Laplace Intelligent Technology's "Akashic Smart Multimodal Report System" is specifically designed for enterprise digital transformation, utilizing cutting-edge AI technology to transform complex data into precise, professional business reports. The system automatically analyzes enterprise information, rapidly generates structured reports, significantly reduces manual writing time, while enhancing report quality and decision-making efficiency. Our solution integrates intelligent knowledge bases with automation technology, helping enterprises optimize operational processes and achieve data-driven precision decision-making in highly competitive markets.

Key Features & Highlights Intelligent Monitoring: Advanced sensors and AI record real-time exercise data, providing actionable insights for precision and safety. Data-Driven Training: Generates personalized plans and dynamically adjusts based on performance. Medical-Grade Reporting: Offers reports with exercise scores, stability evaluations, and improvement recommendations. Smart IoT Connectivity: Enables remote monitoring and data synchronization for smart healthcare solutions. Patented Technologies Eccentric Training Technology (Patent No: I840182): Reduces strain while improving muscle strength, ideal for rehabilitation and sarcopenia users. Maximum Strength Curve Measurement (Patent No: I838256): Dynamically adjusts resistance, enhancing safety and training efficiency. AI-Driven Training Plans: Creates tailored plans in seconds, ensuring personalized and effective workouts. Applications Medical Centers: Assists physicians in improving patient rehabilitation outcomes. Smart Gyms: Provides data-driven, personalized training experiences. Urban Health Systems: Supports public health initiatives through integrated smart solutions.

SONOBA COMET is a paperless conference system using tablet computers. Simple, no complicated operation or preparation required. Convenient, one-person operation, all participants can be expressed simultaneously. Information security, delete the information after the meeting. SONOBA COMET” is a product that has been positively received and implemented by a wide range of customers in different industries and business categories, such as banks and brokerages, IT companies and music-related companies, and public institutions like universities and hospitals. As a communication tool, it is performing well not only in meetings but also in various other scenes such as presentations for operating activities, training and seminars, and telemedicine.

The technical solution of Foxtron Electric Bus combines domestic and international resources, each contributing its strengths： 1. It adopts Foxtron's self-developed VCU software, integrates and develops the EEA architecture for electric buses, and utilizes motors, batteries, and chassis suspension systems from international major manufacturers. In collaboration with domestic manufacturers, Foxtron designs and develops dedicated low-floor bus frames for chassis cooperation. 2. In the product design of electric buses, Foxtron identifies pain points in traditional buses and improves upon them. For example, traditional buses often have issues with rollover protection and numerous blind spots, as well as differential wheel rotation caused by wheelbase, leading to frequent traffic accidents due to visibility problems. To address these issues, Foxtron employs Computer-Aided Engineering (CAE) and NVH (Noise, Vibration, and Harshness) analysis to verify the design of various systems and components. This ensures the overall strength of the vehicle body and chassis, enhances passenger safety, and incorporates features such as panoramic image display and an electronic wide-angle rearview mirror with a blind spot detection system to solve driver blind spot issues. Additionally, to alert pedestrians and other road users to the risk of differential wheel rotation, Model T projects prominent light beams onto the ground during turns, marking the danger zone.

The Track Safety Management System is primarily aimed at addressing safety concerns along the track. It provides real-time monitoring, statistics, and detection-triggered alerts for trackside environments including stations, level crossings, along the track, and slope areas. The goal of this management system is to establish early warning alerts and prevent accidents from causing damage. Through the intelligent AIOT recognition monitoring system, it detects and analyzes station pedestrian traffic, tracks pedestrians at level crossings, identifies passing vehicles and traffic flow, detects foreign objects at level crossings and activates alarms, monitors personnel lingering and debris along the track, conducts rockfall monitoring on slopes with a rain gauge, monitors the environmental conditions in equipment boxes, and oversees the operation status of level crossing equipment. The monitoring data and image information are transmitted to the management system platform for integrated management via fiber-optic networks, NBIOT, or mobile communication. Additionally, it provides central management personnel with real-time interpretation and remote control in case of anomalies.

By the integration and utilization of IoT engineering information and sensor data about water resources management, air quality monitoring, disasters prevention and warnings…, we introduce end-to-end enterprise private networks to provide custom infrastructure systems and services for SMBs and public sectors.

MIRDC’s continuously Rotating Wind Turbine UAV Inspection System can effectively inspect the working wind turbine without interference. It takes 5 minutes to complete the inspection of a single blade to effectively detect 4mm small cracks. The system will not lose power generation by turning off the wind turbine, further observes the actual movement status of running blade structure and pillars to grasp the defects beforehand.

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.

Provide EOC at all levels to disaster management, notification and response, task dispatch, evacuation and shelter, resource scheduling, search and rescue, analysis Statistics, etc. after a disaster occur. Strengthen the collaborative response and dispatch capabilities of central and local governments in large-scale disasters. Minimize the damages caused by disasters. Disaster prevention and relief data are presented in visual charts, showing the latest disaster situation in the disaster area, and can include a variety of warning messages, disaster information, monitoring information, disaster response information and other graphics layers. The graphical interface decision-making dashboard can display important commands Decision-making auxiliary information is provided to commanders at all levels for reference, and then they can issue disaster relief response instructions according to different situations, strengthen the effective use and management of resources, and increase disaster relief energy.

This exhibition is an atmospheric physical-chemical grid model for prediction of changes in air quality, utilizing data from the U.S. NCEP global weather forecast and regional air pollutant emissions. Local scientific investigation data has been used to adjust and calibrate the model and thereby largely improve the accuracy of the air quality forecast over Taiwan. The system is capable of simulating the changes in air quality over the next three days (72 hours) in Taiwan, with a temporal resolution of 1 hour and a spatial resolution of 3 km. The simulated data can be integrated with air quality data from the Civil IoT Taiwan, informing regulatory authorities the changes in air quality for the near future, and key information for formulation of control strategies

The award-winning service application: 【Smart Campus - Smart Library, Healthcare Management System】to realize the independent management of school library and health care, it also greatly reduces the load on the schools’ administration, achieve the goal of sharing library and healthcare resources between teachers and students, through the collection and analysis of the big data in the background system, it will be more accurate for students’ recording values, AI predictive models can also help the govermant authorities the effectively assess and make the timely decisions, so far, all schools have been deployed and put into operation, benefiting about 25,000 teachers and students from 125 schools, the system is also launched simultaneously in all the Digital Opportunity Center (DOC), implement community cultural construction and connection; In future, we will continue to improve our services as a core: friendship between teachers and students, feelings between parents".

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.