Taiwan Food Bank AssociationHereinafter referred to as 'the Association'With the mission of providing food aid, poverty relief, reducing food waste, and building a hunger-free network, there are locations across Taiwan that gather donations from wholesalers, intermediaries, retailers, manufacturers, and even generous individuals These sites also rescue food that would otherwise be discarded, properly allocate and distribute it to needy households, thus aiding local vulnerable families55Food banks at various locations collect daily donations from wholesale stores, intermediaries, retailers, manufacturers, and even benevolent individuals from all over Taiwan These places also rescue about-to-be-discarded edible materials, properly sort them, and distribute to needy households, assisting local vulnerable populations However, each location requires significant human and volunteer resources to manage daily operations using traditional methods of communication with non-profit organizations and donors After receiving donations, these resources are then allocated to needy families or individuals There is a potential issue of uneven distribution of resources due to a lack of digitalization and integrated information management in these processes Warehouse and Transportation Centers and Mini Food Banks Distributing Resources to the Disadvantaged The location under validation by the Kaohsiung Charitable Organizations Association,Hereinafter referred to as 'Kaohsiung Charity' In109year6month24Officially inaugurated Taiwan's first 'Food Bank-Warehouse and Transportation Center' at a location measuring200square meters, enhancing the efficiency of food resource redistribution, proper storage, and management So far, nearly two hundred tons of vegetables and fruits have been saved, serving over a hundred organizations and benefiting over5thousand vulnerable households, and continues to serve19mini food banks, with planned completion across multiple districts in Kaohsiung, distributing food resources to over10ten thousand vulnerable families Kaohsiung Charity 'Food Bank-Warehouse and Transportation Center' in the Dasha Community Photo Source Kaohsiung Charitable Organizations Association Challenges in Labor and Food Resource Management Facing the needs of a large number of economically disadvantaged families, the management of the 'Food Bank-Warehouse and Transportation Center' is particularly critical During procurement, tasks such as sorting, purging, and bookkeeping must be performed, while during shipment, food resource needs suggested by social workers must be followed These activities rely on manual judgment and accumulated experience Many volunteers involved are elderly and have limited physical strength, making warehouse tasks physically demanding and recruitment challenging If a large batch of food resources arrives, space and manpower are consumed in sorting and inventory management, raising concerns about the effective use of resources and turnover rate This highlights the challenge of scaling up food bank services while lacking corresponding labor and material management systems At the same time, food bank resources come from various donations, thus they vary greatly in type, shelf life, standards, and quantity Volunteers at mini food banks, mostly also elderly, must handle multiple responsibilities such as case services, food resource management,resource allocation, and resource development Sometimes they must also explain and accept immediate, large quantities of specific resources, such as adults receiving baby formula 'Food Bank-Warehouse and Transportation Center' Resource Inventory Relies Entirely on Manual Labor Mini Food Bank Volunteers Handle Multiple Responsibilities Photo Source Taiwan Food Bank Association Reducing Scrap Resources60 Increasing Speed of Resource Transfer80 To enhance resource management and ensure effective use of materials, and to address personnel shortages, this field validation case has introduced 'Food Bank Warehouse Resource CollectionAITo advance resource management, ensure effective use of resources, and solve manpower shortages, this validation site has implemented an 'Automated Early Warning Needs Assessment System' for the food bank's warehouse resource gathering The first part involves building a classification model, setting up and collecting warehouse information at the site, andAItraining the model Past sitewarehouse information is collected and stored in a database, allowingAIfor preprocessing, classification, and other tasks At the same time, depending on the dependency conditions of the types of goods as features, algorithms are introduced for computation and modeling, and the data collected is used for retraining, ultimately validating the field and organizing data for the five most common types of goods into training and test datasets as required The second part involves constructing the classification model using AI techniques further use of reinforcement learning constructs the management mechanism for the food bank's warehouse, perfecting the classification of donated goodsRNNTechnical construction of classification models further use of reinforcement learning constructs food bank warehouse management mechanisms, making the classification of donated goods perfectlike white rice, instant drinks, noodles, instant noodles, and canned goodscan then be automatically assigned storage based on storage assignment principles AI Service System Process and Description Source Taiwan Food Bank Association AtAIUnder forecasts, it can optimize the speed of resource transfer and allocation, effectively and accurately match resource donations reducing the loss in the donation process, increase the accuracy of resource distribution, and improve the service rate—the successful donation rate—reducing the waste of resources due to incorrect items, and enabling instant monitoring of food resource stock, ensuring operators can respond quickly to needs, effectively providing resource assistance WithAIthe system's introduction and the establishment of data intelligence, it helps the operations of the warehouse and transportation center, allowing more time for the allocation of donated goods The introduction aims to accelerate the digital service rollout for social welfare organizations, thoroughly addressing the needs of the overall vulnerable segments of society Using the system for resource allocation and dispatching Photo Source Kaohsiung Charitable Organizations Association Following this field validation, it is possible to expand the system to other food bank service pointsAIThe system can also collaborate with more non-profit organizations, public welfare groups, and charitable organizations, expanding 'Food Bank Warehouse Resource CollectionAIAutomated Early Warning Demand Assessment System' application range such as medical supply distribution, helping more organizations manage and distribute more intelligently, reducing resource wastage, and enhancing social welfare 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-12-12」

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」

Although satellite remote sensing images can make all surface objects visible, it still requires a lot of time and manpower to be truly applied to the industry In order to effectively solve the problems that customers face in digesting huge amounts of image data and eliminate technical obstacles for cross-domain users to process satellite remote sensing images, ThinkTron has developed an "AI Analysis Cloud Service Platform for Remote Sensing Big Data" as a new beginning for cross-domain AI applications for spatial information In recent years, in response to the impact of industrial globalization, Taiwan's agriculture has continued to transition towards technology-based and higher quality, improving the yield and quality of crops by solving problems, such as microclimate impacts and pest and disease control The demand of agriculture on images has expanded endlessly to accurately grasp the growing environment of crops In the early years when UAVs unmanned aerial vehicles were not yet popular, manual field surveys were the most basic but most labor-intensive work With the emergence of UAV drones, aerial photography operations might not be difficult, but the range that can be photographed is limited Furthermore, surveying expertise is required to accurately capture spatial information At this time, the use of satellite remote sensing data may break away from the past imagination of using image data Taiwan Space Agency TASA ODC data warehouse services In the past ten years, with the breakthrough of modern satellite remote sensing application technology, Digital Earth has become a new trend in global data collection Countries have developed data cube image storage technology, and the development of smart agriculture has become one of the largest image users Determining planting distribution is the first step in understanding crop yields Free satellite remote sensing images, powerful data warehousing support, and the team's robust image recognition technology are important supports for accelerating agricultural transformation Using satellite remote sensing image data can accelerate the development of smart agriculture However, in the past, it was difficult to extract large-area crop distribution through satellite remote sensing images, not to mention the cost If you wanted to use free information, you had to visit all websites of international space agencies, look through the wide variety of satellite specifications, and carefully evaluate the sensor specifications, image resolution, and revisit cycle After finding suitable images, you had to look at them one by one to filter the ones you need Next is downloading dozens of images that are often several hundreds of Megabytes MB each, which might exceed the capacity of your computer Also, after overcoming image access and preparing data, you must then start to confirm the downloaded image products and which bands you want, because the image you see is not just an image file jpg or png, but rather complex multi-spectral information, attribute fields and coordinate information It takes a lot of effort just to confirm the correct information Facing GIS software packages with complex functions is the start of another trouble The complex image pre-processing process and the inflexible machine learning package greatly reduce the efficiency of analyzing data After finally getting the results of crop identification, you might find that the best time for using map information may have already passed The above-mentioned complex and time-consuming satellite image processing problems are precisely the pain points of the market ThinkTron expanded from traditional machine learning to modern deep learning applications, and developed an "AI Analysis Cloud Service Platform for Remote Sensing Big Data" under the GeoAI framework, breaking through the constraints of details in the spatial information for customers Differences between the process before and after introducing the AI analysis cloud service platform ThinkTron said that Taiwan's ODC Open Data Cube system has been completed and began providing services after years of efforts from the Taiwan Space Agency TASA, formally becoming aligned with international trends The powerful warehousing technology allows users to easily capture and use image data of a specific time and spatial range according to their needs The warehouse stores multiple satellite image resources from international space agencies, including the ESA's Sentinel-1 one image every 6 days, Sentinel-2 one image every 6 days, USGS's Landsat-7 one image every 16 days, Landsat-8 one image every 16 days, and the domestic Formosat-2 one image every day and Formosat-5 one image every 2 days ThinkTron develops satellite image recognition tools based on Python Breaking free from the limitations of GIS Geographic Information System software packages, ThinkTron integrated GDAL Geospatial Data Abstraction Library based on Python, and considered computing efficiency and parallel processing when developing all tools required for satellite image processing and image recognition modeling, including coordinate system and data format conversion, grid and vector data interaction, and data intra-difference and normalization All of the tools are designed with AI applications in mind, and some commonly used tools are packaged into an open source package under the name TronGisPy to benefit the technical community ThinkTron utilized the team's understanding of satellite remote sensing images and the collected tagged data crop distribution maps to preset the image recognition modeling process, the required training data specifications, and dataset definitions This is imported into the machine learning LightGBM or deep learning CNN framework that was completed in advance, and the entire training process to be performed in the Web GIS interface, providing users with partial flexibility to freely filter images, confirm spatial and temporal ranges, select models, and adjust hyperparameters In addition to the operation of training models, it also provides historical models to output identification results, and finally displays the identification results of crop distribution on the Web GIS map In fact, agriculture is not the only industry that needs satellite remote sensing applications AI applications of spatial information have also appeared in various fields as companies in different industries aim to enhance their global competitiveness For example, surveying and mapping companies that have a large amount of map data can use the AI analysis cloud service platform to store map data while also accelerating the efficiency of digital mapping Under the severe global climate change and the risk of strong earthquakes, there is a wide variety industrial insurance, agricultural insurance, financial insurance, or disaster insurance are all inseparable from spatial information The use of remote sensing image recognition to understand insurance targets has long been an international trend AI Analysis Cloud Service Architecture for Remote Sensing Big Data