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The Indo-US Science and Technology Forum launched the US India Artificial Intelligence Initiative on March 17 to foster the science and technology relationship between the two countries.

The Secretary of the Department of Science and Technology, Prof Ashutosh Sharma, said the Indo-US relationships in science and technology go way back and have significantly benefited both countries.

Analytics India Magazine spoke with geopolitics experts to understand what to expect from the initiative and how India will benefit from the partnership.

AI and other emerging technologies play a vital role in modern geopolitics.

Technology is underpinning the future of relations between nations, said Abishur Prakash, geopolitical futurist at the Centre for Innovating the Future, in Canada, For India, the new AI-initiative with the US could result in breakthroughs or collaboration in areas like defence or healthcare. India and Russia adopted a similar model to develop the BrahMos cruise missile. Similarly, India and Finland are exploring 6G. This is the new geopolitical paradigm governments are working with.

Its still early days for AI in India. But, there is a clear desire to improve Indo-US cooperation in the field of emerging technologies.

AI will be deployed like a tool across sectors, but India hasnt set clear priorities, and it is difficult to predict, said Arindrajit Basu, Program Manager at the Centre for Internet & Society. What we can predict is that it is far easier to have a collaboration on capacity building, R&D, exchange on scientific information, securing supply chains rather than getting on to consensus on norms that will govern AI.

There is clearly a desire for greater Indo-US cooperation in the field of emerging technology. This has been made clear through bi-lateral and multilateral initiatives, which include specific agreements to emerging tech like the USIAI or GPAI respectively and agreements that have to do with general security, like the Quad, which also has a focus on emerging tech, he added.

India and the US can complement each other in this collaborative effort to ensure equitable progress.

For the US, India represents a massive consumer market and one of the worlds largest troves of data. Technology firms in the US accessing this data will be like energy firms finding oil in the Middle East, said Prakash.

For India, the US algorithms are solutions to a variety of development challenges India faces, from bringing banking to hundreds of millions of people to modernising the Indian military to offering healthcare to the masses. At the same time, for US technology firms, India churns out massive amounts of engineers and computer scientists critical talent that these firms need.

Another major reason for a partnership between India and the US is the new geopolitical realities. Chinas growing influence in the field of AI is a pressing concern.

What India and the US bring to the table is what is a supposedly democratic governance model of emerging technology, said Basu, Despite the change in administration from Trump to Biden, there are certain things where there is continuity like distrust in China and Chinese technology. There is a clear desire to ensure that supply chains are governed by standards, rules, and norms of the democratic world.

Both countries are leveraging AI and other emerging technologies to improve their relationships and gain a geopolitical edge.

The US and India are at a place where they both need each other. For the US, it needs allies like India to take on China. And India needs technology and support from the US to rise in the world. It is a win-win situation, said Prakash, Because technology is defining geopolitics, both sides are turning to AI to grow closer. This is the beginning of the West, bringing India into its technology orbit. And, it is the beginning of India moving away from its non-aligned position because of Next Geopolitics.

Experts believe AI and emerging technologies will define relationships between countries. India should look for further opportunities to use its potential and establish its footprint in AI and emerging technology.

This is the model going forward. That is, technology is how nations will build their ties. One region that India may be doubling-down on is Southeast Asia. This region is becoming a hotbed of competition between the major powers of the world, said Prakash

India could use the AI-forum with the US as a testbed to understand what works. With this knowledge, India could then take its own algorithms to Southeast Asian nations, creating an AI-corridor and a new kind of geopolitical power. Of course, this could also happen through QUAD or even the Five Eyes (if India joins).

At the same time, it is also essential to establish safeguards to protect Indian citizens from exploitative data practices of the US or other major economies.

While we dont want to get into a regulatory tussle, we also want to ensure that the interests of our citizens are protected, said Basu, Proactive regulation that protects data privacy; prevents inequitable mergers, anti-competitive practices, and competition law; guarantees free and fair taxation of these companies are the first step.

Simultaneously, if we regulate in a manner that is uncertain, excessive, and counterproductive to these companies, we risk losing investment and opportunities for collaboration. A partnership of this nature will hopefully ensure that various stakeholders come to the table and ensure that regulation is fair in a manner that protects the rights of citizens, while businesses are not severely impacted, he added.

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What To Expect From The New US-India Artificial Intelligence Initiative - Analytics India Magazine

Dublin, March 22, 2021 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Supply Chain Management Market by Technology, Processes, Solutions, Management Function (Automation, Planning and Logistics, Inventory, Risk), Deployment Model, Business Type and Industry Verticals 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report provides detailed analysis and forecasts for AI in SCM by solution (Platforms, Software, and AI as a Service), solution components (Hardware, Software, Services), management function (Automation, Planning and Logistics, Inventory Management, Fleet Management, Freight Brokerage, Risk Management, and Dispute Resolution), AI technologies (Cognitive Computing, Computer Vision, Context-aware Computing, Natural Language Processing, and Machine Learning), and industry verticals (Aerospace, Automotive, Consumer Goods, Healthcare, Manufacturing, and others).

This is the broadest and detailed report of its type, providing analysis across a wide range of go-to-operational process considerations, such as the need for identity management and real-time location tracking, and market deployment considerations, such as AI type, technologies, platforms, connectivity, IoT integration, and deployment model including AI-as-a-Service (AIaaS). Each aspect evaluated includes forecasts from 2021 to 2026 such as AIaaS by revenue in China. It provides an analysis of AI in SCM globally, regionally, and by country including the top ten countries per region by market share.

The report provides an analysis of leading companies and solutions that are leveraging AI in their supply chains and those they manage on behalf of others, with an evaluation of key strengths and weaknesses of these solutions. It assesses AI in SCM by industry vertical and application such as material movement tracking and drug supply management in manufacturing and healthcare respectively. The report also provides a view into the future of AI in SCM including analysis of performance improvements such as optimization of revenues, supply chain satisfaction, and cost reduction.

Select Report Findings:

Modern supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. Supply Chain Management (SCM) solutions are typically manifest in software architecture and systems that facilitate the flow of information among different functions within and between enterprise organizations.

Leading SCM solutions catalyze information sharing across organizational units and geographical locations, enabling decision-makers to have an enterprise-wide view of the information needed in a timely, reliable and consistent fashion. Various forms of Artificial Intelligence (AI) are being integrated into SCM solutions to improve everything from process automation to overall decision-making. This includes greater data visibility (static and real-time data) as well as related management information system effectiveness.

In addition to fully automated decision-making, AI systems are also leveraging various forms of cognitive computing to optimize the combined efforts of artificial and human intelligence. For example, AI in SCM is enabling improved supply chain automation through the use of virtual assistants, which are used both internally (within a given enterprise) as well as between supply chain members (e.g. customer-supplier chains). It is anticipated that virtual assistants in SCM will leverage an industry-specific knowledge database as well as company, department, and production-specific learning.

AI-enabled improvements in supply chain member satisfaction causes a positive feedback loop, leading to better overall SCM performance. One of the primary goals is to leverage AI to make supply chain improvements from production to consumption within product-related industries as well as create opportunities for supporting "servitization" of products in a cloud-based "as a service" model. AI will identify opportunities for supply chain members to have greater ownership of "outcomes as a service" and control of overall product/service experience and profitability.

With Internet of Things (IoT) technologies and solutions taking an ever-increasing role in SCM, the inclusion of AI algorithms and software-driven processes with IoT represents a very important opportunity to leverage the Artificial Intelligence of Things (AIoT) in supply chains. More specifically, AIoT solutions leverage the connectivity and communications power of IoT, along with the machine learning and decision-making capabilities of AI, as a means of optimizing SCM by way of data-driven managed services.

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction2.1 Supply Chain Management2.1.1 Challenges2.1.2 Opportunities2.2 AI in SCM2.2.1 Key AI Technologies for SCM2.2.2 AI and Technology Integration

3.0 AI in SCM Challenges and Opportunities3.1 Market Dynamics3.1.1 Companies with Complex Supply Chains3.1.2 Logistics Management Companies3.1.3 SCM Software Solution Companies3.2 Technology and Solution Opportunities3.2.1 Leverage Artificial Intelligence (AI)3.2.1.1 Integrate AI with Existing Processes3.2.1.2 Integrate AI with Existing Systems3.2.2 Integrate AI with Internet of Things (IoT)3.2.2.1 Leverage AIoT Platforms, Software, and Services3.2.2.2 Leverage Data as a Service Providers3.3 Implementation Challenges3.3.1 Management Friction3.3.2 Legacy Processes and Procedures3.3.3 Outsource AI SCM Solution vs. Legacy Integration

4.0 Supply Chain Ecosystem Company Analysis4.1 Vendor Market Share4.2 Top Vendor Recent Developments4.3 3M4.4 Adidas4.5 Amazon4.6 Arvato SCM Solutions4.7 BASF4.8 Basware4.9 BMW4.10 C. H.Robinson4.11 Cainiao Network (Alibaba)4.12 Cisco Systems4.13 ClearMetal4.14 Coca-Cola Co.4.15 Colgate-Palmolive4.16 Coupa Software4.17 Descartes Systems Group4.18 Diageo4.19 E2open4.20 Epicor Software Corporation4.21 FedEx4.22 Fraight AI4.23 H&M4.24 HighJump4.25 Home Depot4.26 HP Inc.4.27 IBM4.28 Inditex4.29 Infor Global Solutions4.30 Intel4.31 JDA4.32 Johnson & Johnson4.33 Kimberly-Clark4.34 L'Oreal4.35 LLamasoft Inc.4.36 Logility4.37 Manhattan Associates4.38 Micron Technology4.39 Microsoft4.40 Nestle4.41 Nike4.42 Novo Nordisk4.43 NVidia4.44 Oracle4.45 PepsiCo4.46 Presenso4.47 Relex Solution4.48 Sage4.49 Samsung Electronics4.50 SAP4.51 Schneider Electric4.52 SCM Solutions Corp.4.53 Splice Machine4.54 Starbucks4.55 Teknowlogi4.56 Unilever4.57 Walmart4.58 Xilinx

5.0 AI in SCM Market Case Studies5.1 IBM Case Study with the Master Lock Company5.2 BASF: Supporting smarter supply chain operations with cognitive cloud technology5.3 Amazon Customer Retention Case Study5.4 BMW Employs AI for Logistics Processes5.5 Intelligent Revenue and Supply Chain Management5.6 AI-Powered Customer Experience5.7 Rolls Royce uses AI to safely transport its Cargo5.8 Robots deliver medicine, groceries and packages with AI5.9 Lineage Logistics Company Case Study

6.0 AI in SCM Market Analysis and Forecasts 2021 - 20266.1 AI in SCM Market 2021 - 20266.2 AI in SCM by Solution 2021 - 20266.2.1 Platforms6.2.2 Software6.2.3 AI as a Service6.3 AI in SCM by Solution Components 2021 - 20266.3.1 Hardware6.3.1.1 Non-IoT Device6.3.1.2 IoT Embedded Device6.3.1.2.1 Security Devices6.3.1.2.2 Surveillance Robots and Drone6.3.1.2.3 Networking Devices6.3.1.2.4 Smart Appliances6.3.1.2.5 Healthcare Device6.3.1.2.6 Smart Grid Devices6.3.1.2.7 In-Vehicle Devices6.3.1.2.8 Energy Management Device6.3.1.3 Components6.3.1.3.1 Wearable and Embedded Components6.3.1.3.1.1 Real-Time Location System (RTLS)6.3.1.3.1.2 Barcode6.3.1.3.1.3 Barcode Scanner6.3.1.3.1.4 Barcode Stickers6.3.1.3.1.5 RFID6.3.1.3.1.6 RFID Tags6.3.1.3.1.7 Sensor6.3.1.3.2 Processors6.3.2 Software6.3.3 Services6.3.3.1 Professional Services6.4 AI in SCM by Management Function 2021 - 20266.4.1 Automation6.4.2 Planning and Logistics6.4.3 Inventory Management6.4.4 Fleet Management6.4.5 Virtual Assistance6.4.6 Freight Brokerage6.4.7 Risk Management and Dispute Resolution6.5 AI in SCM by Technology 2021 - 20266.5.1 Cognitive Computing6.5.2 Computer Vision6.5.3 Context-aware Computing6.5.4 Natural Language Processing6.5.5 Predictive Analytics6.5.6 Machine Learning6.5.6.1 Reinforcement Learning6.5.6.2 Supervised Learning6.5.6.3 Unsupervised Learning6.5.6.4 Deep Learning6.6 AI in SCM by Industry Vertical 2021 - 20266.6.1 Aerospace and Government6.6.2 Automotive and Transportation6.6.3 Retail and Consumer Electronics6.6.4 Consumer Goods6.6.5 Healthcare6.6.6 Manufacturing6.6.7 Building and Construction6.6.8 Others6.7 AI in SCM by Deployment 2021 - 20266.7.1 Cloud Deployment6.8 AI in SCM by AI System 2021 - 20266.9 AI in SCM by AI Type 2021 - 20266.10 AI in SCM by Connectivity6.10.1 Non-Telecom Connectivity6.10.2 Telecom Connectivity6.10.3 Connectivity Standard6.10.4 Enterprise6.11 AI in SCM Market by IoT Edge Network 2021 - 20266.12 AI in SCM Analytics Market 2021 - 20266.13 AI in SCM Market by Intent Based Networking 2021 - 20266.14 AI in SCM Market by Virtualization 2021 - 20266.15 AI in SCM Market by 5G Network 2021 - 20266.16 AI in SCM Market by Blockchain Network 2021 - 20266.17 AI in SCM by Region 2021 - 20266.17.1 North America6.17.2 Asia Pacific6.17.3 Europe6.17.4 Middle East and Africa6.17.5 Latin America6.18 AI in SCM by Country6.18.1 Top Ten Country Market Share6.18.2 USA6.18.3 China6.18.4 Canada6.18.5 Mexico6.18.6 Japan6.18.7 UK6.18.8 Germany6.18.9 South Korea6.18.10 France6.18.11 Russia

7.0 Summary and Recommendations

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

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Insights on the Artificial Intelligence in Supply Chain Management Global Market to 2026 - Integration of AI with Internet of Things Presents...

SAN DIEGO, March 22, 2021 /PRNewswire/ --CamerEye() is reinventing swimming pool safety by introducing the first Artificial Intelligence (A.I.) Pool Smart Fence and safety ecosystem to provide faster distress and near-drowning detection to help save lives. https://www.camereye.ai

Residential pool development has rapidly been growing since the pandemic. With pool fun comes safety issues. There are more than 3,500 annual fatal unintentional drowning-related accidents in the U.S. alone and 15 percent more drowning related accidents have occurred since the COVID-19 pandemic.

Pool safety is coming under increasing regulatory scrutiny, with government regulatory standards and mandates requiring pool owners to have layers of pool safety and security.

"We understand the problem of pool safety and the notion of distress and drowning using life-guarding principles,which can help us solve the problem in a much informed way," says Sai Reddy, Founder and CEO of CamerEye, who was a competitive swimmer and holds a PhD in A.I. and data sciences. "Drowning occurs in various stages. CamerEye offers that layer of safety with very early stage detection when there is unauthorized entry around the pool's perimeter with our A.I. Smart Fence and is able to detect early distress behavior using A. I. technology."

The CamerEye A.I. Smart Fence and safety ecosystem for residential pools uses sophisticated and highly trained and adaptive artificial intelligent technology through overhead cameras. CamerEye excels at eliminating or reducing false detections due to its human detection capabilities ruling out pool toys, leaves and non-human items. It also offers faster and better distress detection alerts within 10 seconds, allowing for quicker critical response time.

CamerEye's smart system empowers pool owners to:

This affordable and easy-to-install overhead camera system keeps pool owners always connected and informed of their pool safety while providing another eye on their pool for peace of mind.

"Having fun in and around your pool should be a cherished lifestyle activity and not a liability," adds Reddy. "With our team's combined expertise in water sports and A.I., we want to make the world a safer place, and help people live their best life by providing peace of mind and helping to reduce risk."

Pricing is $799 MSRP with a free 3-month trial premium monitoring subscription for initial users. Monitoring subscription starts $12.99 per month after the first 3 months and includes a one-year warranty extension with each renewal. The basic subscription is $12.99 per month and premium subscription is $19.99 per month with automatic software upgrades. Live phone, chat and email support are included.

Learn more at https://www.camereye.ai. CamerEye is also seeking pool builders and service dealers for all territories. Call (800) 906-2810 or email [emailprotected] for more information.

Contact:Michele Moninger Baker858-449-3619[emailprotected]

SOURCE CamerEye

http://www.camereye.ai

Original post:
CamerEye Introduces First Artificial Intelligence Smart Fence and Pool Safety Ecosystem for Faster Distress and Near-Drowning Detection to Help Save...

The year 2020 may have been one of turmoil and uncertainty across the globe, but artificial intelligence remained on a steady course of growth and further exploration -- perhaps because of the Covid-19 crisis. Healthcare was a big area for AI investment, and concerns about diversity and ethics grew -- but little action has been taken. Most surprisingly of all, while AI job growth accelerated across the world, it flattened in the US.

These are among the key metrics of AI tracked in the latest release of theAI Index, an annual data update from Stanford University'sHuman-Centered Artificial Intelligence Institute. The index tracks AI growth across a range of metrics, from degree programs to industry adoption.

Here are some key measures extracted from the 222-page index:

AI investments rising: The report cites a McKinsey survey that shows the Covid-19 crisis had no effect on their investment in AI, while 27% actually reported increasing their investment. Less than a fourth of businesses decreased their investment in AI.

AI jobs grow worldwide, flatten in the US:Another key metric is the amount of AI-related jobs opening up. Surprisingly, the US recorded a decrease in its share of AI job postings from 2019 to 2020-the first drop in six years. The total number of AI jobs posted in the US also decreased by 8.2% from 2019 to 2020, from 325,724 in 2019 to 300,999 jobs in 2020. This may be attributable to the mature market in the US, the report's authors surmise. Globally, however, demand for AI skills is on the rise, and has grown significantly in the last seven years. On average, the share of AI job postings among all job postings in 2020 is more than five times larger than in 2013. In 2020, industries focused on information (2.8%); professional, scientific, and technical services (2.5%); and agriculture, forestry, fishing, and hunting (2.1%) had the highest share of AI job postings among all job postings in the US.

AI investment in healthcare increased significantly:The product category of "drugs, cancer, molecular, drug discovery" received the greatest amount of private AI investment in 2020, with more than $13.8 billion, 4.5 times higher than 2019, the report states. "The landscape of the healthcare and biology industries has evolved substantially with the adoption of machine learning," the report's authors state. "DeepMind's AlphaFold applied deep learning technique to make a significant breakthrough in the decades-long biology challenge of protein folding. Scientists use ML models to learn representations of chemical molecules for more effective chemical synthesis planning. PostEra, an AI startup used ML-based techniques to accelerate COVID-related drug discovery during the pandemic."

Generative everything:"AI systems can now compose text, audio, and images to a sufficiently high standard that humans have a hard time telling the difference between synthetic and non-synthetic outputs for some constrained applications of the technology. That promises to generate a tremendous range of downstream applications of AI for both socially useful and less-useful purposes."

AI has a diversity and ethics challenge: In 2019, 45% new U.S. resident AI PhD graduates were white -- by comparison, 2.4% were African American and 3.2% were Hispanic, the report states. Plus, "despite growing calls to address ethical concerns associated with using AI, efforts to address these concerns in the industry are limited. For example, issues such as equity and fairness in AI continue to receive comparatively little attention from companies. Moreover, fewer companies in 2020 view personal or individual privacy risks as relevant, compared with in 2019, and there was no change in the percentage of respondents whose companies are taking steps to mitigate these particular risks."

Computer vision has become industrialized:"Companies are investing increasingly large amounts of computational resources to train computer vision systems at a faster rate than ever before. Meanwhile, technologies for use in deployed systems-like object-detection frameworks for analysis of still frames from videos-are maturing rapidly, indicating further AI deployment."

AI conference attendance up, virtually:An important metric of AI adoption is conference attendance. "That's way up. If anything, Covid-19 may have led to a higher number of people participating in AI research conferences, as the pandemic forced conferences to shift to virtual formats, which in turn led to significant spikes in attendance," the survey's authors contend.

More and more information and research is available: The number of AI journal publications grew by 34.5% from 2019 to 2020 -- a much higher percentage growth than from 2018 to 2019 (19.6%), the report's authors state. "In just the last six years, the number of AI-related publications on arXiv grew by more than six-fold, from 5,478 in 2015 to 34,736 in 2020. AI publications represented 3.8% of all peer-reviewed scientific publications worldwide in 2019, up from 1.3% in 2011."

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Artificial intelligence kept expanding through a turbulent year, with some exceptions - ZDNet

CUYAMA, CA - APRIL 28: Overhead irrigation of this newly planted crop of carrots is putting ... [+] pressure on the available groundwater supplies as viewed on April 28, 2020, in Cuyama, California. Located in the northeastern corner of Santa Barbara County, the sparsely populated and extremely arid Cuyama Valley has become an important agricultural region, producing such diverse crops as carrots, pistachios, lettuce, and wine grapes. (Photo by George Rose/Getty Images)

The globalprecision farming marketincludes technology like robotics, imagery, sensors, artificial intelligence (AI), big data and bio-engineering is expected to reach more than $16 billion by 2028, according to aMarch 2021 reportfrom Grand View Research.

What if you could combine AI and traditional aerial imagery to build data sets that help farmers and food processors gain insight into crop heartiness while it was still growing in the field?

Saul Alarcon, an Agronomist atThe Morningstar Companythat sources and processes tomatoes for several tomato-based products, says that new agriculture technologies based on AI can improve farming decisions. "Accuracy and consistency of data are very important to minimize the impact of crop's yield-limiting factors," said Alarcon.

"Smart farming technologies are becoming, in a short period of time, a key alternative in our worldwide efforts to improve the quantity, quality and nutritional value of food," said Alarcon. "Similarly, we firmly believe that it offers great opportunities to improve our environment while helping farmers to remain profitable."

John Bourne, vice president at Ceres Imaging, says that because food processors are increasingly using AI-powered aerial imagery to help manage their operations, they can now apply that to yield forecasting, quality control and risk mitigation.

"Typically processors pay for imagery and then offer the imagery service as a benefit to growers in their networks at no cost or for subsidized pricing," said Bourne. "This benefits the growers because they get reduced price imagery and product quality control vetted by their processors."

Images paint a picture, but AI images can help provide actionable data for farmers.

"Convolutional neural networks are used to enhance the accuracy of indexes such as segmenting images to identify pixels that belong to the crops we're measuring, and excluding all soil, grass and shadow," said Bourne. "AI can also classify individual plants and the pixels that belong to those plants."

But Bourne says that convolutional neural networks are also used to go from an index to a recommendation for a farmer, which means they could better identify certain acute irrigation issues, such as malfunctioning sprinklers with pins dropped in the imagery and ranking in terms of severity and risk to yield.

Patrick Tokar, Viticulturist atRombauer Vineyardsin Napa Valley, says that the vineyard initially looked into aerial imagery because they were searching for another tool to determine their irrigation needs. The company used Normalized Difference Vegetation Index (NDVI) to help determine the density of a green area in a patch of land but ended up at Ceres Imaging to address irrigation.

"This technology enables us to view the relative water stress for an entire vineyard block as opposed to specific data points within a block," said Tokar.

"What we did not realize when we first started using the service is the amount of correlation between water stress areas and wine quality," said Tokar. "We have traditionally used only NDVI images to map out harvest zones, but given our experiences over the past few years, we now look at the water stress maps in conjunction with the NDVI's."

The aerial data that Ceres processes is transformed into indexes that tell a different crop or yield story based on that index, such as water stress.

"Instead of looking at specific data points in the field to make decisions, aerial imagery gives us literally a bird's eye view of the entire vineyard block," said Tokar. "This enables us to hone in on any problem areas we may not have been aware of otherwise.

Tokar says that by looking at the imagery data, they saved time by planning out specific areas they needed to look at before a site visit, rather than scouting an entire vineyard to find potential problems.

Bourne adds that the primary driver for achieving a high solid percentage optimizes the farmer's irrigation strategy.

"Our most popular index is our water stress index which measures crop transpiration or how much a crop sweats," said Bourne. "The farmer can use the information from the index in several ways such as identifying irrigation issues like clogs and leaks in irrigation equipment."

Bourne says that when they publish the water stress index, the data is passed through an algorithm using convolutional neural networks to look for stress patterns. "The system can then identify issues and predict with a high degree of confidence the cause and severity of such issue such as identifying a grower has an irrigation pressure issue, that impacts six acres with high severity impact on yield," added Bourne.

Bourne adds that farmers can make adjustments caused by human error - an irrigation valve left on, equipment malfunctions, blocked irrigation nozzle, and even optimizing the irrigation schedule.

"For example, aerial imagery could show that the farmer has underwatered or overwatered a parcel of land, or it could show that one section of a block needs more water and one needs less water. So from this, the imager can make zone maps to facilitate watering that fits these issues," said Bourne.

Alarcon says that aerial imagery provided them with high-resolution images of the row and permanent crops. "This technology gives us the advantage of a wider spatial detection of potential yield-limiting factors in crops," says Alarcon.

"Yield uniformity can be improved by assessing low vigor areas during critical crop production stages. Factors like non-sufficient water levels due to low water pressure, plugged-up emitters, insects and disease damage, etc., can be rapidly detected and corrected through the use of crop aerial images.

Bourne believes that this knowledge lets the farmer "dial in" what they want as a result.

"By example, in tomatoes, a common metric is solid as a percentage of total tomato weight its water as a percentage of total tomato," said Bourne. "The grower gets paid more for high-quality tomatoes, so a high solid content tomato generally tastes better can be used fresh for things like salsa which is a higher value and a higher margin use."

Ceres Imaging is based in Oakland, California, and hasraised $35Mto date from institutional investors, including Insight Partners and Romulus Capital.

Originally posted here:
This Winery And Tomato Processor Used Artificial Intelligence To Make Their Crops Better - Forbes