This is reflected in the Bloomberg Agriculture Spot Index, which measures the price movements of agricultural commodities, has risen from 227.38 on May 15th, 2020 to a recent high of 386.47 on April 23rd, 2021, representing a 70% increase in a little more than one year.

While the aforementioned commodity price and supply challenges represent a more near-term acute issue, there remain longer-term structural market drivers for improvements in agricultural technologies. As the world population grows, so does the demand for food. The UN estimates that Earth will need to produce 70% more food by 2050 to support these growing populations. Complicating matters, natural resources are slowly being depleted and usable agricultural land is shrinking.

There is an ever-increasing need for intelligent and highly scalable agriculture solutions. Increasingly, the agriculture business is becoming controlled by companies that are not conventional agriculture experts. The publisher sees a shift from conventional agriculture to farm management. With this shift, software developers and predictive data analytics companies will take control of end-to-end agricultural operations.

Agriculture has transformed in the last few decades from small to medium farming operations to highly industrialized, commercial farming that is concentrated among a few large corporations. However, as various Internet of Things (IoT) technologies mature beyond the R&D phase and go into general production, costs for everything from drones/UAVs to sensors will continually decrease, making connected agriculture more accessible to smaller farms and third world countries.

With this agricultural transformation, farming operations are increasingly a highly mechanized and computer-driven operation. This allows corporations to treat agriculture like manufacturing in the sense that measurements, data, and control is very important to manage costs, maximize yields, and boost profits. This shift in managing agricultural operations will bring various benefits to farming and livestock management, including enhanced crop quality and quantity, improved use of resources and farm equipment, real-time monitoring of farms, animals, and machines, automated irrigation systems, fertilizer spraying, and pest control.

The general term, AgriTech, represents the use of technology in agriculture, horticulture, and aquaculture for purposes of improving yield, efficiency, and profitability. The commercial agriculture industry is rapidly becoming one of the most IoT data-driven markets. With the emergence of M2M, IoT, and advanced data analytics technologies, data is becoming available that was previously uncollectible. The application of various AgriTech analytics tools and methodologies, such as predictive analytics will provide substantial enhancements to agriculture operations.

IoT in Agriculture (IoTAg) represents a more specific use of technology wherein agricultural planning and operations becomes connected in ways previously impossible if it were not for advances in sensors, communications, data analytics, and other areas. Virtually every aspect of agriculture that can be automated, digitally planned, and managed will benefit from IoT technologies and solutions.

Accordingly, we see IoTAg fundamentally transforming the way agricultural operations and farms are managed, which will bring various benefits to farming, including enhanced crop quality and quantity; improved use of resources and farm equipment; real-time monitoring of farms, animals, and machines; and automated irrigation systems, fertilizer spraying, and pest control.

The implementation of IoTAg is intended to facilitate greater agricultural efficiency and effectiveness. Essentially, IoTAg solutions, coupled with artificial intelligence and a few other supporting technologies, enable smart agriculture. IoTAg solutions provide many intelligent agriculture benefits such as increase of yields, monitoring crops, automating operations, and reducing waste.

IoT technologies allow farmers and ranchers to enhance productivity. For example, if part of the irrigation system malfunctions, sensors can provide alerts, allowing the problem to be addressed in a timely fashion. These technologies also allow agricultural staff to view operational conditions from anywhere and make changes with real-time solutions.

Illustrative examples of smart agriculture solutions include the following:

Greenhouse Automation: With IoT and sensors, greenhouses can be almost entirely automated. Real-time data on greenhouse conditions, including temperature, lighting, soil condition, and humidity, can be examined and modified automatically. Users can input desired parameters, and automation systems adjust the ecosystem to match them.
Cattle Monitoring/Management: IoT sensors can be attached to animals to monitor and record their health. These solutions can collect data on livestock health, well-being, and location. Sensors can identify sick animals quickly, allowing farmers to separate them from the herd and reduce the spread of contagion. These sensors also save farmers cost in staffing expenses while making better use of their time.
Harvesting Robotics: Agribots are being used to harvest crops, helping to fill the void of workers. These bots can pick fruits and vegetables 24/7, using robotic arms and digital image processing to do so. Companies can control the quality of their products better by utilizing these bots, as they determine when to harvest based on programmed parameters.

Key Topics Covered:

1 Executive Summary

2 Overview

3 IoT in Agriculture Market Dynamics

4 IoT in Agriculture Market Analysis and Forecasts 2021 – 2026

5 IoT in Agriculture Vendor Analysis
5.1 Smart Agriculture Vendor Ecosystem
5.2 IoT in Agriculture Vendor Strategies
5.3 Select Smart Agriculture Solutions
5.3.1 Accenture
5.3.2 AgEagle
5.3.3 Cattle Watch
5.3.4 Monsanto (Bayer)
5.3.5 Decagon (METER Environment)
5.3.6 Deepfield Robotics (Bosch)
5.3.7 DroneDeploy
5.3.8 FarmersEdge
5.3.9 IBM
5.3.10 Euravka
5.3.11 FluxFarm Inc.
5.3.12 John Deere
5.3.13 Kaa Open Source IoT Platform
5.3.14 Libelium Comunicaciones Distribuidas S.L.
5.3.15 MTN
5.3.16 SWIM
5.3.17 SlantRange
5.3.18 Telit
5.3.19 PTC
5.3.20 TopCon
5.3.21 Intrinsyc Technologies Corp
5.3.22 Raven Industries
5.3.23 Semtech
5.3.24 Trackit

6 Appendix One: IoT Data Analytics

7 Appendix Two: Additional Company Analysis
7.1 AG Leader Technology
7.2 AGCO Corporation
7.3 AgJunction Inc.
7.4 Agribotix
7.5 Amber Agriculture
7.6 Antelliq Corporation
7.7 Arable
7.8 Atos
7.9 aWhere
7.10 Bext360
7.11 C2M
7.12 Caterpillar
7.13 Cisco Systems, Inc.
7.14 CNH Industrial
7.15 Connecterra
7.16 CropMetrics LLC
7.17 Decisive Farming
7.18 Deere and Company
7.19 Delaval, Inc.
7.20 Dickey John
7.21 E-peas
7.22 Everynet
7.23 Farmers Edge, Inc.
7.24 Fasal
7.25 GEA Farm Technology
7.26 Hitachi, Ltd
7.27 IBM
7.28 Intel Corporation
7.29 Komatsu Forest AB
7.30 Lely
7.31 Libelium
7.32 Lindsay Corporation
7.33 Monsanto
7.34 NTT DoCoMo
7.35 OnFarm Systems Inc.
7.36 Plenty
7.37 Ponsse
7.38 Precision Hawk
7.39 Pycom
7.40 Raven Industries, Inc.
7.41 Scriptr
7.42 SemiosBIO Technologies
7.43 Semtech Corporation
7.44 Skylo Technologies
7.45 SlantRange, Inc.
7.46 Spectrum Technologies, Inc.
7.47 SST Development Group Inc.
7.48 Swift Navigation
7.49 TeeJet Technologies
7.50 Telit
7.51 The Climate Corporation
7.52 Tigercat
7.53 Topcon Positioning Systems
7.54 Treemetrics
7.55 Trimble Inc.
7.56 UpTake Networks