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【2020 Application Example】 AI Implementation in Construction Industry Reduces Workplace Accidents: Safety Visibility Enhanced

The construction industry is Taiwan's leading industry, supporting the architecture, decoration, and repair sectors. However, the high incidence of occupational accidents in this sector is a major concern for both employers and workers. The introduction of AI for equipment recognition in the construction industry reassures companies and protects workers, creating a win-win situation.

According to the Ministry of Labor's 2017 statistics on occupational injuries, the average rate of occupational injuries per thousand workers across various industries is 2.773. However, the construction industry tops the list with a rate of 10.036, which is 3.6 times the average and categorizes it as a high-risk group for occupational injuries. Proactive early warning measures can significantly reduce the rate of workplace accidents.

In light of this, the Institute for Information Industry, under the mandate of the Ministry of Economic Affairs' Industrial Development Bureau, has initiated an AI project that prioritizes the implementation of AI technology in the construction industry. Selecting well-known construction firms in Taiwan, the project applies Canon's safety helmet proper wearing recognition solution to reduce occupational accident rates.

Smart Recognition of Safety Helmet Wearing: A Solution for Employers

Senior executives in the construction industry emphasize that compared to other industries, construction workers face higher health and safety risks primarily at construction sites. Many risks arise from the workers not properly wearing or using personal protective equipment, such as safety helmets. Relying solely on human supervision for ensuring safety gear compliance is time-consuming and often ineffective. Implementing AI technology for smart monitoring on construction sites can save corporate resources while ensuring worker safety, achieving dual benefits.

Indeed, to protect workers during operations, construction plants require workers to properly wear safety helmets. Wearing a helmet does not imply it is worn correctly. To prevent the helmet from falling off during operations, it is necessary to securely fasten the chin strap directly under the chin after putting on the helmet.

Proper Wearing Method for Construction Site Safety Helmets

▲工地用安全帽正確佩戴方法

At construction sites, many foreign workers often do not follow proper safety protocols, such as not wearing safety helmets correctly. If supervisory personnel were to be assigned, it would entail excessive use of human resources. With the assistance of the information strategy team, major construction companies have adopted Canon's image recognition technology.

To determine the optimal placement of image recognition cameras, both teams first conduct site surveys and collect various types of safety helmets used on-site. Subsequently, standard cameras are installed at entry points of construction sites and work zones to capture footage of the site personnel. This footage helps Canon develop models for correctly and incorrectly worn helmets, aiding the image recognition software in its learning phase. Canon's engineers regularly visit the site to retrieve footage, and once the image recognition software achieves a certain accuracy level, the image recognition cameras are then installed at the construction site.

Canon Construction Site Safety Helmet Data Collection Camera Setup

▲佳能工地安全帽資料搜集攝影機設置

Improving Recognition Accuracy for Concrete Implementation of Workplace Safety

Currently, no local technology can accurately recognize the proper wearing of safety helmets. Therefore, Canon has developed and trained its own recognition software. The complex environment at the actual installation sites can impact the effectiveness of recognition.

In the future, machine learning will significantly enhance the overall recognition accuracy, ensuring that safety measures involving the wearing of safety helmets are concretely implemented.

While AI recognition technology is introduced in the construction industry's safety domain, it can also be integrated with mobile devices for early warning. In practice, once a camera captures recognition data and processes it, the results can be pushed immediately to specific individuals such as safety managers on their mobile phones, tablets, or even linked to access control systems. If a worker is detected without a properly worn safety helmet, relevant personnel can be alerted promptly. Access can be denied until the worker correctly wears the safety helmet, offering considerable potential for future applications.

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

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【解決方案】優式AI智能割草機器人 搶攻高爾夫藍海市場
USRROBOT's AI Lawn Mowing Robot Enters the Blue Ocean of Golf Market

An AI smart lawn mowing robot, resembling a vacuum robot, shuttles back and forth on the 30-hectare golf course lawn for weeding This robot, independently developed and designed by Taiwanese, is equipped with the world's first electronic fencing positioning technology which utilizes high-precision GPS integrated with cloud AI computation to determine the most efficient mowing paths, targeting the lucrative blue ocean market of golf courses This AI lawn mowing robot was developed by USRROBOT, a Taiwanese startup established in 2019 Chao-Cheng Chen, the president of USRROBOT, once served as the executive vice president of one of the top five ODM tech companies in Taiwan, and specializes in software and hardware integration When he served as the chairman of the Service Robot Alliance, he knew that the service robot industry was bound grow rapidly due to declining birth rates and the growingly severe labor shortage New demand - The horticulture market is large and the has rigid demand "To develop the core technology of service robots, we must find rigid demand Looking at European and American countries, there is a shortage of labor, but demand for horticulture has increased, and there has been a long-term shortage of 7-10 of horticultural workers" Under this strong "rigid demand," Chao-Cheng Chen established USRROBOT, and the company's first product is the AI lawn mowing robot In terms of overseas markets, the United States is the world's largest horticulture market, accounting for 30-40 of the global output value It is estimated that there are about 1 million horticulture workers, but they have been experiencing a labor shortage of 7-10 in recent years and have not been able to improve the situation The main reasons for labor shortage are Aging population and gardening is a labor-intensive job, so young people don't want to do it Unlike in Taiwan, European and American countries attach great importance to lawn maintenance and have expressly stipulated in the law that heavy fines will be imposed for failing to mow the lawn Therefore, the AI lawn mowing robot has considerable market development potential The introduction of AI multi-device collaborative mowing sensor technology is expected to reduce the burden of staff maintaining the golf course The AI lawn mowing robot developed by USRROBOT is currently in its second generation Domestic universities and well-known art museums are using the latest model M1, and it is also being used by some world-renowned high-tech companies and well-known universities in the United States The company is currently involved in negotiations for subsequent business cooperation USRROBOT stated that the professional RTK system currently used can reduce the original GPS positioning error from tens of meters to about 2 centimeters, allowing the robot to move accurately outdoors After setting the boundaries, it can be easily operated using the app New application - Implementation in golf courses solves the problem of labor aging and shortage Chao-Cheng Chen further explained that the National Land Surveying and Mapping Center is a RTK service provider RTK provides the error reference map of the positioning point USRROBOT can access the positioning error value of a specific position through 4G Internet access The AI algorithm of USRROBOT reduces the general 10-20 m error of GPS to 2 cm After positioning, USRROBOT then uses six-axis accelerator positioning, gyroscopes, and wheel differential sensing devices for software and hardware integration Only by matching the wheel's movement pattern and the terrain can accurate mowing path planning be achieved The AI lawn mowing robot, which is 62 cm wide, 84 cm long, 46 cm high, and weighs only 25 kg, can set the mowing boundaries in the cloud It can avoid pools and sand pits through settings, using AI algorithms to automatically calculate the optimal path It is able to mow approximately 150 ping of grass in one hour The battery can be used continuously for more than 6 hours The battery life is currently the highest in the world In addition to general gardening companies, with the assistance of the AI project team of the Industrial Development Bureau, Ministry of Economic Affairs, USRROBOT's AI lawn mowing robot has been applied to golf course lawn mowing A well-known golf course located in Taiping District, Taichung City currently has a staff of 5 people who are responsible for the lawn, planting maintenance, and other landscape maintenance of the entire 30-hectare course However, the average age of staff is as high as 55 years old, and the golf course has been unable to recruit new staff members for a long time In view of the aging staff and the shortage of manpower, the golf course hopes to mitigate the impact with AI technology, and is therefore using AI multi-device collaborative mowing sensor technology, in hopes of reducing the burden of staff maintaining the golf course New challenges - Expert systems are needed to overcome difficulties with different grass species "This AI lawn mowing robot has low noise, low pollution, low labor costs, and is waterproof and anti-theft In the lawn mowing process, it can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality, maintaining aesthetic and consistent grass length" Chao-Cheng Chen went on to say that the most important part about golf courses is that the grass pattern should be beautiful and free from diseases and pests Based on the site survey, golf courses are mainly divided into three major areas green, fairway and rough There is no problem using the current mowing robot to mow the rough area, and it can overcome slopes within 20 degreesThe short grass in the fairway area may only be two centimeters long, and the grass types are also different, so the cutterhead design needs to be modifiedAs for the grass in the green area, the grass must be mowed close to the ground and maintained in a consistent direction because it affects the putting speed Many factors will affect the green index, and this part requires more research and testing The AI lawn mowing robot can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality The AI smart lawn mowing robot has a built-in camera that can be used to detect the health condition of the lawn Chao-Cheng Chen said that in the future, an expert system will also be introduced for early determination of whether there are diseases, pests in the lawn or whether there is sufficient moisture, and provide lawn health data analysis to customers, so that they can take preventive and response measures sooner to reduce disaster losses Chao-Cheng Chen, who is also a good golfer himself, said that golf has developed well in Taiwan However, due to weather factors, such as rainy and humid climate and typhoons, Taiwan's golf courses have harder soil and more potholes compared with top tier golf courses overseas If AI lawn mowing robots are to be widely introduced into golf courses, there are still many difficulties that must be overcome However, Taiwan's difficult terrain creates a good testing ground Once Taiwan can overcome the many problems and successfully introduce the robot, it will be able to expand to overseas markets and seize new market opportunities in a blue ocean Chao-Cheng Chen, President of USRROBOT nbsp

【解決方案】搭上綠能商機 華鉬實業打造全釩液流電池儲能系統設備 長效儲能的最佳選擇
Taking advantage of green energy business opportunities, Hua Molybdenum Industry creates all-vanadium redox flow battery energy storage system equipment, the best choice for long-term energy storage

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battery electrolyte and wind turbine AI predictive operation and maintenance, providing 100 safety, long-term efficiency and reducing customer initial manufacturing costs cost-effective power energy storage equipment, and through AI predictive operation and maintenance services to help customers reduce power generation costs by 10 and save up to 30 in maintenance and warranty costs Hua Molybdenum Industry was established in 1998 The industry started by refining vanadium, molybdenum and rare metal elements and other products, and used them in high-end steel, professional chemicals and specialty chemicals industries, and vanadium is more like a steel-making Vitamins can increase the effectiveness of steelmaking Among them, vanadium and molybdenum related products are one of the company's main projects The company sees that the all-vanadium redox flow battery, which is 100 vanadium-based, will be a very promising mainstream green energy technology in terms of long-term energy storage in 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turbines uses machine learning The main technology provider comes from ONYX Insight, a subsidiary of British Petroleum BP The company uses AI Hub analysis software technology to analyze the wind turbines faced by Taipower Pain point analysis, including power generation loss of road-based wind turbines and damage prediction of key components of land-based wind turbines such as gearboxes, pitch bearings under abnormal vibration three-dimensional vibration frequency or abnormal temperature, etc output Through this implementation, it can effectively help Taipower reduce power generation costs by 10, increase asset value by 12, and save up to 30 in maintenance and warranty costs In the past three years, ONYX Insight has successfully predicted and operated more than 20,000 offshore or onshore wind turbines around the world, accumulating extremely high AI model accuracy It is believed that the international partnership established with ONYX Insight will effectively guide and accelerate the green energy division of Hua Molybdenum Industry in its goal and layout to become an independent technology service provider for wind turbine AI predictive operation and maintenance Works with partner ONYX insight to provide customers with an AI predictive operation and maintenance system, including wind turbine power generation loss and damage prediction of key wind turbine components Building a solid foundation for domestic wind turbine operation and maintenance, using Taiwan as a base to expand to Southeast Asian wind farms The market output value of offshore wind turbine AI predictive operation and maintenance in Taiwan will exceed NT30 billion in the future, and the energy storage market has an output value of more than 100 billion US dollars globally In the future company vision, Hua Molybdenum Industrial hopes to become An independent technical service provider for vanadium flow battery electrolyte and wind turbine AI predictive operation and maintenance The long-term goal is to establish a local supply chain of vanadium flow battery electrolytes around the world by accumulating abundant technology and performance capital to supply industry needs nearby 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】哈瑪星科技建構AI模型管理平台 加速AI落地應用
Hamastar Technology Builds an AI Model Management Platform to Accelerate the Application of AI

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