The aerospace industry's global market rise considerably in recent years. StarDetect, founded in Beijing in 2020, is a startup focusing on small satellite technology, developing functional payloads and providing customised services within the needs of space astronomy or earth geography observation. However, due to the relatively short and immature development of China's small satellite commercial industry, the current satellite service targets is limited, and most of the end-users are government and research institutes. StarDetect's has to reach out to more potential customers and develop new satellite application scenarios. Therefore, the goal of this thesis is to investigate a new commercial market for StarDetect and formulate a strategy for its entry. The thesis employed the double diamond design process to provide structure for the creation process and obtain solutions by using iterative analysis. As the result, a roadmap is designed for StarDetect to enter the Smart Tourism market. In the first horizon, Destination Discovery Service based on mature technology is launched to open new businesses in the market with price penetration, to meet the needs of tourism project developers for quick access to destination information. And a 3D visualization service is available as an add-on value. In the second horizon, the Destination Environmental Monitoring service is introduced for increasing sales, which meet the demands of management organizations for monitoring the sustainability of natural destinations. At the same time, a website providing sustainable travel information to responsible travellers is offered, to develop StarDetect's brand recognition and build connections with potential consumers in preparation for the next horizon's B2C business. Finally, Horizon 3 continue to grow market segments by launching Disaster warning and Safety monitoring services. Meanwhile, StarDetect started to serve consumers directly by providing a one-stop service platform for outdoor adventure to capture new business opportunities.

Background: In the context of the COVID-19 outbreak, 80% of the persons who are infected have mild symptoms and are required to self-recover at home. They have a strong demand for remote health care that, despite the great potential of artificial intelligence (AI), is not met by the current services of eHealth. Understanding the real needs of these persons is lacking. Objective: The aim of this paper is to contribute a fine-grained understanding of the home isolation experience of persons with mild COVID-19 symptoms to enhance AI in eHealth services. Methods: A design research method with a qualitative approach was used to map the patient journey. Data on the home isolation experiences of persons with mild COVID-19 symptoms was collected from the top-viewed personal video stories on YouTube and their comment threads. For the analysis, this data was transcribed, coded, and mapped into the patient journey map. Results: The key findings on the home isolation experience of persons with mild COVID-19 symptoms concerned (1) an awareness period before testing positive, (2) less typical and more personal symptoms, (3) a negative mood experience curve, (5) inadequate home health care service support for patients, and (6) benefits and drawbacks of social media support. Conclusions: The design of the patient journey map and underlying insights on the home isolation experience of persons with mild COVID-19 symptoms serves health and information technology professionals in more effectively applying AI technology into eHealth services, for which three main service concepts are proposed: (1) trustworthy public health information to relieve stress, (2) personal COVID-19 health monitoring, and (3) community support. @en

In "A Patient Journey Map to Improve the Home Isolation Experience of Persons With Mild COVID-19: Design Research for Service Touchpoints of Artificial Intelligence in eHealth". (JMIR Med Inform 2021;9(4):e23238) the authors noted one error. In the originally published manuscript, Multimedia Appendix captions incorrectly appeared as follows: Multimedia Appendix 1: Patient journey map of persons with mild COVID-19 during home isolation. Multimedia Appendix 2: Visual summary. Multimedia Appendix 3: Video purpose and comments coding trees. Multimedia Appendix 4: Personal video story coverage and experienced symptoms during home isolation. In the corrected version of the manuscript, Multimedia Appendix captions have been corrected to: Multimedia Appendix 1: Personal video story coverage and experienced symptoms during home isolation. Multimedia Appendix 2: Patient journey map of persons with mild COVID-19 during home isolation. Multimedia Appendix 3: Video purpose and comments coding trees. Multimedia Appendix 4: Visual summary of design research. The correction will appear in the online version of the paper on the JMIR Publications website on May 4, 2021, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.@en