Handling abnormal complaints requires extensive experience and expertise. However, the resignation or retirement of senior employees often leads to knowledge loss, impacting organizational efficiency and competitiveness. Through vector models, Morale AI transforms unstructured data (such as emails, PDFs, and Word documents) into structured data and integrates it into databases, enhancing data usability. Multi-modal models combine diverse data types, including text and images, to systematically record and preserve experience. By leveraging Retrieval-Augmented Generation (RAG) technology and similarity search, the model can accurately categorize issues, identify the root causes, and recommend relevant cases, significantly reducing manual processing time and error rates. This systematic approach not only enhances response efficiency and enables real-time analysis and resolution of customer issues but also reduces repetitive work for employees, improving overall productivity and customer satisfaction.

This project uses the 阡陌(QianMo) System, which drawing the road profiles, markings, signs, and signals based on the road geography data as a universal base map, to integrate cross-domain digital applications. Besides, 阡陌(QianMo) System has developed an application on mobile phone, through this application, user can complete the case opening, drawing, conversation recording, and photo-taking operations on-site, and convert the accident cases into collision elements in accordance with time, vehicle type, direction, collision type, and number of casualties. On the other hands, when handling improvements for accident-prone intersections, 阡陌(QianMo) System can overlay the elements to implement the collision composition analysis serves as a scientific proof and visualization tool for researching traffic improvement measures and explaining accident risk hotspots. Besides, after the subsequent engineering improvements, user can provide revision of road geography data as the feedback. Through this mechanism, which can achieve a digital governance cycle. Finally, through 阡陌(QianMo) System , this project integrates cross-domain applications related to police administration, transportation bureau, and engineering industry to improve driving environments and prevent traffic accidents.

RiChitech has pioneered integrating generative AI models with GIS drawing technology, developing the generative smart map drawing module—geoAI Maker. This module is designed for users with many spatial description documents and graphic information but cannot identify locations and create maps. geoAI Maker can automatically recognize text and images, parse various types of spatial descriptions (such as addresses, landmarks, and range information), and further convert the content into GIS spatial coordinates, automatically generating vector maps. This process fully leverages the powerful capabilities of generative AI, allowing users to immediately utilize advanced analysis and visualization displays, helping various industries solve and accelerate the processing of spatial data.

Yunlin County Government is dedicated to establishing a human-centric smart agriculture, providing services for digital and green transformation to overcome industry challenges and climate change. People collaborate with machines, automation equipment, and computers to enhance industrial productivity by using information technology. Simultaneously, it promotes Intelligence Augmentation (IA), fostering the growth of industry personnel capabilities. To accelerate agricultural transformation, solutions are developed with experts in various fields of agriculture and livestock. Through sharing successful case studies, the aim is to guide industry stakeholders to embrace new knowledge and technologies. Additionally, counseling teams assist farmer groups in transitioning towards a smart agriculture concept that combines 'smart technology' and the 'net-zero emission' approach. The development focuses on creating a future agriculture model primarily based on automation and AI, striving for efficiency, quality, and Intelligent Automation (IA).The project won the 2024 Smart City Innovation Application Awards.

By leveraging AI digital twin models, we predict KPI performance to support decision-making for backup machine selection, enabling energy savings and operational efficiency. Explainable AI is used to analyze the parameters influencing KPI, revealing that air compressor efficiency is strongly correlated with its shaft bearings, highlighting the importance of predictive maintenance for these components. Additionally, an intuitive dashboard visualizes the relationship between demand and supply data, facilitating real-time decision-making and responsiveness. With the integration of LLM Agents, users can communicate seamlessly with digital twins through natural language, enhancing usability and interaction efficiency.

There are increasing demand for self-service and remote-control devices.Besides safety reason, it is also easier for customers to purchase tickets and obtain travel information, plus the added benefits of time saving and convenience. MiTAC’s Smart ticketing solution for tourism was implemented at “Hạ Long Bay” in Vietnam. Passengers can use self-service devices, such as the Ticket Vending Machines, kiosks and POS to purchase tickets, place orders, arrange trips and inquire for additional information. The operators can also utilize automated devices and information system to reduce human resources investment, strengthen operational efficiency, and improve service quality. In addition, the operators can utilize the data collected for big data analysis for precision marketing in the future.

The accounting system will automatically send reminder bills via Line and Email. The payment account supports online cash flow and offline payment. If you use a bank account that cooperates with JGB, it will have a 24-hour automatic reconciliation function. The tenant will immediately remit the payment. Notification, say goodbye to the daily routine of Excel reconciliation.

AI Image Recognition (Intelligent Storage): Install surveillance cameras in the warehouse campus to accelerate the identification speed of AI Intelligent Image Analysis System through 5G network, and assist the management of the enterprise campus. AR Remote Equipment Maintenance: Use a 5G network to enable field workers to communicate with remote experts through AR smart glasses and simultaneously initiate multi-party video collaboration. Light A.I. Virtual Guard: Replace traditional human monitoring with AI cameras, connect to the cloud in 5G for real-time image recognition, and achieve real-time alerts via monitoring platforms and mobile app. AGV/AMR applications: Use 5G wireless connectivity technology to move cargo to designated picking stations and communicate with other equipment in the field to improve efficiency and reduce labor costs.

By applying environmental sensing IoT technology and mobile sensors, the coverage of sensing can be significantly enhanced. With the analysis through AI algorithms, it assists governments in identifying potential sources of pollution for regulatory actions and pollution reduction measures. Meanwhile, supplemented by generative AI innovation technology, it achieves smart environmental governance.

The Smart Mobility Solution is best fit for 2 industries: (1) With the occurrence of service demand, the service provider take requests that are to fulfill in limited time. Company such as ride-sharing, food or grocery delivery, professional services(car washing, garbage recycling, house maintenance, roadside assistance, etc., (2) Are required to deliver multiple shipments by 2/4 wheelers to destination at the same time. Factors such as specified time, locations, travel intervals, oil consumption, travel distance, are to be considered. A logistic company is the target audience under the scenario. The Smart Mobility Solution takes account of all possible concerns that the 2 industries encounter daily. With its unique AI algorithm, ETA data, etc., From the moment when the consumer inputs the address, the routing, distribution, delivery, records, optimization, all progress is assisted by 2-5 API tools. During implementation, industries are accompanied by Google premium partner Master Concept. Industries are expecting 1. Enhance to consumers and drivers experience 2. Increase to delivery efficiency 3. Cost saving to manpower and vehicles 4. Achieve ESG goals.

This project establishes a 5G private network in rural Tainan schools, introducing AR/VR gamified English teaching. Students engage in scenario-based games, simulating English conversations in virtual reality, fostering entertaining and interactive learning. The curriculum incorporates famous global landmarks and utilizes AR technology for checkpoint missions, enhancing student interest. Beyond English education, the initiative collaborates with the National Palace Museum, integrating AR/VR historical artifacts. Using 5G streaming, historical content is seamlessly integrated into campus teaching. The project not only enhances learning outcomes in rural junior high schools, reducing the urban-rural digital gap, but also has the potential for nationwide expansion. Through cross-disciplinary collaboration, it drives the development of both horizontal and vertical industry chains.

The Smart Dust Sensor technology is an innovative solution for integrating IoT networks into air quality monitoring. Developed collaboratively by the National Science and The National Science and Technology Council (NSTC), in collaboration with Taiwan Instrument Research Institute (TIRI) and Taiwan Semiconductor Research Institute (TSRI) of NARLabs, and leading academic teams in Taiwan, this technology has successfully miniaturized gas sensors while achieving low power consumption and high sensitivity. Its core features include exceptional sensitivity and stability, enabling real-time monitoring of multiple gases. Moreover, the fully domestically developed technology reduces dependence on imports and offers cost-effective sensor modules, driving the widespread adoption of air quality monitoring devices. The Smart Dust Sensor has undergone extensive field testing and third-party certifications across various applications. These include environmental monitoring stations (e.g., Taichung Dali Station), public recreational areas (e.g., odor monitoring in public restrooms), and industrial settings (e.g., semiconductor facilities and wastewater treatment plants). With its proven accuracy, reliability, and traceable data, the technology plays a key role in advancing air quality monitoring solutions, facilitating the development of smart cities, and contributing to improved environmental management.