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【2019 Solutions】 NexCOBOT - Smart Self-Checkout System Makes Future Shopping Convenient

Imagine a future where all shops have no clerks, fully replaced by smart devices. Simply placing items on the table and letting the intelligent self-checkout system handle the rest makes shopping convenient and easy. This scenario is not far-fetched, as unmanned store projects have already emerged in Taiwan, such as the recent multi-million investment by FamilyMart to create their second tech-concept store. Through human-machine collaboration and the latest technology, they aim to alleviate clerical work, and NexCOBOT hopes to bring this concept into unmanned stores to simplify the checkout process for consumers.

▲ NexCOBOT introduces a smart self-checkout system, aiming to incorporate this technology into unmanned stores, simplifying the checkout experience for consumers.

Dedicated to smart retail solutions to enhance consumer technology experience

NexCOBOT, a subsidiary of NEXCOM, specializes in the independent development of six-axis robots and smart retail solutions. With the rise of the Internet of Things, the line between physical and virtual commerce has blurred. NexCOBOT identifies three foundational elements of IoT commerce: smart retail, smart logistics, and cloud-based real-time management systems. Continually, NexCOBOT commits to smart retail solutions, addressing major pain points for business owners while considering enhanced technological experiences for consumers, hoping to pioneer unprecedented innovative applications.

NexStore machine displays the initial screen and confirms user identity
▲ When it's time to check out, simply place the items on the table, and a scanner will identify the products and display both the items and prices on the screen.

How does NexCOBOT's smart self-checkout system work? When checking out, place the shopping cart's items on the table. An overhead scanner performs image recognition, then the screen displays the types of products and the amounts. Payment can then be made using cards, smartphones, or other payment devices. It can even integrate with facial recognition systems, allowing customers to pay through face scanning, which saves the time previously spent scanning barcodes and queuing. Additionally, the store can utilize backend analyses to track customer data and popular products.

NexStore machine interface completes scanning food items, confirmation stage diagram
▲ Due to the need for precise image scanning, a detailed product database must be established beforehand. The store can also analyze customer data and popular items through backend analytics.

Establishing a product database to gain control of product information

Precise image scanning requires that all items have a previously established database. Scanning could include detailed 3D images of merchandise like cookie boxes or drink cans. The more detailed the database, the faster the checkout process and the more effective the backend analytics. However, because of limited space on counters, scanning large volumes of merchandise could be problematic. Initially, items easily recognizable (like those in bakeries) might be prioritized. Additionally, NexCOBOT offers modular solutions such as smart shelves, smart self-order systems, smart self-checkouts, smart marketing dashboards, etc., all customizable as per the client's requirements. Integration with existing systems such as Point of Sale (POS), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Digital Signage is also feasible.

▲ Besides using payment devices, it can even integrate with facial recognition systems, allowing customers to pay through facial scanning, eliminating the need for manual barcode scanning.

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

Recommend Cases

【解決方案】2秒鐘完成結帳動作 Viscovery AI影像辨識助攻智慧零售
Complete checkout in 1 second, Viscovery AI image recognition assists smart retail

Artificial intelligence AI has gradually changed the way various industries operate in recent years However, most of the work is still done by humans, with AI playing a supporting role This has led to emergence of the term "AI Copilot," which stands for "AI-driven tools or assistants" that aim to assist users in completing various tasks and improve productivity and efficiency The concept of AI Copilot comes from the role of "co-pilot" During flight, the co-pilot assists the main pilot in completing various tasks to ensure flight safety and efficiency In fact, there have been signs of various "machines" beginning to play the role of "copilot" in different fields since the Industrial Revolution, assisting humans in completing heavy physical and repetitive tasks, greatly improving factory production efficiency, and driving rapid economic development Following the advancement of computing equipment and breakthroughs in machine learning, deep learning, and image recognition technologies, the concept of AI Copilot has gradually taken shape The development of AI Copilot marks the transition from "machine-assisted to AI-assisted" Early robots could only complete preset repetitive tasks, but today's AI copilot can learn and adapt to new environments and tasks, and continuously optimize its performance in practical applications This transformation not only changes human-machine interactions, but also has a profound impact on various industries The application scope of AI copilot covers various industries, including finance, healthcare, manufacturing, education, retail, etc, and are everywhere to be seen Application of AI copilot in the retail industry AI image recognition checkout In the retail industry, the application of AI copilot has begun to show concrete results Take Viscovery's AI image recognition checkout system as an example This system is a type of AI copilot model that helps store clerks speed up checkout or assists consumers in simplifying the self-service checkout process The store clerk needs to scan the product barcodes one by one in the regular checkout method If a product does not have a barcode, such as bread and meals, the clerk needs to first visually confirm the items, and then input them into the POS checkout system one by one Based on actual measurements at a chain bakery, it takes 22 seconds for an experienced clerk from "visual recognition" to "entering product information of a plate of 6 items into the checkout system" New clerks may need even more time In addition, according to a Japanese bakery operator, it takes 1 to 2 months to train employees to become familiar with products Now with AI image recognition technology, store clerks let AI handle the "product recognition" step, and AI will play the role of copilot, quickly identifying items within 1 second, speeding up checkout to save 50 of checkout time, and optimizing customers'shopping experience The time cost of training employees to identify bread can also be effectively shortened Even for products with barcodes, AI can quickly identify multiple items in one second, which is more efficient than scanning barcodes one by one The self-checkout system "assisted" by AI image recognition allows consumers to successfully complete shopping without the help of store clerks, eliminating the trouble of swiping barcodes or searching for items on the screen, which improves the shopping experience In a time when store clerks are hard to hire due to labor shortage, this also helps stores reduce operating costs AI quickly identifies multiple checkout items in just one second Source of image Viscovery Recently, startups dedicated to developing AI image recognition checkout solutions have emerged in various countries The most lightweight solution currently known is in Taiwan It can be immediately used by installing a Viscovery lens and a tablet installed with Viscovery AI image recognition software at the checkout counter to connect to the store's existing POS checkout system There are various integration methods, including plug-and-play and API solutions integrated with the store's POS system Viscovery AI image recognition system can be painlessly integrated with the store's existing POS system Source of image Viscovery Example of AI image recognition checkout Currently, the Viscovery AI image recognition system is being used in bakery chains in Taiwan, Chinese noodle shops in Singapore, micromarkets in department stores in Sendai, Japan, and Japanese bakeries and cake shops Over 7 million transactions were completed through this AI system, which identified more than 40 million items These use cases demonstrate the extensive application of the Viscovery AI image recognition system in the retail industry In the future, the company will continue to explore the various possibilities of using Vision AI in retail and catering nbsp The Viscovery AI image recognition system is already being used in bakeries, cake shops, restaurants, and convenience stores in Japan, Singapore, and Taiwan Source of image Viscovery

【解決方案】7毫秒內分離人聲 洞見未來科技協助聽損者「聽說更簡單」
Voice Separation in 7 Milliseconds: RelaJet's Future Technology Makes 'Hearing and Speaking Easier' for the Hearing Impaired

One rainy Thursday afternoon near Taipei Arena, the Taipei Experience Center of RelaJet was fully booked with appointments from people with hearing loss eager to try hearing aids made with a voice separation engine For the hearing impaired, having affordable, lightweight, and effective noise-reducing hearing aids is truly a blessing 'We hope to help users in need to hear the world's wonders again' This empathetic expectation by RelaJet's founder and CEO Po-Ju Chen, who is also hearing impaired, illustrates his understanding of the needs of the hearing impaired He hopes that RelaJet's unique voice amplification hearing aid technology will benefit many more people Affordable hearing aids benefit many with hearing loss Founded in 2018 by Po-Ju Chen and his brother Yu-Ren Chen, RelaJet developed a multi-voice separation engine paired with Qualcomm's Bluetooth audio platform, drastically reducing the price of imported hearing aids, typically costing 80,000-100,000 NT dollars, to just under 10,000 NT dollars They aim to develop affordable goods with excellent noise-cancelling capabilities that wirelessly connect to smartphones In its first two years, the company primarily developed the multi-voice separation engine, which significantly improved the noise reduction quality Once equipped with Qualcomm Bluetooth earphone chips, the audio processing time is drastically short, at about 7 milliseconds to enhance main voice projection and reduce ambient noise, less than half the time required by traditional medical standard of 16 milliseconds for hearing aids, nearly 'zero-delay' 洞見未來科技推出平價助輔聽器,大大嘉惠聽損者 Yu-Ren Chen explains that the primary use of Qualcomm chips for edge computing, along with a streamlined algorithm, achieves extremely low latency and better noise reduction The hearing aids can cover 18 channels, whereas traditional hearing aids cover 4-48 channels In the future, RelaJet will progressively increase the number of channels According to statistics, there are 470 million people globally with hearing disabilities, with a 30 average device use rate in developed countries, with the highest in Western countries Taiwan has nearly 15 million people with disabling hearing loss, of which the middle-aged and elderly make up 30, yet the device use rate is only about 10, which is quite low Yu-Ren Chen further analyzes that the low device usage rate is due to two reasons firstly, the high average selling price of international big brands ranges from 80,000 to 200,000 NT dollars with a three-year usability period, which deters many due to the high cost and maintenance Secondly, in noisy environments, the noise is also amplified which does not necessarily ensure clarity for the users, and the sound parameters can't be adjusted in real-time, making it inconvenient to frequently visit stores for tuning Thirdly, most models cannot connect to smartphones, making it inconvenient for the hearing impaired to take phone calls Utilizing Qualcomm Bluetooth chips for rapid product development In light of this, Po-Ju Chen, formerly a semiconductor engineer at MediaTek, leads the technical development, while Yu-Ren Chen, with a legal background, manages the operations Their seamless collaboration, along with their team employing AI algorithms and chip integration, learns from thousands of hours of audio files in databases through neural networks and deep learning technologies to develop low-latency, high-noise-reduction voice amplification technologies for hearing aids In 2019, this sound processing technology was integrated into Qualcomm Bluetooth chips, winning first place in the Qualcomm Taiwan Startup Competition and becoming a partner in Qualcomm's Global Expansion Program, significantly boosting product development pace In 2021, they launched their own Otoadd series of hearingenhancement products in Taiwan, which received both market favor and positive reviews from many with hearing loss Based on different consumer needs, various product designs are available According to Yu-Ren Chen, the Otoadd wireless earphones with hearing enhancement functions, model N1, are entry-level neckband style priced at 9,500 NT per pair Users can wear the hearing aid while taking calls, and control noise reduction strength and volume through a mobile app They plan to develop accessories in the future tailored to the needs of older adults Besides being available for trials at experience centers in Taipei and Kaohsiung, this hearing aid is also sold through PChome, Taiwan Mobile's myfone, and Elder Age networks, among other channels Another model intended for individuals with mild to severe hearing loss is the Classic R hearing aid, which received the Japanese Good Design Award in 2021 Since its market debut last year, it has attracted those with congenital hearing loss, with users noting improved clarity in noisy environments and appreciating the convenience of Bluetooth connectivity for calls and watching videos This product is anticipated to be exported to international markets in the latter half of this year Additionally, a hearing aid product combining Bluetooth functionality, set to launch in June this year, is sized like typical Bluetooth earphones, targeting visually conscious consumers with hearing loss Its small size and attractive wireless earphone design allow for phone calls, and if approved by the Ministry of Health and Welfare, eligible users can apply for government subsidies RelaJet to expand into overseas markets, using the USA as a beachhead An interesting question arises due to the pandemic everyone must wear masks which impedes lip-reading How does this affect those with hearing loss Yu-Ren Chen indicates that this situation highlights RelaJet's advantages As each person with hearing loss has different levels of hearing ability, hearing aids can only augment to an appropriate volume, assisting users to hear about 60-70 content, with the remainder relying on lip reading and gestures During the pandemic, as everyone wears masks, masks also muffle sounds, but RelaJet's voice separation engine can correct and strengthen the separation, making it easier for those with hearing loss to recognize voices Besides the Taiwan market, RelaJet's next stage will be expanding into overseas markets, expecting to obtain ISO 13485 medical device quality management system certification and US medical device approval in 2022 They plan to enter the US market, either under their own brand or through OEM arrangements Apart from the Taiwan market, RelaJet will also enter the US market in the next phase for hearing aids「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 Defect Intelligent Detection - Energy Reduction Smart Monitoring Solutions

AIIntelligent Defect Detection-Smart Monitoring Solution to Reduce Process Energy Consumption When there are over2ten thousand chip resistors on a ceramic substrate, how should one quickly detect defects The answer isUsingAIto detect。 In the era of rapid technological development, Leike proudly announces significant advances in its laser processing technology, thanks to the innovative applications of artificial intelligenceAILeike is committed to integrating advancedAItechnology into laser processing machines, and in2019year, in collaboration with partners, developed the world's first laser machining system that integratesAItechnology, and on this basis further developed in2023year the first ceramic substrate inspection machine that integratesAOIAILASERtechnology Smart Ceramic Substrate Inspection Machine Through the introduction ofAIand machine learning, along with the accumulation of big data samples, the system becomes smarter, which has led to improved product yield within one year5dramatically reducing the inspection time from originally2minutesper piece to just20secondsper piece, drastically lowering inspection costs, enabling efficient initial detection and post-laser marking to reduce waste in subsequent processes, diminishing overall carbon emissions of the site, allowing the automatic generation of detailed inspection reports for data analysis and optimization, which helps increase equipment capacity, reduce human error, enhancing the value of Leike's equipment, and strengthening the international competitiveness of the country's electromechanical industry Leike CorporationLaser TekFounded in1988year, and officially listed as a publicly traded company in2002year Since its establishment, it has become a leading global service provider and manufacturer of electronic packaging materials,SMDElectronic Packaging Materials,SMTinspection equipment, and laser systems Leike's general manager, with years of laser integration experience, observed that passive component customers can produce over20With many years of laser integration experience, he observed that the production capacity of passive component customers can exceed10billionSMDcomponents every month, but withSMDcomponents per month However, as component sizes continue to miniaturize, defect detection during production becomes increasingly challenging With thousands to millions of components on a single ceramic substrate, and as component sizes decrease and their laser processing positions become smaller, the difficulty of detection increases, making production inspection a critical process R-SMD Production Inspection Process AOIproblems of yield overkill relying onAIfor oversight, Yet,AOIthe inspection machine is a widespread and mature type, but the high accuracy on the marketAOIuses a technique that captures small images in a single shot and stitches them into a larger image Although accurate, this method requires more time for small-sizedSMDcomponents, which are more likely to be influenced by environmental factors like lighting and vibration that can cause misjudgments as a result,AOIyield rate can only be estimated by sampling, and components with poor sampling yield are not removed individually but discarded together with good ones manual re-inspection not only increases costs, but the lack of unified inspection standards ultimately results in about2-5products that are not detected as defective enter the subsequent manufacturing process monthly at least2,000thousands of such defective componentsSMDthat were not initially detected causing ongoing printing and machining inspections in subsequent processes Regardless of the waste of ink materials and energy, which increases the cost burden, this also accelerates equipment wear and shortens operational life Each stage of waste increases the site's carbon emissions, unfavorably impacting the company's carbon footprint Post-Adjustment Sample Photo Example 0402 TraditionalAOI High false positive rates in Automatic Optical Inspection AOI are a major production issue for manufacturers, particularly in the passive components industry where 'it's better to mistakenly reject a hundred than miss one'—a high standard, often leading to AOI setting extremely high parameters which makes devices overly sensitive Excessive stringency in data parameter settings can lead to high false positive rates For instance, if the dirt contamination on passive components resembles the color of the printing layers,AOI the misjudgment rate could reach 7 percent Contamination Dirt and Print Layer Color SimilarityAOIProne to Misjudgment Raytek stands apart from otherAOIsuppliers by discarding the stitching of small images or line scanning, effectively preventing data loss and discrepancies caused by hardware or environmental conditions during image processing It employs a large-array photodetector coupled with custom high-resolution lenses, using specialized imaging for composite processing Throughout this process, each pixel of the photodetector contains light information captured from various positions By combining this data, the image resolution and detail are enhanced, reaching a resolution of millions, and with multiple automatic light adjustments, a single shot can manage7070mmachieving an image resolution up to5umobtaining clear images, then throughSmart-AItechniques for analysis and selection Three Innovative Methods to Achieve Rapid InspectionSmart -AI Raytek's General Manager shares, rapidly implementingAItechnology and reducing inspection computation time, further developingSmart-AIthree major approaches Method one, initially useAOIto quickly separate good products from those with controversial defects, focusing the detection on the minority of defective identifications Method two, an automated labeling platform simplifies the training issue by using cameras to collect data from machines, automatic labeling replaces manual labeling, progressively training to improve accuracy The simpler the problem, the less data needed for training Method three,AOIandAIDual-track Advancement In the smart manufacturing process, relying solely onAOIorAIis not enough to accomplish the task alone, it must be preceded byAOIfirst marking the characteristics, distinguishing between good and defective parts, then usingAIa method for labeling and training Subsequently, by utilizing a repeating cascade effect, the detection benefits are greater as more training data accumulates,AOIreducing the ratio of errors,AIand gradually increasing the accuracy ratio Post Adjustment Object Detection and Training Through three major methods gradually building system reliability, and categorizing data for defect sorting, ultimatelyAIreturning the judgement results to the main system, utilizing laser machining to control truly defective products at the front end of the process, reducing the inflow of defective products into other stations, thus minimizing losses due to repeated tests or reprocessing Leading in smart laser equipment, chooseLASERTEKthe right one Continuously developed by the Taiwanese brand Raytek, combiningAIsmart detection and laser processing equipment to progressively build a smart monitoring solution stack from raw materials, products, testing, laser equipment, etc, aiming at reducing the energy consumption of the production process, implementing semiconductor advancements, substrates and component processing among other fields, producing equipment products capable of meeting the end-user demands under low carbon conditions, rapidly and with quality products and services expanding both domestic and international markets, enhancing the global competitiveness of localMade in TaiwanMITequipment 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」