Technology

Computer Vision Technology Market for Agriculture Global Analysis 2023-2033: Fostering Digital Agriculture through Global Government Initiatives

Published

2 years ago

March 1, 2024

DUBLIN, Feb. 29, 2024 /PRNewswire/ — The “Computer Vision Technology Market for Agriculture: A Global and Regional Analysis, 2023-2033” report has been added to ResearchAndMarkets.com’s offering.

The computer vision technology market for agriculture was valued at $432.0 million in 2023, and it is expected to grow at a CAGR of 16.78% and reach $2,037.5 million by 2033. The computer vision technology market for agriculture is currently in a dynamic growth phase, marked by rapid advancements and heightened adoption. The market exhibits a degree of fragmentation, with diverse players contributing to specialized applications within the agriculture sector.

Key companies such as Climate LLC, Granular, IBM Corporation, Ceres Imaging, and Deere & Company hold notable market shares, indicating a mix of technology-focused startups and established giants collectively shaping the landscape of computer vision solutions in agriculture. As the market matures, consolidation trends may emerge, influencing the competitive dynamics and further fueling the integration of computer vision technologies into modern farming practices. As of 2022, significant players held around 30% of market shares in the computer vision technology market for agriculture. These percentages underscore the influence of these companies in driving innovation and technology adoption in the agricultural sector, reflecting the evolving landscape of precision farming and broader application of computer vision solutions.

The market is characterized by entities offering innovative solutions designed for the following applications such as biotic stress monitoring, harvest dynamic monitoring, autonomous equipment control, and abiotic stress monitoring in agriculture, with a focus on interpreting and extracting valuable insights from visual data captured through various imaging devices. The products offered by the players in the market have been segmented into data processing and analytics and operational integration and automation.

During the forecast period 2023-2033, the computer vision technology market for agriculture is set to undergo substantial evolution and expansion. Persistent advancements in computer vision technologies will drive the development of more sophisticated and cost-effective solutions for analyzing agricultural data. With an increased emphasis on sustainability and adherence to circular economy principles, governments, industries, and consumers will prioritize the integration of computer vision for optimizing farming practices.

A surge in investments directed toward startups specializing in computer vision for agriculture and dedicated research and development initiatives can be expected. This era presents a golden opportunity for the computer vision technology market for agriculture to mature and firmly establish itself as an indispensable component of the sustainable farming landscape. Companies that swiftly embrace technological advancements and foster effective collaborations are poised for significant growth and a leading position in this transformative market.

Market Segmentation

Biotic Stress Monitoring to Dominate the Computer Vision Technology Market for Agriculture (by Application)

Biotic stress monitoring, encompassing disease, pest, and weed detection, stands as a cornerstone in contemporary agriculture, utilizing cameras to capture various growth stages and enhance production efficiency. This approach empowers farmers to swiftly identify subtle abnormalities in crop development caused by factors such as malnutrition, disease, or pest infestation. The integration of advanced computer vision applications, such as Taranis and Blue River Technology, has become integral to modern farming practices. These technologies analyze vast fields with high-resolution imagery and artificial intelligence algorithms, providing real-time insights. This capability enables farmers to make informed decisions, proactively manage issues such as pest infestations, and optimize resource allocation for improved crop health and productivity, ensuring a more sustainable and efficient future for agriculture.

Biotic stress monitoring through computer vision allows providers to swiftly detect and identify plant diseases or pest infestations. This proactive approach enables timely intervention, minimizes crop damage, and increases agricultural productivity. By leveraging real-time data and image analysis, computer vision providers can offer farmers precise and targeted solutions, optimizing resource utilization and contributing to sustainable farming practices. Overall, biotic stress monitoring enhances efficiency and resilience in agriculture.

Data Processing and Analytics to Dominate the Computer Vision Technology Market for Agriculture (by Product)

The data processing and analytics segment in the computer vision technology market for agriculture is rapidly growing and plays a crucial role in modern farming practices. A report on the “Environmental Benefits of Precision Agriculture in the U.S.” highlights that adopting precision agriculture technologies has resulted in avoiding the application of an estimated 30 million pounds of herbicide. Furthermore, there is potential to avoid an additional 48 million pounds of herbicide with broader adoption of precision agriculture. This underscores the importance of raising awareness about the adoption of advanced technologies such as computer vision in agriculture. Such technologies assist farms in identifying and controlling weed growth at an early stage, preventing the unnecessary overuse of herbicides. This not only benefits the environment but also contributes to more efficient and sustainable farming practices.

Data processing and analytics empower computer vision providers by enhancing the accuracy and efficiency of image recognition algorithms. Through the analysis of vast datasets, these providers can refine their models, improving object detection and classification. Real-time processing enables quicker decision-making in applications such as autonomous vehicles and surveillance. Overall, data-driven insights contribute to the continual advancement and optimization of computer vision systems.

In recent years, the use of computer vision technology in agriculture has grown significantly worldwide, with North America leading the way in its adoption. Precision agriculture initiatives, such as automated crop monitoring and yield prediction, have propelled the region to the forefront, reflecting a progressive approach to enhance agricultural efficiency. For example, in 2020, the University of California, Davis, utilized drones equipped with computer vision for a study. It gathered data on crop health and growth, revealing the technology’s ability to detect early signs of disease and pests. This breakthrough resulted in reduced pesticide use and increased crop yields. The integration of automated drone surveillance and AI-driven image analysis tools on farms underscores North America’s dedication to leveraging advanced technologies for enhanced crop management.

The swift adoption of precision agriculture is also driving the growth of the computer vision technology market for agriculture in North American countries. The integration of AI and computer vision in precision farming is proving to be highly beneficial by optimizing planting, irrigation, and fertilization based on real-time data and can bring about significant input cost savings. According to a report from the Precision Agriculture Development Trust published in 2022, precision farming has the potential to boost crop yields by up to 30%, highlighting the substantial positive impact of technology on modern agriculture practices.

Demand – Drivers, Challenges, and Opportunities

Market Drivers: Advancement of Deep Learning Techniques

Deep learning (DL), a pivotal aspect of artificial intelligence, harnesses artificial neural networks (ANNs) to glean insights from vast datasets and execute diverse tasks. Particularly impactful in computer vision (CV), which pertains to the interpretation and processing of visual information, DL’s applications in agriculture are extensive.In this sector, it facilitates tasks such as crop monitoring, autonomous harvesting, weather analytics, animal health tracking, and plant disease diagnosis.For CV technology providers in agriculture, DL brings multifaceted advantages. It enhances model accuracy and complexity by assimilating insights from extensive data, reducing the risk and cost of crop failures through weather and soil condition analysis, and maximizing crop yield and quality by identifying diseases and optimizing harvesting.

Market Challenges: Navigating Data Ownership and Privacy Challenges

The integration of artificial intelligence (AI) and computer vision in farming and breeding relies heavily on processing data from remote sensors, UAVs, and satellites. While many farmers embrace digitalization, some hesitate to share data due to the lack of clear legal frameworks on issues such as ownership, privacy, cybersecurity, and liability. Some companies have unlawfully shared farm data, raising concerns about data privacy among farmers.The major stakeholders in agricultural data include farmers, agricultural technology providers, input companies, and governments. Computer vision adoption raises concerns about data exposure and identity disclosure to hackers. A survey by the American Farm Bureau Federation revealed that over 75% of farmers worry about data ownership and potential regulatory use, while 60% fear companies influencing market decisions using their agricultural data.

Market Opportunities: Fostering Digital Agriculture through Global Government Initiatives

Government initiatives to promote digital agriculture encompass public-private partnerships and the establishment of a supportive environment for companies, be they established or startups, to introduce computer vision-based products. Notably, the U.S. Department of Agriculture has launched diverse programs leveraging computer vision in agricultural facets such as production, food supply chain, sensor development, ecosystem management, and rural community support. Robotic solutions for tasks such as pollination, pesticide application, weeding, and harvesting are also promoted. The American Research Service collaborates with companies to integrate computer vision and AI in livestock monitoring, irrigation analysis, robotic harvesting, and drone-based crop health monitoring.In India, the state government of Karnataka entered a memorandum of understanding (MoU) with Microsoft in 2007, aiming to enhance agricultural productivity through innovative technologies, primarily computer vision. The Indian government further partnered with IBM to deploy the AI-based Watson Decision Platform for Agriculture, offering accurate weather forecasts and soil information to empower local farmers in making informed decisions on crop and water management. This trend is anticipated to proliferate globally, fostering increased opportunities in the IoT-driven agriculture industry.

Key Market Players and Competition Synopsis

Some of the prominent companies in this market are:

Climate LLCGranular Inc.IBM CorporationCeres ImagingDeere & CompanyProspera TechnologiesAgEagle Aerial Systems Inc (MicaSense)TaranisPrecisionHawk, Inc.GamayaPlantixDJIIteris, Inc.CropIn Technology SolutionsHIPHEN (SlantRange, Inc.)

Segmentation by Application

Biotic Stress MonitoringHarvest Dynamic MonitoringAutonomous Equipment ControlAbiotic Stress Monitoring

Segmentation by Product

Data Processing and AnalyticsOperational Integration and Automation

Segmentation by Region

North America: U.S. and CanadaEurope: France, Germany, Spain, Italy, Belgium, Bulgaria, Ukraine, U.K., and Rest-of-EuropeAsia-Pacific: China, India, Japan, Australia and Rest-of-Asia-PacificLatin America: Brazil and MexicoMiddle East and Africa: Turkey, South Africa, and Rest-of-Middle East and Africa

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

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SOURCE Research and Markets

Technology

Bloomberg Introduces Spread-to-Benchmark Quoting for EUR and GBP Portfolio Trading Baskets

Published

13 hours ago

June 2, 2026

LONDON, June 2, 2026 /PRNewswire/ — Bloomberg today announced the launch of Spread-to-Benchmark quoting and trading for Euro (EUR) and Sterling (GBP) denominated portfolio trades through its Portfolio Trading Basket Builder (PTBB). The new functionality expands the range of quoting protocols available for European credit portfolio trading and reflects growing client demand for spread-based execution workflows, alongside increased dealer support for the convention across EUR and GBP markets.

Spread-to-Benchmark quoting is a well-established protocol for USD credit portfolio trades and is used by market participants to evaluate and execute portfolio trades. By extending this workflow to EUR and GBP portfolio trades, Bloomberg enables clients and dealers to transact using a familiar spread-based methodology across additional credit markets.

The introduction of Spread-to-Benchmark quoting for EUR and GBP baskets reflects increased client interest in evaluating portfolio trades through a spread-based lens and the growing adoption of spread-based execution workflows in European credit markets. The workflow provides market participants with an additional framework for assessing the relationship between credit spread risk and underlying government bond yields when pricing and executing portfolio trades.

Additional Workflow Flexibility 
The workflow complements Bloomberg’s existing portfolio trading capabilities, which support the full range of market-standard quoting conventions, including Price, Yield, Spread-to-Benchmark and Spread based workflows that reference Bloomberg’s evaluated pricing service (BVAL). This gives clients flexibility to compare and execute portfolio trades using the quoting methodology that best aligns with their investment objectives, execution preferences and internal risk management processes.

“European credit clients continue to look for execution workflows that reflect how they evaluate risk and monitor portfolio trading outcomes,” said Harry Street, Global Head of Credit and Equities Trading Product at Bloomberg. “By expanding dealer support for Spread-to-Benchmark quoting for EUR and GBP baskets, Bloomberg is broadening the range of workflow options available to clients trading European credit portfolios.”

“Portfolio trading workflows in fixed income continue to become more sophisticated as institutional investors look for ways to evaluate execution quality in changing market conditions,” said Kevin McPartland, Head of Market Structure & Technology Research at Crisil Coalition Greenwich. “Spread-based quoting helps market participants more clearly distinguish between the impacts of credit spread and underlying rates movements when determining how best to execute a portfolio trade.”

Bloomberg’s Electronic Markets solutions are used by leading financial institutions to trade efficiently in over 175 markets around the world. More than 9,000 client firms use Bloomberg Electronic Markets to access industry-leading depth and breadth of liquidity across asset classes from over 800 dealers globally. Bloomberg Electronic Markets provides market participants with comprehensive solutions across the trading lifecycle, including robust price transparency, analytics, automation and execution, powered by Bloomberg’s high-quality, multi-asset class data and tools.

About Bloomberg
Bloomberg is a global leader in business and financial information, delivering trusted data, news, and insights that bring transparency, efficiency, and fairness to markets. The company helps connect influential communities across the global financial ecosystem via reliable technology solutions that enable our customers to make more informed decisions and foster better collaboration. For more information, visit Bloomberg.com/company or request a demo.

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SOURCE Bloomberg L.P.

Technology

Dr. Sunho Kang, a senior battery-technology executive with leadership experience at major global battery and EV manufacturers, joins TeraWatt Technology as Head of Product and Technology

Published

13 hours ago

June 2, 2026

SAN FRANCISCO, June 2, 2026 /PRNewswire/ — TeraWatt Technology Inc. (Headquartered in California, USA) is pleased to announce that Dr. Sunho Kang has joined the company as Head of Product and Technology.

Dr. Kang is a globally recognized battery-technology executive with more than 25 years of leadership experience spanning the United States, Asia, and Europe, and a distinguished track record of advancing innovations from laboratory research through gigafactory-scale production. He has held senior executive positions at world-leading organizations including Samsung SDI, Apple, and Volkswagen Group of America, and brings deep expertise in lithium-ion battery materials, cell engineering, and product industrialization across a broad range of applications, including electric vehicles and energy storage systems.

At TeraWatt, Dr. Kang will lead global product development and the commercialization of TeraWatt’s battery technology platform, aiming to accelerate the delivery of TeraWatt’s competitive products as well as the technology and commercialization roadmap including manufacturing scale-up.

Dr. Kang commented:

“I am thrilled to join TeraWatt Technology as Head of Product and Technology. TeraWatt’s innovative battery platform presents a tremendous opportunity to push the boundaries of lithium-ion technology, and I look forward to working with the team to accelerate product development and commercialization to deliver meaningful impact.”

TeraWatt Technology founder CEO Ken Ogata, Ph.D. commented:

“We are thrilled to welcome Dr. Kang as our Head of Product and Technology. His deep expertise in battery materials, cell engineering, and productization will be instrumental in accelerating TeraWatt’s product roadmap and technology leadership. Together with Dr. Kang, we will continue to drive our mission forward.”

About TeraWatt Technology Inc.
TeraWatt Technology Inc. is a California-based company that produces lightweight, high-power, and safe next-generation lithium-ion batteries.

Company Overview
Name: TeraWatt Technology Inc.
Representative: Co-founder and CEO Ken Ogata
Headquarters: 28 Geary St, Suite 650, San Francisco, CA 94108, United States
Founded: January 2020
Established: December 2019
URL: https://www.terawatt-technology.com/

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SOURCE TeraWatt Technology Inc.

Technology

Tencent Cloud and Soniox Announce Strategic Partnership: Combining Advanced Speech-to-Text (STT) Technology with Global Real-Time Infrastructure

Published

13 hours ago

June 2, 2026

HONG KONG, June 2, 2026 /PRNewswire/ — Tencent Cloud, the cloud business of global technology company Tencent, today announced a strategic partnership with Soniox, a San Francisco-based speech AI company that specializes in developing high-accuracy, low-latency speech AI solutions. The collaboration integrates Soniox’s speech-to-text (STT) technology with Tencent Cloud’s Real-Time Communication (TRTC) enterprise-grade global infrastructure, enabling enterprises to build and deploy multilingual voice AI applications across 200+ countries and regions.

Elevating Enterprise Voice AI at a Global Scale

In enterprise voice AI deployments, latency directly affects user experience and application reliability. The integration of Soniox’s high-accuracy, low-latency STT with TRTC’s global transmission infrastructure reduces latency across the entire pipeline, creating a comprehensive end-to-end solution for enterprises deploying conversational AI applications worldwide.

Soniox is the voice platform for every language. Unlike legacy speech AI, which was built primarily for English-speakers, Soniox delivers native-speaker accuracy across 60+ languages. Its technology can handle mid-sentence language switching — a user can switch between English and Chinese in a single utterance, and Soniox will capture every word with complete accuracy. All of this works through a single API that works for both speech-to-text and text-to-speech.

By integrating TRTC, the partnership leverages an enterprise-grade real-time communication backbone featuring more than 3,200 global nodes, sub-300 ms worldwide latency, and advanced capabilities such as AI noise suppression and weak-network resilience. These capabilities enable conversational AI applications to operate reliably across diverse network environments, including regions such as Southeast Asia and Africa.

With the roll out of this partnership, developers can integrate the Soniox STT API directly within the Tencent Cloud console. Whether targeting English-speaking markets or supporting languages such as Arabic, Hindi, and Malay, enterprises can build global voice applications — including intelligent customer service, voice assistants, real-time translation, and meeting transcription — to address the demands of expansion into emerging markets and multilingual scenarios.

Wison Xie, Head of Product at Tencent RTC, stated: “Tencent RTC has always been committed to providing reliable real-time communication infrastructure for global enterprises. Our partnership with Soniox brings together our strengths in enterprise-grade audio transmission and Soniox’s advanced speech recognition technology. Together, we are making it easier for businesses to deploy accurate, low-latency voice AI applications across any language and any market.”

Klemen Simonic, CEO at Soniox Inc., stated “At Soniox, our mission is to help businesses understand every word, in any language, with native speaker accuracy and exceptional speed. Partnering with Tencent Cloud combines our speech AI with world-class real-time infrastructure, enabling enterprises to build voice AI experiences that scale globally with low latency and reliability.”

About Tencent Cloud:

Tencent Cloud, one of the world’s leading cloud companies, is committed to creating innovative solutions to resolve real-world issues and enabling digital transformation for smart industries. Through our extensive global infrastructure, Tencent Cloud provides businesses across the globe with stable and secure industry-leading cloud products and services, leveraging technological advancements such as cloud computing, Big Data analytics, AI, IoT, and network security. It is our constant mission to meet the needs of industries across the board, including the fields of gaming, media and entertainment, finance, healthcare, property, retail, travel, and transportation.

About Tencent RTC:

Tencent RTC provides real-time communication solutions, including audio/video calling, live streaming, and in-game voice. With enterprise-grade security, AI-powered enhancements, and a global network of over 3,200 nodes, Tencent RTC powers mission-critical communication for customers worldwide.

About Soniox:

Soniox is a next-generation voice AI company bringing about the end of English-first speech AI. Most people on the planet did not grow up speaking English and often mix languages mid-sentence; and yet legacy speech AI was built for just English. Soniox is different: native-speaker accuracy across 60+ languages, true mid-sentence language switching, and flawless alphanumeric recognition that legacy providers still can’t match. For developers building global apps, Soniox is the only option. Try it for yourself at soniox.com.

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SOURCE Tencent Cloud