:::

【2021 Application Example】 Savior of Wastewater Treatment: Combining Big Data and AI Technology Opens Another Horizon in the Environmental Industry

As water resources deplete and environmental protection needs increase, wastewater treatment plants have increasingly adopted AI technology to assist in monitoring and warning systems. Zhongxin行's integration of big data and AI technology has opened up new possibilities in the environmental industry. In the future, besides boosting the technological momentum of the wastewater treatment industry, it can also be promoted to other industries to foster technological and economic development.

Founded in year 1980 as Zhongxin Engineering (later renamed to Zhongxin行 Company Limited), it is one of the largest and most technically equipped environmental companies in the domestic operation and maintenance field. Zhongxin行's achievements in the operation and maintenance of sewer systems span across Taiwan, including science parks, industrial zones, international airports, schools, collective housing, national parks, and factories.

Introduction of AI systems in wastewater plants Precisely reduces medication addition times and lowers the risk of penalties for water quality violations

At the wastewater treatment plant in Hsinchu Science Park, Zhongxin行 introduced the 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' which accurately predicts air volume control and reduces medication times, thus lowering the risk of hefty fines. Zhongxin行 points out that with the vigorous development of advanced industries and increasingly strict effluent standards, a slight misalignment in equipment control can lead to major discrepancies in water quality.

In recent years, many wastewater treatment facilities have incorporated automatic control functions, yet onsite conditions often deviate slightly from theoretical expectations, causing situations where good treatment technologies must continuously adapt and adjust to achieve effective effluent water quality control. 'The better the quality of the effluent, the greater the pressure on the operators. This is the biggest pain point for Zhongxin行,' said a senior manager candidly.

Regular water quality testing and equipment maintenance ensure that effluent water stays below legal standards.

▲ Regular water quality testing and equipment maintenance ensure that effluent water stays below legal standards.

This means that operators need to be on top of equipment and water quality conditions daily. If there are sudden anomalies in influent water quality or equipment malfunctions, linked issues can lead to pollution. Therefore, besides performing regular maintenance and testing, it is critical to constantly monitor the dashboard to ensure system stability, consuming both manpower and mental energy.

Zhongxin行's on-site operators work 24-hour shifts, constantly monitoring effluent water quality. Combined with laboratory water testing and analysis, if the wastewater treatment values do not meet requirements, they face both administrative and contractual fines from environmental agencies and granting authorities, which also create significant psychological pressure on the employees.

Over the years, Zhongxin行 has built up a vast database of water quality information and invaluable experience passed down among employees, allowing a comprehensive understanding of the entire system's operational characteristics. Moreover, by analyzing equipment or water quality data for key signals, problems in the treatment units can be pinpointed. If AI technology could be adopted to replace manual inspections of wastewater sources and generate pre-warning signals for systematic assessment, it would significantly alleviate the pressure on staff.

Response time reduced from 8 hours to 4 hours, saving half the time

By implementing 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' Zhongxin行 utilizes accumulated wastewater data along with verbal recounts of operator experiences on-site. With the support of AI technology and environmental engineering principles, key parameters in the biological treatment unit such as carbon source dosages and aeration can be effectively controlled. Through the AI transformation of wastewater treatment, a balance is achieved among pollutant removal, microbial growth, equipment energy conservation, and operation economization, achieving rationalized control parameters.

Carbon source and aeration parameter adjustment steps range from data collection, model training to prediction verification.

▲ Carbon source and aeration parameter adjustment steps range from data collection, model training to prediction verification.

In the long run, incorporating historical data calculations, AI can operate within known boundary conditions, not only recording past water quality and equipment operational characteristics far more accurately, but also developing predictive models to find optimal solutions that offer the best results in terms of chemical use, energy saving, reduced greenhouse gas emissions, and pollutant removal.

According to Zhongxin行's estimates, originally due to human parameter adjustments leading to errors, controlling response time would take about 8 hours. With the introduction of AI technology, not only can measurement errors be reduced, but also the control response time can be shortened to 4 hours, saving around half the time. This enhancement increases the turnover rate of personnel and effectively reduces the risks of penalties due to operator errors and thus markedly reducing the pressure on employees.

Dashboard digital display panel illustration.

▲Dashboard digital display panel illustration

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

Recommend Cases

【導入案例】化身大型AIOT科技遊樂場 海科館華麗轉身好吸睛
Transforming into a Large-Scale AIoT Technology Playground: The Spectacular Makeover of the National Museum of Marine Science & Technology

Taiwan is a maritime nation When you visit the Badozi Fishing Port or Tidal Park in Keelung, do you also explore the mysteries of the ocean world at the 48-hectare National Museum of Marine Science amp Technology To get more people closer to marine technology, Keelung's Marine Museum has introduced technological services, transforming the venue into a large technology playground that delights both children and adults, fully utilizing the 'learning through play' approach After a lengthy planning process, Northern Taiwan's largest marine science museum in Keelung opened in January 2014 The museum focuses on marine education and technology, boasting Taiwan's largest IMAX 3D ocean theater The unique themes and modern viewing facilities should make it a well-known landmark in Keelung However, the original exhibition planning was static and highly specialized, lacking sufficient interaction with the public Visitors who have attended the museum also reported that the exhibits were limited and quite boring, leading to poor overall consumer experience ratings The top three dissatisfactions with the museum were weak connections to surrounding attractions, unengaging display content, and lack of exhibit material According to statistics from the Marine Museum, the ratio of local to visiting guests is approximately 64, with most foreign visitors coming from the north transportation is primarily by car and bus common types of visits include family, parent-child, and friends and the stay duration is generally 1 to 2 hours Upon deeper investigation, the top three visitor complaints were weak linkages to surrounding attractions, unengaging display content, and insufficient number of exhibits The museum analyzed potential reasons, including some displays being too specialized, making it difficult for the public to understand, and a lack of interactive elements, making the exhibition boring and the visit hurriedly brief Analysis of visitor profiles revealed that since half of the museum's visitors are locals, and accessing the museum is not so easy for out-of-towners who must travel by car or public transport, the design of the venue and exhibitions must incorporate more interactivity and intrigue to encourage locals to return and extend the duration of visitors' stays while using technological services to highlight the museum's unique features Through a recommendation from the Information Software Association, part of the Ministry of Economic Affairs' Industrial Bureau AI team, the Marine Museum commissioned Jugu Technology to resolve the issue of uninspiring venue attractions Preliminary interviews by Jugu Technology revealed that many visitors were attracted by the architectural design of the museum, notices posted on nearby walls, flags, or events being held the most interesting feature for visitors was the 3D ocean theater, indicating that content presented through audio-video and physical scenic methods was more engaging Seven major AI technologies lead to a boost in regional tourism at the Marine Museum Through the introduction of technology services, Jugu Technology designed the 48-hectare site with seven major services AI voice tours, treasure hunt puzzle games, AI exhibit interactive revitalization, AI space exhibition interactive experience, AI crowd control, Face AI interactive experience, and AI voice customer service system By utilizing AIoT and cloud technology, they made the exhibition more interesting, not only solving the issue of boring static viewings for children but also doubling the learning efficiency and dramatically improving public perception of the Marine Museum, thus increasing visitor intent and boosting regional tourism The National Museum of Marine Science and Technology introduced seven major technological application services including AI voice guide Jugu Technology aimed to improve the space optimization of the Marine Museum, using the special exhibition of coastal birds in northern Taiwan as a prototype, integrating 'face', 'limb', 'crowd' as three main axes to enhance functionality and assist in improving the museum's application of AI Practically, the Marine Museum and Jugu Technology selected the on-site special exhibits to avoid any installation of water and electricity works or pipelines in active exhibits, thereby maintaining the quality of the viewing experience Instead, they selected exhibits that were not yet open to introduce a series of technological services tailored to the unique characteristics of the exhibits In the coastal bird special exhibition inside the Marine Museum, initial construction discussions with the curators utilized Bella X1 for a welcoming interactive introduction at the exhibition entrance This was followed by an AI-powered smart guide in both Chinese and English using X1 for narration, coupled with a fun treasure hunting stamp-collecting activity - APP X1, allowing visitors to participate in challenges Subsequently, bird species within the bird exhibition were brought to life interactively using X1, and AR scenarios X1 were introduced into the exhibition space to add elements of fun and entertainment Finally, Face AI was used to interactively test facial expressions and score smiles The gorgeously transformed Marine Museum will become the best travel destination for families with children ImageMarine Museum FB Page The AIoT services introduced by the Marine Museum could be extended to various exhibition-type museums and even static art galleries in the future, tailored to the unique characteristics of different venues They could also be promoted through government projects and related plans, aiding in rural revitalization, making visits more than just sightseeing in rural areas, and breaking free from stereotypes associated with different venues The applications of these services are broad「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
AI Assists the Red Cross for Smarter Emergency Response

More Preparation Less Loss The Taiwan Food Bank Association, a non-profit organization, collects donations daily from wholesalers, retailers, manufacturers, and even kind-hearted individuals across Taiwan They also rescue consumable materials that are about to be discarded, properly allocate and deliver to households in need, aiding local underprivileged populations When natural disasters such as earthquakes, landslides, mudslides, typhoons, floods, and droughts occur in Taiwan, the food bank's resources can be immediately deployed for disaster relief This field verification unit is the Nantou County Red Cross AssociationOne of the food bank locations, hereinafter referred to as the Nantou Red CrossIs responsible for tasks like pre-disaster supplies preparation and disaster relief material distribution, helping the government bear the responsibility of disaster relief and aid In Taiwan, various natural disasters have characteristics of different duration and spatial coverage, wide or narrow With the normalization of extreme weather, the scale and number of disasters are gradually increasing and becoming harder to predict The required amount and type of materials differ by disaster, and they must address the lifestyles of the affected areas, rescue needs, traffic conditions, geographical restrictions, and other factors for varied material allocation, facing numerous challenges Typhoon Kanu severely damaged transportation in Nantou mountain areas Nantou County Red Cross planned the mountainous route Puli gt Fazhi Elementary School gt Qin'ai Village gt Aowanda to deliver supplies Disasters happen repeatedly We need to be prepared at all times Effective disaster preparedness can mitigate the impact, including swift response to material needs in affected areas, aid distribution, and even psychological support, providing added security for life and property of those in disaster zones Lack of Timeliness in Disaster Information To improve the living conditions and address the lack of supplies in remote areas, the Taiwan Food Bank Association has partnered with the Nantou Red Cross and has successively established food bank points in Nantou City, Puli, and Ren'aiLixing, Ruiyan, XinyiWangmei, Tongfu, Shuili, Lugu and Caotun among others9establish food bank locations, providing supplies worth a certain amount per household every month6001000in New Taiwan Dollars However, many challenges still need to be overcome during natural disasters For example, when typhoons, earthquakes, and landslides occur, the information source for disaster relief dispatch systems relies on post-disaster reports The time lag between reporting, response, and execution prevents timely adjustment and distribution of 'disaster relief' supplies based on the needs of affected areas, affecting rescue efficiency due to lack of timely information The 'preparedness' supplies of the Nantou Red Crosssuch as dry food, water, instant noodles, etc,are recorded manually in terms of stock, expiration dates, and distribution,When a disaster occurs, there is a chance that 'preparedness' supplies have expired and cannot become 'disaster relief' supplies It’s also possible that both conditions mentioned above occur simultaneously, leading to a need for more time to reassign 'preparedness' supplies into usable 'disaster relief' materials On the other hand, upon receiving information about shortages in disaster areas, the supplies donated by the public often grossly differ from the actual needs of the disaster zone, leading to an excess of supplies The Process of Material Operations Before and After a Natural Disaster AIAnticipating Natural Disasters Reinforcing the Accuracy of Preparedness Material Dispatch Application API Technology connects to compute the state of the climate, the intensity of disaster rescues, prioritizing the main tasks of the Nantou Red Cross and the needed areas of search and rescue Coordinated with the existing heavy rain and typhoon simulation 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」

【導入案例】赫銳特科技VCSEL封裝元件瑕疵導入AOI檢測 提升產能效率20
HRT Technology Improves Production Efficiency by 20% Through AOI Detection of Defects in VCSEL Packaging

In 2017, the launch of the iPhone X made 3D sensor technology used in Face ID highly popular, which drove the development of VCSEL, a core component in the 3D sensor module In the detection of defects in incoming packaged VCSEL, the use of AI inference models can solve the industry's issue with low yield and improve reliability to 95 VCSEL technology currently can be used in many applications and various end consumer markets, including robots, mobile devices, surveillance, drones, and ARVR VCSELs are a good solution in applications that require high-speed modulation capabilities, such as cameras and biometrics VCSEL technology has a wide range ofnbsp applications, including in drones Pictured Zoyi Technology's Agricultural Drone VCSEL technology has a wide range of applications, AI technology assists in defect detection HRT Technology stated that the packaged VCSEL market is also facing strong price competition from competitors, and needs to further reduce costs and enhance product competitiveness One of the key problems is the replacement of glass lens with epoxy resin lens The production of traditional glass lenses has high yield, but the cost is higher than that of epoxy resin lenses Due to the cutting process of epoxy resin, the side wall of cutting lines can easily have rough edges, causing it to be oversized The release of stress caused by heat during the mounting process will directly cause the optical lens to break HRT Technology pointed out that the incoming inspection of VCSEL epoxy resin lenses is very important Under the constraints of packaging space, the space for fitting the package and optical lens is limited Moreover, the optical lenses will be confined to a metal frame If the dimensional tolerances are properly controlled, stress release due to heat during mounting can easily cause the optical lens to break, resulting in a yield loss of up to 10 in the VCSEL package reliability verification, resulting in an increase in production costs In order to solve the problems above, HRT Technology hopes to use AI to monitor the size and appearance defects of epoxy resin components in the VCSEL epoxy resin lens incoming stage, verifying whether their dimensions meet specifications, whether the cutting edges are smooth, and whether there are any defects in their appearance Since traditional incoming material inspection requires a rough visual inspection by humans to distinguish the quality The problem of image collection needs to be solved first to successfully collect image data Therefore, HRT Technology first developed an Automated Optical Inspection AOI device, which includes X, Y, Z three-axis motion, high-resolution cameras, and related control software to automatically record images After collecting the image data, opencv aligns the test image and a normal image to determine differences between the two images, and then pixel mapping is used to compare the pixel area to complete initial screening Manual labeling is carried out according to the image classification above, including samples that are normal, have defects in appearance, or have different shape characteristics, and then algorithm training and verification is carried out Residual neural network ResNet or other related algorithms are used for deep learning to identify the quality of lenses Implementation of AOI inspection improves production efficiency by 20 and above Comparing the differences before and after the implementation of AI image inspection, the incoming VCSEL lens inspection before implementation only involved manual inspection of the appearance The lens is packaged on the VCSEL package that has completed die bonding After passing the general light up test, the final reliability test high temperature reflow is performed Failed samples go into the rework process However, after the implementation of AOI inspection, it can screen defective lenses sooner and reduce the cost of subsequent materials input, it can also reduce the need for rework due to failure, improving yield to 95 and above in the reliability verification This is expected to help companies reduce production costs by 10 and increase production efficiency by 20 and above The difference before and after implementing AI image detection HRT Technology pointed out that this technology is an AI application developed based on tiny images It uses deep learning algorithms to identify defects in the images The trained network automatically classifies image data to predetermined categories Defect categories can be determined through reference images, so cumbersome programming is not required In the industrial machine vision environment, deep learning is mainly used for classification tasks in applications, such as inspection of industrial products or identification of parts In the future, with the development of IoT wearable devices and the trend of energy saving, the size of optoelectronic components will continue to shrink This technology can be applied to the detection of defects in the appearance of other tiny optoelectronic components in the future