Smart Agriculture Drives 18.5 Billion US Dollars and AI Data Is the Key!
Market News

Smart Agriculture Drives 18.5 Billion US Dollars and AI Data Is the Key!

The era of AI smart agriculture is coming, and whether enough data can be collected to train robots to solve the problem of automated harvesting will be the key to digital transformation.
Published: Sep 13, 2022
Smart Agriculture Drives 18.5 Billion US Dollars and AI Data Is the Key!

According to the "World Agrochemical Network" report, the application-based "smart agriculture" market is expected to reach a scale of US$18.45 billion in 2022, with a compound annual growth rate of 13.8%. Smart agriculture has a wide range of applications, such as remote data monitoring of sunlight, temperature and humidity in farms, crop growth monitoring, fruit picking robots, even pest control, and regional 3D vegetation detection. The scope of smart agriculture.

Facing The Trend of Smart Agriculture, Countries Around the World Offer "Data" To Solve the Problem

France, as the EU's largest agricultural producer, bears the brunt of this. The French government, agricultural organizations, and private enterprises have collaborated to establish an agricultural information database covering planting, fishing, animal husbandry, and even agricultural technology research and development, commercial markets, and legal policies. French farmers don't have to go out under the sun, just swipe their mobile phones, and they can master the world's "farming affairs" with one hand.

In Asia, Japan is notoriously aging country, with the average age of farmers as high as 67 years old. The Ministry of Agriculture, Forestry and Fisheries of Japan estimated that in 2015, there were still 1.5 million agricultural employees, but by 2030, it will drop all the way to 750,000, and it will be reduced by half within 15 years. This figure made the Ibaraki prefectural government decide to take action to save local agriculture.

Ibaraki Prefecture is located in the northeastern part of Japan, with a vast area of agricultural land, about the size of 460 Tokyo Domes. In April of this year, Ibaraki Prefecture launched the "Tsukuba City Future Co-creation Project". Through industry-government-academia cooperation between the government, farmers and new start-ups, it will jointly develop AI robots for smart agriculture with farmers, and introduce robots in a low-cost way. Locally grown tomato, cucumber, green pepper, lychee and other farms. Committed to creating time-saving, labor-saving and "earned-money" agriculture with AI video surveillance, creating the prosperity of sustainable agriculture in the next 100 years.

Smart Agriculture Starts with Data Collection

The smart agriculture projects I have handled in the past have covered main types such as automatic harvesting, growth monitoring, and pest control. Some of the clients are from large enterprises, start-ups or agricultural organizations, among which Japan has the most clients.

Before embarking on digital transformation or AI industrialization, "data collection" is an important way to start. For example, we all know that a top-quality Wagyu beef needs to have fine meat quality and evenly distributed oil flowers, and a good data set is very similar to Wagyu beef and needs to have the following characteristics at the same time:

  1. Is the “quality” of the images clear and correct?
  2. Are the “proportions” of various target objects and field situations evenly distributed?

If a batch of AI data is collected from the wrong angle, or if there is a large deviation in the number of images among various target objects, and the images are blurred, it is easy to cause machine learning errors.

Taking the AI application of the growth monitoring of flower farmland as an example, a high-angle aerial camera is generally used for framing, and when collecting pictures, the surrounding objects that will cause interference, such as weeds, vegetation, other mixed objects, are not overlooked. Flower varieties, etc. If necessary, even the influence of sunny and rainy days should be taken into consideration.

The AI application of fruit harvesting robots needs to be photographed from a head-up angle, and may focus on obtaining features such as stems, leaves, buds, flowers, and fruits that are similar in proportion and clear, in order to learn quickly and well. .

After the data collection is completed, it enters another important link - data annotation.

How To Label Ai Data Is the Key

The AI data labeling of smart agriculture is actually not simpler than the general data labeling, because it involves a lot of "botany" and pays great attention to details.

For a while, we had an entire row of potted tomatoes in the office. After a while, tomatoes were replaced with raspberries, lilies and other plants. Some customers come to visit, thinking that these potted plants exist to beautify the environment, but in fact, the project management and AI data annotation team can grasp the characteristics and details of the annotation in order to observe the details of plant growth up close. When encountering problems that cannot be solved, we will also consult experts related to agriculture, so as to fully understand the growth characteristics of plants, so that the labeling work can be done in place and with high quality.

Because there is abundant data labeling experience as a nutrient, when dealing with different agricultural projects, past experience can be quickly copied to other project types. Take the case of the raspberry harvesting robot, for example.

If only the fruit and flower parts are framed when labeling, and machine learning is performed, a blind spot will be found: that is, the "branches" also need to be labeled, and the difference between the trunk and the branches must be clearly distinguished. Why do you say that?

If only the fruit is marked, the machine may directly cut off the branches in order to achieve the goal of harvesting the fruit, causing serious agricultural damage. At the same time, the branches are divided into two types: the main trunk and the branch trunk. The machine must be clearly told several principles that do not contradict each other, so that the machine can know which parts should be cut and which ones must not be cut.

The reason sounds simple, but from the perspective of customers and AI robots, we need professional insights into data and innovative solutions. Through the feedback mechanism, it not only optimizes the labeling principle, but also saves the time for customers to correct data errors back and forth.

The era of AI smart agriculture is coming. Under the promotion of production, government, and education, with the assistance of AI data, the work of harvesting rice in the future may be easier, and may no longer be hard work.

Published by Sep 13, 2022 Source :Business Next

Further reading

You might also be interested in ...

Headline
Market News
Is Self-Driving Technology Not Far from Commercial Use? Learn to Accept the Imperfection of Technology
The wave of electric vehicles has allowed the commercialization of self-driving technology, and has more room for imagination. However, the director of Berkeley's DeepDrive artificial intelligence and automatic system research center, believes that we must first accept the imperfection of technology.
Headline
Market News
What is a Smart Building?
Smart Building is to integrate building design and information communication active perception and active control technology to achieve safety, health, convenience, comfort, energy saving, and create a humanized living space as the goal.
Headline
Market News
AR Smart Glasses Drive the Explosion of Micro LED Demand, With an Output Value of Us$41 Million In 2026
Micro LEDs have the advantages of high resolution, flexibility, and foldability. They are the focus of the development of next-generation display technology. AR smart glasses have driven the explosion of demand for Micro LEDs.
Headline
Market News
The Plastic Industry Faces the Challenges of the Market Environment
With such high uncertainty and high volatility in the market environment, how can the plastics industry improve its physique? Can we respond flexibly to the ever-changing world economy?
Headline
Market News
What are the Business Opportunities for "Home" Sports Under the Epidemic?
The COVID-19 sweeping the world has brought huge turbulence to the fitness industry. At the moment when gyms have declared bankruptcy, fitness equipment manufacturers have ushered in an unprecedented surge in demand due to the trend of home fitness.
Headline
Market News
Wearable Devices - Smart Clothing from Function to Intelligence
Smart clothes are clothes made of fibers or fabrics integrating electronic components and combining information technology, which can be used as signal transmission. Looking at the technological changes of functional clothing, the content of patents has shifted from functionality to intelligence, gradually narrowing the gap between technology and reality. The design of smart clothing requires multi-faceted considerations. Cross-industry integration and cross-domain integration are inevitable trends in the future. Taiwanese industries already have the advantageous technologies required for smart clothing, breaking through the existing operating framework of wearable devices and combining with different needs and usage scenarios. And integrating wireless transmission module and communication technology, using fabric as the carrier of signal transmission, can achieve new thinking of creating value and new opportunities for product development.
Headline
Market News
RCEP Officially Signed in the World's Largest Economic Circle - China Dominates the Asia-Pacific Regional Economy
The main goal of RCEP is to integrate the existing ASEAN+1FTA and add new regulatory rules, such as e-commerce, telecommunications services, etc., to establish unified trade rules for Asia-Pacific countries.
Headline
Market News
Mastering the Five Key Changes, Taiwan's Bicycle Industry Jumps Again
Under the multiple influences of technology, sharing and global economic and trade reforms, the global bicycle industry has entered a critical moment of multiple flips. Taiwan's bicycle industry, which has always had a competitive advantage, is facing a severe challenge of how to maintain its advantages. The addition of new startups injects a stream of innovation and brings new opportunities for the rise of Taiwan's bicycle industry.
Headline
Market News
Explore the Pulse of the US Machine Tool Market
The U.S. machine tool industry is the industry that has been hit the most by this wave of epidemics, including smart machinery and Industry 4.0, which are still the unchanged development trends for machine tool manufacturers in the future.
Headline
Market News
Global Semiconductor Packaging Materials Market Outlook and Analysis
Wafer-level packaging (WLP) has gained traction over the past decade as the semiconductor industry continues to push for generations of higher-performance chips. Back-end packaging technologies are becoming increasingly important in meeting the demands of low-latency, high-bandwidth, and low-cost semiconductor devices.
Headline
Market News
Sewing Machinery Industry - Analysis of Taiwan, China, Japan, Germany
The cutting bed in the textile and garment industry is rapidly popularized, the automation penetration rate of sewing equipment continues to increase, the acceptance of template machines is improved, and the textile and garment industry continues to move abroad.
Headline
Market News
General Situation and Development of the Shipbuilding Industry
An industrial sector engaged in the construction of hulls, the installation of engines and complete outfitting, and the refurbishment of finished ships.
Agree