Have you had your morning coffee yet Over the past decade, Taiwan has gradually formed a coffee drinking culture With the advancement of AI technology, autonomous coffee roasters can now rely on AI for precise location setting while also cultivating a loyal customer base Let's see how this is done According to the International Coffee Organization ICO, Taiwanese consume approximately 285 billion cups of coffee annually, with the coffee market in Taiwan estimated at 80 billion TWD, growing about 20 each year In recent years, the 'drinking coffee' culture in Taiwan has become synonymous with popularity, with coffee being the most frequently chosen daily beverage by 65 of the population Coffee enthusiasts, particularly the more avid ones, are willing to pay more for coffee beans that suit their tastes An increasing number of unmanned drink kiosks have also begun to appear in the Taiwanese beverage market Unmanned coffee beverage shops face difficulties in expanding quickly, primarily due to two major issues one is the appropriateness of customer flow and machine placement locations which still rely on manual analysis the second is penetrating the market of mid to high-end coffee lovers accurately AI resolves two major challenges for autonomous coffee roasters suitable placement and cultivating a loyal customer base To tackle these issues and help autonomous coffee roasters quickly break into the market, Raysharp Electronics intends to implement AI for people flow counting analysis and unfamiliar face recognition These technologies aim to calculate the crowd size at potential roaster locations and classify consumers by gender and age for more precise market analysis They also provide multiple choices for the roasting of raw coffee beans, offering a more customized service tailored to the needs and tastes of professional coffee aficionados with a pack of 'high-quality roasted beans' Since 2018, the rise of unmanned stores has been mainly due to owners wanting to reduce persistently rising rent and personnel costs However, the initial assessment of store locations still requires hourly labor expenses for manual estimation of customer flow, leading to possible miscalculations of both on-site consumers and passerby traffic These inaccuracies may prevent precise real-time analysis of customer flow, or even misguided estimations of operational efficacy after a trial run, thus missing the optimal timing for loss-preventing location retraction Raysharp Electronics introduces autonomous coffee roasters equipped with AI-based people counting analysis and facial recognition Raysharp Electronics combines AI people counting analysis and facial recognition with the coffee trend known as 'black gold', addressing the preferences of numerous coffee connoisseurs in Taiwan who enjoy personally selecting coffee beans at bulk stores and frequenting high-quality grinding cafes or chain coffee shops A new concept for the first autonomous coffee roaster offering choices based on the origin, variety, and roasting methods of coffee beans has emerged AI coffee roasters enhance customer loyalty and materials management efficiency by 20 For the advanced development of autonomous coffee roasters, Raysharp Electronics engineers have equipped the AI NVIDIA development platform on the basis of TCNNFacenet Through AI, tens of thousands of images related to gender and age are used for sample training, allowing even first-time coffee roasting customers to be easily classified using unfamiliar face recognition This gains consumer trust, enhances willingness to use, and allows for recording purchase information and future product recommendations, leading to consumer purchase behavior analysis This information helps owners tailor future material preparation based on consumer preferences for different coffee beans, reducing raw material transportation and storage issues, and improving material management efficiency by 20 Moreover, by placing these autonomous coffee roasters in high-traffic areas, owners can use cameras to capture the crowd and assess whether the machine location has an adequate customer base, quickly analyzing whether to reposition the machines, and more easily targeting the best locations for middle and high-end coffee lovers The unmanned coffee roaster features a professional roasting mode interface, providing options based on the origin and variety of coffee beans, their roasting methods light, medium, deep, and related temperature, wind speed, and timing settings If improvement needs arise during the process, engineers can adjust firmware parameters and also assist in integration with the owner's ordering system Staff members briefly describe the operation of the autonomous coffee roaster 'Black Gold' penetrates deeper into coffee shops, science parks, and commercial buildings through AI This autonomous coffee roaster targets coffee connoisseurs and can be placed in middle to high-end coffee shops to roast more customized coffee beans than those available in bulk stores Upon completing a batch of coffee beans, it immediately provides them to professional technicians within the coffee shops for grinding and manual brewing The remaining roasted beans can also be taken home for brewing and enjoyment It also adds value to coffee shops by better understanding consumer preferences for coffee beans and launching more customer-attracting drink promotions and appropriate inventory management In addition to coffee shops, the autonomous coffee roaster can also utilize AI-based people counting analysis to precisely set up near scientific parks and commercial buildings, offering high-quality coffee beans for office brewing to internal employees with high coffee consumption needs Furthermore, implementing a physical membership system can initiate coffee bean purchase promotions or periodic payment incentives, thus attracting new clients and cultivating existing customer loyalty and retention The operation interface of the smart autonomous coffee roaster「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

In recent years, global climate change and environmental issues have become increasingly severe, causing major impacts on agricultural production Traditional agriculture heavily relies on weather conditions, facing challenges such as unstable crop quality, plummeting yields, and difficult pest control Particularly in Taiwan, agricultural biotech companies and farmers have suffered continuous losses, creating an urgent need for innovative solutions Meanwhile, Taiwan's plant factory industry faces many challenges high equipment and labor costs, an incomplete industrial chain diminishing international competitiveness, and a lack of cooperation among enterprises, all of which limit industry development Additionally, COVID-19the pandemic has highlighted the importance of remote monitoring and management Traditional manual inspections and data collection methods no longer meet the needs of modern agricultural production These issues collectively underline the urgent need for smart agricultural solutions, driving companies like Taiwan's HaiBoTe to develop innovative projects integrating IoT, cloud computing, and artificial intelligence technologies HaiBoTe Cloud Data Integration and Analysis Platform Facing these challenges, the agricultural sector urgently needs a system that can precisely control growth environments, improve resource efficiency, enable remote monitoring, and facilitate intelligent management Existing plant factory equipment often requires complete replacement, with poor compatibility with older equipment, and sensors and camera systems may require different interfaces, making them inconvenient to use Therefore, there is a need for a flexible solution that can integrate various equipment and technologies, providing real-time monitoring and data analysis, and automatically adjusting environmental parameters based on plant growth conditions This demand exists not only in Taiwan but is also a global trend in the development of smart agriculture By incorporating artificial intelligence, more scientific evaluation standards can be established, optimizing production processes, improving yield and quality, while reducing energy consumption and environmental impact Additionally, such smart solutions can attract more young people to participate in agricultural production, promoting industry upgrading and sustainable development Overall, the demand for smart agricultural solutions stems from the urgent requirements to address climate change, enhance production efficiency, reduce costs, and achieve precise management, and this is exactly the problem companies like Taiwan's HaiBoTe are striving to solve Taiwan's plant factory operators are facing a series of severe challenges, which are gradually eroding their competitiveness and survival space Firstly, the high cost of equipment and operations is their biggest burden Each electricity bill feels like a heavy blow, forcing them to balance between ensuring product quality and controlling costs Secondly, the unpredictability brought by climate change has become their nightmare Sudden extreme weather events can destroy their carefully nurtured crops in a short time, causing massive economic losses What's worse, they find themselves increasingly at a disadvantage in international market competition In contrast, large overseas plant factories, with their advanced automation technology and well-organized supply chains, can produce stable-quality agricultural products at lower costs, putting unprecedented pressure on Taiwan's operators On the technical level, they also face numerous challenges Compatibility issues between new and old equipment often put them in a bind, encountering various technical obstacles when trying to integrate different systems Lack of precise data analysis and forecasting capabilities also makes it difficult for them to make production decisions and accurately determine the best growth conditions for each crop Existing monitoring systems provide data that is often disorganized, difficult to interpret and apply Human resource challenges are also severe, with young people generally lacking interest in agricultural work, making it difficult for them to recruit employees with modern agricultural skills Even existing employees often feel exhausted from tedious manual operations and monitoring tasks These problems are intertwined, creating a complex dilemma that leaves plant factory operators confused and anxious They urgently need a comprehensive solution that can enhance factory operational efficiency, reduce costs, and improve product competitiveness, helping them overcome difficulties and regain their footing in the fierce market competition In facing the various challenges of plant factory operators, Taiwan's HaiBoTe company has demonstrated exceptional technical innovation and a flexible customer-oriented development strategy They deeply understand that the solution must be able to seamlessly integrate existing equipment while providing highly intelligent management functions To this end, HaiBoTe's RD team adopted a modular design approach to develop a system that can be flexibly configuredIoTIoT system The core of this system is a smart control hub that can communicate with various sensors and actuators During development, HaiBoTe worked closely with customers, deeply understanding their specific needs and operational environments They even dispatched engineers onsite to observe the daily operations of the plant factories, ensuring that the developed system actually solves practical problems This in-depth cooperation not only helped HaiBoTe optimize their product design but also established a close relationship with customers, laying the foundation for subsequent continuous improvements HaiBoTe's innovation is not just reflected in hardware design but also in their developed intelligent software system This system integrates advanced machine learning algorithms, capable of precise forecasts and optimal control of plant growth conditions based on large amounts of historical data and real-time monitoring information To help customers overcome technical barriers, HaiBoTe designed an intuitive and easy-to-use user interface, which even non-technical operators can master easily Additionally, they provide comprehensive training and tech support services, ensuring customers can fully utilize all functions of the system When facing challenges, HaiBoTe's technical team can quickly identify problems through remote diagnostics and provide solutions In one incident, during a serious equipment failure emergency faced by a customer, HaiBoTe's engineers guided the customer through system remote access, successfully instructing them on repairs and avoiding potential massive losses This full-range service not only solves customers' immediate difficulties but also strengthens their confidence in intelligent management, driving the entire industry toward more efficient and sustainable development HaiBoTe's developed smart agriculture solution not only brought revolutionary changes to plant factories but also painted an encouraging picture for the future of the entire agricultural industry The excellence of this system is evident in several aspects firstly, it achieves precise control of the plant growth environment, significantly improving crop yield and quality stability Through advanced artificial intelligence algorithms, the system can forecast and adjust optimum growth conditions based on historical data and real-time monitoring information, ensuring each plant grows in the ideal environment Secondly, it significantly reduces energy consumption and operational costs, improving resource efficiency The intelligent management system optimizes water, electricity, and nutrient supply, reducing waste and lowering manpower costs Additionally, the system's modular design and strong compatibility allow it to seamlessly integrate various new and old equipment, providing a flexible solution for gradual upgrades of plant factories Most importantly, the system injects a sense of technology and modernity into agricultural production, helping to attract the younger generation to the field and injecting new vitality into the industry Looking ahead, HaiBoTe's smart agriculture system has broad application prospects and expansion potential In addition to plant factories, this system can also be applied to traditional greenhouse cultivation, urban agriculture, and even home gardening In the field of aquaculture, similar technology can be used to monitor and optimize the breeding environments for fish or shrimp In the food processing industry, similar intelligent monitoring and forecasting systems can be used to optimize production processes and enhance food safety Even in the pharmaceutical industry, this type of precise environmental management system could be applied to drug research and production processes To further promote this system, HaiBoTe could adopt a multifaceted strategy Firstly, they could collaborate with agricultural colleges and research institutions to establish demonstration bases, allowing more people to experience the benefits of smart agriculture firsthand Secondly, they could develop customized solutions tailored to different scales and types of agricultural production, expanding the applicability of their products Furthermore, they could raise awareness and acceptance of smart agriculture within the industry by hosting forums, online seminars, and sharing success stories Lastly, they could explore collaborations with government departments to integrate this system into policies supporting the modernization and sustainable development of agriculture, thereby promoting the widespread adoption of smart agriculture on a larger scale Through these efforts, HaiBoTe not only can expand its market share but also make a significant contribution to the sustainable development of global agriculture, truly realizing the vision of technology empowering agriculture 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-12-09」

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」