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【2022 Application Example】 Even the United Nations is on board! Yoyo Data Application captures global business opportunities with agricultural data

Nearly 2,000 days in the fields have made Yoyo Data Application a top player in Taiwan’s agricultural data sector. Their comprehensive grasp of crop yields, production periods, and prices has enabled them to collaborate with the United Nations. The service area for agricultural land skyrocketed from 24 hectares to over 6,000 hectares in less than three years—a 250-fold increase. For Wu Junxiao, founder and CEO of Yoyo Data Application, aligning with global environmental trends and becoming a data company at the intersection of climate technology and the green economy to serve the global market is his ultimate entrepreneurial goal.

Wu Junxiao, originally an engineer, joined the Industrial Technology Research Institute in 2010, where he honed his profound technical and data science analytic skills. 'At that time, I was working in data analysis engineering, and almost all data-related materials would be directed to me. Additionally, I worked on indoor cultivation boxes, planting vegetables and mushrooms, hence planting the seed of entrepreneurship by integrating agriculture with data analysis,' Wu recalls.

Since 2016, Wu Junxiao has been frequently visiting farms to 'embed' himself among farmers and agricultural researchers, chatting and sharing information systematically, which quickly established his agricultural know-how.

Solid data analysis capabilities have even convinced the United Nations

In 2017, he left the Institute to start his own business and founded Yoyo Data Application in 2019. Today, many agricultural businesses are his clients, with service areas rapidly climbing from 24 hectares to over 6,000 hectares, expected to surpass 7,000 hectares in 2022. His clientele includes markets in Japan, Central America, and even entities under the United Nations like the World Farmers Organization, which utilizes the 'Yoyo Crop Algorithm System' supported by Yoyo Data.

How exactly does Yoyo Data Application manage to impress even UN agencies?

The 'Yoyo Crop Algorithm System' developed by Yoyo Data Application accurately predicts the production period, yield, and prices.

▲The 'Yoyo Crop Algorithm System' developed by Yoyo Data Application accurately predicts the production period, yield, and prices.

Firstly, due to Wu Junxiao's precise mastery over agricultural data, Yoyo Data Application's clients don't necessarily need sensors or other hardware devices. 'Sensors are expensive and if you buy cheap devices, you just collect a lot of noise or flawed data, which is useless,' Wu explains. He continues, 'Collecting data doesn't necessarily require sensors; our data solutions can solve problems more directly and effectively.' For instance, one of Yoyo Data Application's products, the Yoyo Money Report Agri-price Linebot, developed in collaboration with LINE in 2020, gathers data on origin, wholesale, and terminal prices spanning over 10 years, driven by Yoyo Data’s proprietary AI algorithms. This enables the system to autonomously learn about agricultural product trading prices, using big data and AI to perform price prediction analysis, thereby helping buyers reduce transaction risks and expanding the data application to the entire agricultural supply chain.

Regarding banana prices, the accuracy of price predictions increased from the original 70% to 99.8%. Wu Junxiao notes that both buyers and farmers are very sensitive to prices. Now, through the Yoyo Money Report service, both buyers and farmers can precisely understand the fluctuations in agricultural product prices. Yoyo Data can also provide customers with optimal decision-making advice based on predictive models for crop growth, yield, and price estimations. Currently, price predictions cover 28 types of crops.

Precise estimates of production periods and price fluctuations allow Yoyo Data to provide differentiated services based on data analysis

The 'Yoyo Crop Algorithm System' provided by Yoyo Data Application incorporates a 'Parameter Bank', usually collecting 200-300 parameters, not just straightforward data like temperature and humidity, but also data divided according to the physiological characteristics of the crops. Through effective dynamic data algorithms, it can accurately calculate when crops will flower and when they can be harvested, what the yield will be, and so forth. For instance, the prediction accuracy of the broccoli production period is 0-4 days, with the flowering period predicted this year to be precisely 0 days, perfectly matching the actual flowering time in the field. In these dynamic calculations, a 7-day range is considered reasonable, and the average error value of Yoyo Data's predictions typically ranges from 2-4 days, with most crop production period accuracies above 80%.

Through effective dynamic data algorithms, over 120 global crops can have their production periods and yields accurately estimated.

▲Through effective dynamic data algorithms, over 120 global crops can have their production periods and yields accurately estimated.

Using these effective dynamic data algorithms can set estimates for production quantities, helping adjust at the production end. Yoyo Data Application's clientele primarily includes exporters of fruit crops like pineapples, bananas, guavas, mangos, pomelos, sugar apples,

Taiwan's agricultural production is highly homogenized, often leading to a rush to plant the same crops and resulting in price crashes. Yoyo Data Application helps clients differentiate their offerings. Thus, Wu Junxiao positions his company as a boutique digital consultant, carefully selecting clients for quality over quantity. He notes that Taiwanese agricultural clients focus on how to improve yield rates, even categorizing yield rates by quality, aiming for high-quality, specialized export markets; whereas international clients prioritize maximizing per-unit yields, showing different operational approaches in domestic and international markets.

In addition to agricultural fruit, Yoyo Data Application has also extended its services to the fisheries sector, including species like milkfish, sea bass, and white shrimp, all using the same system to establish various parameters related to the growth of fish and shrimp, such as when to feed and when to harvest, and the anticipated yield, timing, and prices.

Yoyo Data Application harnesses the power of data to create miracles in smart agriculture.

▲Yoyo Data Application harnesses the power of data to create miracles in smart agriculture.

In response to the company's rapid development, Yoyo Data Application introduced venture capital funds in 2021 to expand its staff and promote its business. Wu Junxiao states that in response to the global trend towards net zero carbon emissions by 2050, he plans to help clients plant carbon in the soil, effectively retaining carbon in the land while also connecting clients to carbon trading platforms, creating environmental business opportunities together.

Wu Junxiao says that from the start of his entrepreneurial journey, he positioned the company as a global entity, thus continuous international collaborations are planned. As a data company serving a global clientele and focused on climate technology and the green economy, this represents Wu’s expectations for himself and his company's long-term goals.

Yoyo Data Application founder and CEO Wu Junxiao.

▲Yoyo Data Application founder and CEO Wu Junxiao

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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【導入案例】維繫遊艇王國美譽 嘉信遊艇導入國內第一套FRP複材超音波智慧檢測
Maintaining the reputation of the “Kingdom of Yachts” - Kha Shing Enterprise introduces the first domestic FRP ultrasonic smart inspection of composite materials

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constructed in sections to facilitate inspection For large yachts over 24 meters long, construction in sections is very time-consuming and labor-intensive To shorten the time of the yacht manufacturing process, Kha Shing Enterprise will first carry out the gel coating process for the hull, and then perform the hand lay-on process The hull manufacturing process has two types of composite material test specimen structures In terms of 54-foot yacht hulls, the hull contains gel coat, core material, fiber and resin, and the total thickness is about 32cmplusmn01cm, which is twice the total thickness of FRP hull without core material of about 16cmplusmn01cm Defects such as incomplete impregnation of glass fiber or residual air bubbles between glass fiber and resin occasionally occur during the manufacturing process The types of defects include insufficient resin, voids, and delamination Once defects occur, the supply of hull materials will be insufficient and yacht delivery will be delayed Schematic diagram of types of FRP hull In order to solve this problem, Kha Shing Enterprise has engaged in technical cooperated with the metal materials industry and the AI technology industry, combining the ultrasonic inspection expertise of the metal materials industry with AI technologies developed by the AI technology industry in recent years to help solve issues of Kha Shing Enterprise with defect detection The method uses PAUT on the composite material structure of yachts, conducts FRP ultrasonic evaluation to determine the thickness of the yacht hull and material properties, and evaluates the ultrasonic probe frequency applicable to the hull structure based on professional ultrasonic experience After testing, a frequency of 5MHz and a probe width of 45mm can successfully find the location and size of defects in the simulated defect test specimen The three parties jointly found defect detection solutions from array ultrasonic evaluation, AI technology model development, and 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這是一張圖片。 This is a picture.
AI Assists the Red Cross for Smarter Emergency Response

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disaster training of the Nantou Red Cross, a 'Natural Disaster Emergency Preparedness Material Dispatch and Supplement Decision System' is establishedreferred to as the Emergency Preparedness Material System。 In material management, inventory data along with immediate supply data are entered into the Emergency Preparedness Material System for comparison and analysis, helping the Nantou Red Cross quickly recognize materials like cookiesdry food, beverages, frozen food, toilet paper, etc, and determining whether they should be 'preparedness' materials or regularly distributed materials Adding to this, information forecasting understands the potential disaster conditions in remote areas, facilitating food delivery, addressing both front-end food wastage and backend practical needs When a natural disaster occurs, it enables faster response and decision-making, completing material deployment, hence increasing the speed of material operation transition20。 AI Emergency Preparedness Material System Helps Rapidly Adapt Material Distribution Through the field verification of the Nantou Red CrossAIthe system, material management, and related applications are promoted to more emergency response organizations in different areas, while continuously improving the alert functions within the Emergency Preparedness Material System, strengthening the technological foundation for alerts, enhancing prediction accuracySystem immediacy, and optimizing the data collection and analysis process Simultaneously, it can collaborate with government agencies, meteorological departments, or other rescue teams to discuss integrating more data sources, establishing a mechanism to share resources and data promptly, sharing information in real-time, helping more emergency response organizations enhance their disaster response abilities, seizing the golden rescue time 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

【解決方案】佐翼科技無人機導入高爾夫球場域 可節省一半人力
Droxo Tech Applies Drones in Golf Courses to Reduce Manpower by Half

For most golf courses, the operations and management is a headache "Golf courses are selling turf and need to be properly taken care of," a golf course manager bluntly pointed out Facing the market pain points of labor shortage, aging population and high cost, the use of AI drones for pesticide spraying and pest control will reduce labor costs by more than half and greatly improve the overall operational efficiency At noon in early summer, an AI drone is slowly taking off at the Taipei Golf Club in Taoyuan Its main task is to test AI drone fertilizing and pesticide spraying on the golf course In fact, drones of Droxo Tech, the company performing this task, are widely used for fertilization, pesticide spraying, and pest and disease control for rice, bananas, and tea trees For golf courses with turfs that often cover tens to hundreds of hectares, AI drones are needed to assist in turf maintenance Data collection, development of pesticide spraying AI models, and multispectral image analysis and testing will be carried out in the current stage In the future, large-scale technology implementation and verification will be carried out to set an example for applying drones to golf courses Using AI drones to fertilize and spray pesticides can reduce the manpower required by half The traditional way of maintaining the turf in golf courses is to carry spray buckets or drive spraying vehicles to spray areas one by one "Domestic golf courses began to plant ultra-dwarf Bermuda grass in 2001 This grass species prefers a cool climate and is not suitable for Taiwan's hot and humid weather" Droxo Techrsquos CEO further pointed out that to prevent turf from pests and diseases, pesticide spraying is necessary For an 18-hole golf course, it is equivalent to spraying pesticides once a week, and the T-ground and fairways are sprayed every two months For golf courses, spraying pesticides is time-consuming and labor-intensive It is important to note that large-scale spraying will increase the risk of personnel poisoning and increase the amount of pesticide used Benefits of applying agricultural drones to golf courses According to Droxo Techrsquos research, golf course pests include Spodoptera litura, which comes out at night to look for food, so pesticide spraying must be carried out in the evening According to the traditional method, pesticide spraying requires two vehicles and three personnel for a total of 45 hours If AI drones are used for fertilizing and pesticide spraying, it only takes one operator to spray 08 hectares of land in 20 minutes, saving about two-thirds of the manpower and reducing operating costs by about 30 Using AI drones to fertilize and spray pesticides on golf courses can reduce the manpower required by half In addition to the significant benefits of using agricultural drones for golf course turf maintenance, Droxo Tech also specially introduced AI multispectral image recognition for NDVI Normalized Difference Vegetation Index analysis "The so-called multispectral is to direct light with different wavelengths on the turf, and the reflected images are collected for analysis" Droxo Tech CEO Liu continued to explain that each plant absorbs light with different wavelengths, so multispectral imaging can determine the growth status of grass species At the same time, combined with AI image recognition, the distribution of pests and diseases can be accurately detected, and the amount of pesticide used is determined on this basis Cross-domain collaboration to build a multi-source turf image databasenbsp Using AI multispectral image recognition technology, Droxo Tech will collect visible light, multispectral, thermal images, and hyperspectral images to establish a multi-source turf image database to fully understand the growth cycle of Bermuda grass Droxo Tech has accumulated rich experience in agricultural AI drone pesticide spraying , but there are still many problems that need to be overcome to implement AI solutions in golf courses For example, it is necessary to establish a new pesticide spraying model and test flight methods, especially the application of multispectral image recognition PoC is not difficult, but actual implementation requires more test evidence, repeated inferences, and collaboration with plant experts This part must rely on the cross-domain integration of legal entities such as the Institute for Information Technology III, gathering more fields for verification, and creating a paradigm before it can be more widely adopted by golf courses There are not many international cases on the application of AI drones in golf courses During the verification process, it is not yet known whether it can be quickly copied to the next golf course However, Droxo Tech CEO Liu believes that through cross-domain collaboration, clearly defining the problems and listing them one by one, supply and demand parties can reach a consensus, propose solutions to each problem, and seek cooperation with internal and external resources Only then will we be able to gradually achieve the goal of making golf courses smarter and smoothly assist the industry with transformation Zuoyi Technology's CEO, Liu Junlin 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」