Micro Gas Sensing Chip Public Board System and Technology Research and Development Service Platform of Taiwan Instrument Research Institute (TIRI)

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

In the past, human operation and judgment were required, but now technology assists people in handling water distribution work. Set up water level or flow sensing devices in important water supply channels and transmit the collected data to the information management platform. Using online information or mobile APPs, water stewards can instantly grasp the field water distribution to achieve the goals of saving manpower and accurately allocating water. Taking the research results of the Jianan Irrigation District as an example, water stewards management can save about 20 to 25% of water by allocating irrigation water. If it is combined with Smart irrigation system, it can save another 5% of water. Currently, Water Resources Department, MOEA continues to cooperate with National Science and Technology Council, Ministry of Agriculture to gradually expand to 3,000 hectares in the Jianan Irrigation District and 3,000 hectares in the Kaohsiung Irrigation District, and gradually promote Smart irrigation and water-saving management technology.

NCREE has developed a Hybrid earthquake early warning system (EEWS) by integrating on-site EEWS from NCREE and regional EEWS from Central Weather Administration (CWA). Within a 10 to 100-kilometer radius from the earthquake epicenter in the local region, this system can provide 3 to 15 seconds of warning time. To achieve effective alerts with the available warning time, the utilization of a Hybrid EEWS cloud platform is crucial. This platform facilitates the transmission of alerts and the affected administrative regions to various industries. Industries, in turn, leverage these alerts to develop warning systems and automated control devices tailored to meet the specific requirements of different environments. This approach aims to minimize secondary damages resulting from earthquakes, transforming EEWS beyond being notifications received Presidential Alert on mobile phones. Instead, it offers a multi-faceted alerting and disaster reduction application system tailored to different environmental settings.

The application of digital twin technology in building smart cities is becoming increasingly clear, serving as a crucial engine for driving urban transformation. In the development of smart cities in recent years, citizens can view the growth and development of the entire city, including population growth, new construction, and other major activities, in a 3D format, gradually emphasizing the concept of a virtual city. Digital twin technology can simulate disaster scenarios, including weather events and traffic accidents, assisting disaster response personnel in rapidly understanding the situation and optimizing the efficiency of disaster response. In recent years, with the advancement of aerial photography, simulation technology, and computing resources, The National Science and Technology Center for Disaster Reduction has leveraged advanced technology to create a mountainous flood inundation model system. This system enhances disaster warning and impact analysis, providing a comprehensive view of vulnerable settlements. It utilizes dynamic models and virtual-real integration, presenting alert information and disaster impacts through visual elements, contributing to informed decision-making in disaster situations.

The Ministry of Economic Affairs, Department of Industrial Technology has commissioned the Industrial Technology Research Institute's Center for Smart Sensing and System Technology to develop a "Composite Long-Term Air Quality Sensor." This sensor is capable of simultaneously measuring particulate matter (PM2.5), ozone (O3), carbon monoxide (CO), volatile organic compounds (VOC), and other air quality monitoring parameters. Also, the Industrial Technology Research Institute (ITRI) to develop a "Composite Water Quality Sensing System." This system enables simultaneous measurement and detection of parameters such as Chemical Oxygen Demand (COD), Suspended Solid Concentration (SS), Copper Ion (Cu2+) concentration, conductivity, pH value, temperature, and more.

In order to enhance the efficiency of irrigation water management in Hsinchu, the Irrigation Agency (IA) applies low-power sensors, remote control systems of water gates, and gate inspection systems to the irrigation management of the Zhudong Canal. The IA combines water gauges with the low-power NB IoT transmission module to monitor the real-time water level. Meanwhile, with the remote control systems of water gates, the real-time opening and closing of water gates can be operated through the "Platform of IA for Remote Monitoring and Management of Water Gates", making the operation of irrigation management more labor-saving and convenient. In addition, installing NFC tag cards allows to fill out the information and transmit the inspection results of water gates through an inspection APP, enhancing the efficiency of gate management.

The Central Weather Administration (CWA) is the government agency responsible for earthquake monitoring and reporting in Taiwan. In order to reduce fatalities and property losses caused by earthquakes, a high-density real-time seismic network and the advanced earthquake early warning (EEW) system have been implemented and in operation. Currently, the CWA EEW system can issue the warning message in about 10 seconds after a strong earthquake occurring in or very near Taiwan. Starting from 2021, in order to further enhance the benefit of EEW to the practical earthquake hazard mitigation, the CWA has begun to develop the customized urban EEW system. By means of introducing the on-site earthquake early warning methods, and developing the artificial intelligence models. The systems, particularly for the big urban shallow earthquake, aim to further shorten the time of EEW to 7 seconds. That means it can give warning to the areas about 25 km away from the epicenter, and more people could be alerted before the destructive shaking.

Delivering a comprehensive fire and disaster information service, it allows users to access evacuation information even in offline environments. Based on the user's location, it provides immediate push notifications for 21 types of disaster alerts, including heavy rain, typhoons, and earthquakes. Additionally, it updates critical maps such as shelter locations and air-raid shelters as offline resources.

The Ministry of Environment has promoted the deployment and application of the Internet of Things for empty product sensing since 2017, and has deployed approximately 10,000 sensors to make up for the deficiencies in time and spatial resolution of standard monitoring stations. Among them, in 2022, it expanded from the Taiwan island to Lienchiang County on the outlying Island. Its unique geographical location is more conducive to early warning of transboundary pollutants and reminds people to take precautions in advance.

Civil IoT Taiwan is part of the government’s Forward-looking Infrastructure Development Program under the Digital Infrastructure category. With the collective effort of the National Science and Technology Council (NSTC), the Ministry of Transportation and Communications (MOTC), the Ministry of Economic Affairs (MOEA), the Ministry of the Interior (MOI), the Ministry of Environment (MOENV), the Ministry of Agriculture (MOA), the Ministry of Digital Affairs (MODA) and the Academia Sinica, the project aims to address the core needs of the public by prioritizing four key mission areas, namely air quality, earthquake, water resources, and disaster prevention and response. By leveraging AI and IoT technologies, the project strives to deliver well-rounded, smart living services to facilitate the government and the people to respond to the challenges in an ever-changing environment.

The Administration for Digital Industries(ADI) is actively promoting the use of data from Civil IoT Taiwan and integrating it with other public and private sector data to develop data-driven applications and IoT solutions with commercial value. ADI assists businesses in securing international orders, achieving a total of NT$12.6 billion in revenue.

The Civil IoT data service platform collected and stored environmental sensor data in four key areas: earthquake, water resources, air quality, and disaster prevention, and provides real-time data service using the OGC SensorThings API that conforms to the international data modeling standards for value-added services through a unified data modeling framework. In order to solve the problem of insufficient communication in remote areas, Band20 frequency band is utilized to build a backbone network core service for IoT application, which provides remote areas with the use of Band20 frequency band as a network communication method for IoT data transmission, and expands the scope of IoT deployment in remote areas.

AQUAS Solution of high cost-effective smart monitoring for effluent water quality and flow volume. We provide an excellent product portfolio, including multiparameter water quality controllers, radar flow meters, and water quality analyzers, which can accurately and stably monitor the quality and flow of the effluent in the long term. Ensure the water quality compliance with the regulations and standards to reduce environmental pollution.

P-Waver Inc. is the global leader of AI on-site earthquake early warning system and structural safety monitoring system, providing earthquake early warning before earthquake, intelligent disaster mitigation measures, and structural safety monitoring after earthquake.

By applying multiple disaster data on CIoT, including disaster warning and notification, rainfall, earthquake, regional drainage data, etc., collected from various public sectors, alongside with the on-site environment monitoring data, the data is verified and utilized by ThinkTron to develop the comprehensive All-Hazard Emergency Data Platform for the emergency response centers of some municipal fire departments in Taiwan. This not just enables the digital transformation but also boosts the digital governance. In addition, this GIS+IoT+AI integrated application is extended to smart industrial park management, helping corporate clients on achieving ESG goals accordingly by sustainable operation.

VISION's Air Quality Detector II has been integrated into the Environmental Protection Administration's Air Quality Monitoring Network as a key sensor. Building upon practical experience and feedback, its enhanced design is adaptable for various outdoor scenarios with modular expansion capabilities. The device features PM2.5 sensing technology derived from ITRI, setting it apart as the sole Taiwanese-designed and manufactured air quality monitor in the network. Noteworthy for its exceptional sensing performance, the Air Quality Detector II employs LTE communication technology and GPS positioning. With a visually appealing design, remote maintenance management, and convenient inspection capabilities, this device serves multiple functions. Its distinctive blue and white color scheme seamlessly blends with the environment, providing a unique and aesthetically pleasing alternative to the conventional appearance of air quality monitors.

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.