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    Multi-value added usecross-domain combination of meteorological data

    Taiwan is one of the vulnerable areas frequently suffering from natural disasters. Typhoons, floods, landslides, droughts, and earthquakes are the most frequent natural disasters. Despite this increasing risk, which is due to a number of climatic and non-climatic factors, improvements in decision support system for disaster risk management and early warning are making it possible to limit losses from natural disasters. This would not be possible without the informed use of constantly improving meteorological, hydrological and related data-information. In addition, meteorological data can be integrated and analyzed with the related multiple data collected by AIOT (Artificial Intelligence of Things), and then applied in different fields to generate data-driven innovation and economic value. According to the Global Framework for Climate Services (GFCS) by the World Meteorological Organization (WMO), the informed use of meteorologicaland related data-information can deliver enormous benefits to society, including agriculture, water resources, the natural environment, human health, tourism,energy, transport and communications, urban settlement and sustainable development, etc.

    Reference : https://library.wmo.int/doc_num.php?explnum_id=3314
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    Trade warcovid-19 accelerate the realization of smart manufacturing

    In 2018, the trade war and tech war between the United States and China had a huge impact on the global economy, and it also promoted the reorganization of the global supply chain. In 2020, due to the Covid-19 pandemic, the impact on the supply chain and production chain is more serious. The manufacturing industry that relies on the operation of physical equipment, is faced with problems such as the inability to import materials, the shutdown of production lines, and the inability to export products. Due to these uncertain factors, many countries and industries realize the benefits of digital transformation, accelerate the intelligence and digitalize of manufacturing, and help companies develop more competitive operations and business models. The rate of IT investment in my country’s manufacturing industry in the past three years has also increased year by year, especially in technologies such as AI, IoT, and machine learning. Develop solutions for process optimization and predictive maintenance to realize intelligent operation, production, and management. Most importantly, it will strengthen the ability to cope with future challenges and create a sustainable and resilient manufacturing industry.

    Reference : MarketsandMarkets、iThome
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    The post-epidemic new normal accelerates the deployment of new networkinformation security technologies

    Under the impact of Covid-19, the world has adopted lockdown measures to slow the spread of the virus. The companies must quickly move to remote work from home in order to operate normally. However, remote access has caused more blind spots in cybersecurity, including the unstable behavior of employees at home, the inconsistent security of personal devices, and the use of home internet. All these factors reduce the security visibility and allow cyberattacks to take advantage. According to the recent VMWare Global Security Insights report, nearly 80% of corporates have suffered cyberattacks due to WFH, and most of the cases have serious damage. It shows that under the new normal after the epidemic, traditional cybersecurity systems are no longer adequate. This trend has also begun to become significant as the epidemic in Taiwan is heating up. According to Check Point’s research, cyberattacks in the Asia-Pacific region increased by 53% during April and May 2021, and Taiwan's growth rate ranked fifth, reaching 17%. In order to cope with the fact that remote work from home will become the new normal after the epidemic, and the proportion of enterprises using cloud services has gradually increased, new cybersecurity technologies and solutions, such as the secure access service edge (SASE) model, and the user identity-centric Zero Trust Architecture (ZTNA), will help enterprises redefine network security and border defense.

    Reference : https://www.vmware.com/security.html
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    An aging populationhas accelerated the adoption of telecare in Taiwan

    According to the Population Projections for R.O.C. of National Development Council, Taiwan became an aged society in 2018, and is projected to become a super-aged society in 2025. The problem of an aging population and its long term care is now an important topic. The problem is that the elderly have a lack of care, insufficient resources for care in rural areas, difficulties traveling long distance for care services, and the high risk of spreading infectious diseases. However, telecare systems can be used in the improvement of the care quality. It is a continuous, automatic and remote monitoring of real time emergencies and lifestyle changes over time in order to manage the risks associated with the elderly living independently. Telecare is believed to be one of the solutions to keep older people independent and reduce medical costs in an aging society. In addition, AI technologies transform health care industry and increase the telecare market value in Taiwan.Refer to the Smart Health-Assist (SHA) programme in Singapore, Infocomm Development Authority (IDA) and Ministry of Health (MOH)rolled out a Smart Health-Assist pilot project in the Jurong Lake District. It is designed to record data from user - friendly sensors in the houses of the elderly and the patients suffering from chronic diseases to be sent securely online to healthcare providers, allowing them to monitor individuals, receive alerts, and respond to any emergencies. The Smart Health-Assist (SHA) programmerecommended solution is(1) Development of next generation sensors: These can include network ready-heart rate monitors and blood pressure monitors which come in the form of stick-on patches, digital wrist watches, or sensors embedded in household items like pillows and rugs;(2) Networking the homes and care centres: The captured data must make its way securely to healthcare providers;(3)Decision support systems:These systems can help healthcare professionals to recommend the right treatment and care plans for patients;(4) Big data analyticswith national health databases: In the area of big data & analytics, data collected by the sensors can be collated with data in national health databases. This will lead to more consistent delivery of evidence-based care and monitoring of key clinical and service outcomes.

    Reference : https://www.ndc.gov.tw/Content_List.aspx?n=695E69E28C6AC7F3
    Data reference : https://reurl.cc/95XDMn
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    AIST launched the Global Zero Emission Research Center (GZR)

    In order to solve the urgent global climate change problem, Japan hopes to create discontinuous innovations in environmental and energy technologies. Therefore, the Japanese government announced that it will gather global wisdom and establish Global Zero Emission Research Center (GZR) by Industry's Institute of Industrial Technology (AIST). GZR was established in January 2021,as a zero-emission international joint research base that takes G20 framework as the core, and cooperates with the world's top public research institutions to conduct innovative technology research (renewable energy, storage batteries, hydrogen, CO2 separation and use, artificial photosynthesis, etc.), aiming to promote environmental technology innovation for the aforementioned goals. Achieve the vision of a zero-emission society. Dr. YOSHINO Akira, who won the 2019 Nobel Prize in Chemistry, was appointed as the director of the research center. The headquarters of the research center is located in the AIST Tokyo Waterfront main building, and the new research facility is located in the Tsukuba area. The Fukushima Renewable Energy Research Institute (FREA) is responsible for demonstrating the innovative technologies that have been developed, and the Kansai Regional Center of AIST is engaged in development of Storage battery.
     
    Reference:https://www.gzr.aist.go.jp/en/
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    Use AI to achieve smart sustainable water management

    In 2015, the United Nations "World Water Development Annual Report"pointed out that if there is no improvement in the future, the global water resource will be short of 40% by 2030. The shortage of water resource will cause water conflicts in different fields of people's livelihood, agriculture and industry. Such warning signs are now confirmed in Taiwan. Facing the difficult challenge of the "Hundred Years Drought", besides relying on rainfall, using digital technology, especially AI applications, to achieve effective water saving, high-efficiency water resources management and optimization of water allocation will be an alternative. This is one of the conclusions produced by the participants in the innovative technology application topic co-creation workshop held by this project.
    For example, the German Federal Ministry of Education and Research launched a three-year plan in 2019, to research and implement the possible sustainable water management solutions with 90 partners. By collecting big data on global water usage and forecasting water availability and drought by AI, German government called for changing the global foreseeable water dilemma. The key is that the public and private sectors should use digital technology on a long-term basis.
    Reference:https://bit.ly/3f1vfbf
    File download:https://bit.ly/3zFI42Q
  • Topics

    The multiple innovative applications of AI technology

    Since 2016, after AlphaGo demonstrated the power of AI, this technology has swept the world and governments and industries have invested a lot to drive the continuous innovation and advancement. This project tries to find out the recent technology trend through text mining. From more than 5,000 articles published in the 2020 in 4 Top AI international seminar, one of the emerging technologies is the "emotion recognition", not only from text but also from facial expression and voice. Through the analysis and processing of the audio collected by the sensor, the machine will be able to recognize our disgust, fear, happiness, sadness and surprise and other different emotions. By allowing machines to hear the "overtones" of our speech, there will be more possible diversified and innovative application. For example, smart customer service can make the cold and standard voice interaction become a customized service or select appropriate response content based on customer emotions. It may also be used in the medical field to assist patients who have lost their voice due to illness or accidents, by customizing the exclusive speech synthesis system to increase the temperature of communication and interaction.
    Reference:https://bit.ly/3f26vQb
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