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Innovation (Camb)
Innovation (Camb)
The Innovation
2666-6758
Elsevier

S2666-6758(24)00116-4
10.1016/j.xinn.2024.100678
100678
Out-of-the-Box
“DigitalMe” in smart cities
Park Seung-min park.seungmin@ntu.edu.sg
1∗
Hong Seunghun 2
Joo Kyonghee 3
Kim Soh 4
Lepech Michael D. mlepech@stanford.edu
45∗∗
1 School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637459, Singapore
2 Walmart Connect, Hoboken, NJ 07030, USA
3 LG CNS, Seoul 07795, South Korea
4 Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA
5 Stanford Center at the Incheon Global Campus (SCIGC), Incheon, South Korea
∗ Corresponding author park.seungmin@ntu.edu.sg
∗∗ Corresponding author mlepech@stanford.edu
23 7 2024
09 9 2024
23 7 2024
5 5 10067822 3 2024
19 7 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Published Online: July 23, 2024
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pmcPrecision health and DigitalMe

Continuous monitoring of high-value equipment, such as semiconductor production equipment and jet airplane engines, has become a standard practice across myriad commercial sectors. “Digital twin” technologies enable such monitoring by providing sensor data for maintenance and other mission-critical operations in real time. While continuous monitoring has become standard in some industry, its application to monitoring healthy adults globally remains underexplored, with many individuals seeking medical care only when symptomatic. Insights gained from digital twin could be transferred to healthcare, revealing opportunities for more data-driven and personalized care.

Precision health1,2 emphasizes proactive disease prevention, early detection, and tailored treatments through individualized, longitudinal monitoring, often utilizing wearable, implantable, or home-based devices. This approach extends beyond genetics to include exposomes, digital biomarkers, and environmental data. Thus, we introduce “DigitalMe”—analogous to industrial digital twins but designed for individual health. DigitalMe is more than a data warehouse seeking to digitize all aspects of our lives. This encompasses more than just health information, including individual-generated data such as social media posts and online shopping habits. DigitalMe’s unique “micro- to macro-scale coverage” bridges the gap between personalized medicine and public health applications, transforming how cities approach healthcare planning and delivery. By understanding these insights, city planners can make informed decisions to enhance urban living standards, optimizing services like public transportation.

Smart cities leverage information & communication technologies and other means to improve the living standards of their residents and commonly operate upon a hierarchy of three layers: sensing, computing, and engagement.3 DigitalMe seamlessly integrates into these layers, enhancing healthcare and urban living. Through wearable/smart-home-based sensors, healthcare professionals can receive real-time information on residents, enabling prompt interventions. DigitalMe also capitalizes on existing data streams from various city infrastructures. The computing layer, powered by artificial intelligence (AI), assists in faster and accurate diagnoses, while the engagement layer offers citizens easy access to healthcare and urban services, minimizing the need for physical visits. In Figure 1, DigitalMe leverages advanced technology to improve the efficiency of healthcare delivery. DigitalMe can play a pivotal role in sustainable city planning. Insights from daily habits aid in optimized resource allocation, reducing energy consumption and waste. For instance, transportation patterns derived from DigitalMe can lead to more efficient public transit systems and promote eco-friendly travel alternatives. Thus, DigitalMe provides timely insights into an individual’s health and predicts potential risks by integrating with smart city Internet of Things (IoT) networks and AI data hubs, collating environmental and personal data for tailored healthcare. Potential applications range from diabetes risk models to gastrointestinal health insights.4 It goes beyond traditional reactive care, predicting high-risk areas for disease outbreaks such as COVID-19 or monitoring air quality.Figure 1 Hyperconnected smart cities and DigitalMe application example

This figure illustrates the integration of the DigitalMe concept within hyperconnected smart cities, seamlessly combining sensing, computing, and engagement. On the right, we see a smart city infrastructure where personalized healthcare intersects with public health, fostering sustainable development driven by precision health and artificial intelligence. DigitalMe emphasizes the ethical considerations and potential challenges related to data privacy and individual autonomy. On the left, a specific application of DigitalMe focusing on cardiovascular disease management demonstrates the capabilities of a human digital twin. The Digital Review of Me (DRM) covers various human systems, including cardiovascular, gastrointestinal, respiratory, musculoskeletal, endocrinology, genitourinary, and mental health. It integrates sensor data, electronic medical records (EMRs), and 3D scans, digitized for health pattern recognition, actionable response, and predictive health modeling. This comprehensive approach of DigitalMe shows its potential in monitoring and enhancing health across multiple systems, paving the way for responsible technology use in smart cities.

Real-world implementation

The current level of implementation of DigitalMe is in its nascent stages but shows promising development.

Busan Eco Delta City (EDC) in Korea planned to integrate DigitalMe to incorporate real-time health data into urban living, focusing on high-quality medical services, especially for vulnerable and disabled residents. EDC’s healthcare framework consists of three pillars: 1) personalized health management, 2) real-time smart community services, and 3) community health keeper services, targeting primarily high-risk and disabled populations. These services encompass preventive care, early diagnosis, and instantaneous health alerts from professionals, as shown in Figure 1. Driven by Korea’s aging population and a shift toward consumer-centric healthcare, EDC uses AI, big data, and digital tools to provide personalized medical services.

Similarly, Sejong, the administrative capital of South Korea, received the world’s first smart city international certification (ISO37106) in December 2018. In Sejong, the potential integration of a conceptual framework like DigitalMe could leverage existing initiatives—the “Sejong Smart Health Platform” and the “AI IoT-based Senior Health Management Pilot Project.” These projects demonstrate how comprehensive data collection and analysis can enhance urban administration and citizen life through advanced, data-driven solutions. By enabling real-time policy participation and smarter governance, such initiatives improve public administration efficiency and citizen engagement. DigitalMe could further inform the development of essential urban infrastructure that directly impacts citizen well-being and facilitates smart healthcare services, integrating seamlessly with IoT and wearable technology.

Furthermore, the predictive analytics capabilities of DigitalMe could enhance disaster and crime prevention measures and improve traffic and pedestrian safety through detailed data analysis in Sejong. These integrations not only propose to elevate healthcare delivery but also enrich various aspects of urban management, promoting a holistic and optimized approach to urban planning that benefits all city residents. For effective dissemination, DigitalMe necessitates 1) advanced disease prediction tools, 2) continuous sensor-based health monitoring, and 3) scalable health management systems.

In Korea, telemedicine is mostly prohibited except for certain situations like COVID-19, but to promote innovation in smart cities, the government introduced a regulatory sandbox allowing businesses to test new solutions in smart cities. Meanwhile, Singapore formally licensed telemedicine under its Health Services Act by mid-2022. Given these differences, it is vital for DigitalMe to adapt to local regulations, ensuring compliance with data protection, patient consent, and ethical standards.

Limitations and challenges

The initial pilot phases of DigitalMe raise acute ethical issues related to data privacy, security, consent, and surveillance. First, the AI tools powering DigitalMe can only be effective if trained on large, well-characterized, and well-represented data. The multimodality of the datasets needed to create an accurate DigitalMe profile of smart city residents presents serious limitations to rolling out this technology. It has proven exceedingly difficult to computationally model social determinants of health and environmental exposures, for example, that we know are significant over the life course and therefore should be built into a digital twin. Second, collection and continuous monitoring of data needed to feed DigitalMe is invasive. The scope and scale of DigitalMe data collection and analysis would serve the goal of capturing every molecular, social, and environmental interaction as data points to be fed into the AI system. Such invasive and multimodal data collection, processing, and sharing lead to “wholesale erosion of data minimization principles” that underlie consumer and patient data rights, whereby only a minimal amount of data are generated to accomplish a specific analytic task. However, DigitalMe aims to responsibly use extensive data by applying advanced anonymization techniques to protect privacy while preserving data utility for health analysis. Multimodality also heightens the risk of re-identifiability of both humans and objects, even if data were de-identified or anonymized prior to their incorporation into AI models. Third, the social consequences of datafication in healthcare, specifically, are widely cautioned in the literature, but geosurveillance within smart cities layer new equity concerns related to inference about health behaviors. Sensors within smart cities track individuals’ movements and behaviors. If disclosed to third parties, this information could be stigmatizing and invite discrimination. Some have argued that privacy laws should be amended to also “help close the accountability gap” and protect individuals’ right to reasonable inference, given the potential for grave privacy and reputational damages when inferences are used to make important decisions. Fourth, passive monitoring and surveillance of data collected through smart city infrastructures challenge extant practices of notice and consent. Smartphone users who download mobile applications consent to the terms outlined in its data privacy policies. However, extensive research shows that users infrequently read privacy policies before consenting and generally lack an understanding of what types of data mobile applications truly collect about them and how these data are shared. It is anticipated that not all residents of smart cities will possess smart devices for data collection. Additionally, ambient surveillance devices will be placed at public access points throughout these cities, such as traffic lights, businesses, and parks. Many residents may be unaware that they are being monitored by these devices.

In this regard, DigitalMe is proposed to enhance data security through blockchain technology for transparent, immutable transactions, robust anonymization to prevent identification, advanced encryption, and key chunking methodologies that distribute encryption segments to secure data storage and access.

Additionally, equity concerns are acknowledged, with planned strategies to prevent biases in healthcare provisioning. DigitalMe aims to foster community engagement and education, empowering residents to understand and influence how their data are used, aligning with ethical standards and personal rights.

Realistic solutions

Cities should adopt comprehensive strategies that intertwine technological adoption with societal trust. Establishing public-private partnerships (PPPs) is pivotal. Such alliances allow governments and private tech entities to collaboratively share resources and expertise. This synergistic approach is crucial to effectively bringing the DigitalMe concept to fruition on a city-wide scale. A hallmark of this initiative is Sejong. The project, led by the PPP of Sejong Smart City, integrates public resources and private expertise from entities like LG CNS, which is instrumental in developing essential smart services across mobility, healthcare, and environmental management. Equally essential is the role of education. Cities must proactively launch widespread awareness campaigns to enlighten residents about DigitalMe’s multifaceted benefits, its inherent risks, and the mitigation steps in place. By demystifying DigitalMe, urban centers can foster informed consent, thereby deepening trust among their denizens. In our data-driven age, cybersecurity cannot be overemphasized. Cities should invest significantly in state-of-the-art data protection infrastructures. Furthermore, ethical considerations are paramount.2,5 Cities should establish oversight committees, bringing together tech specialists, ethicists, policymakers, and community voices. Financially, cities should earmark dedicated funds for DigitalMe, potentially augmented by state grants or international organizations passionate about urban healthcare. Concluding the strategy should be the emphasis on continuous feedback channels and targeted training sessions, ensuring it remains tethered to the community’s needs.

Future research should focus on enhancing data privacy through advanced encryption, increasing transparency using explainable AI, and validating its effectiveness with longitudinal studies across diverse populations and settings.

Acknowledgments

This publication was supported by the 10.13039/100015521 Stanford Maternal and Child Health Research Institute through the Stanford Medicine Children’s Health Center for IBD (Inflammatory Bowel Disease) and Celiac Disease and the Stanford Center at the Incheon Global Campus (SCIGC). We are thankful for Prof. Rahimzadeh’s helpful discussion. We dedicate this perspective to Dr. Sanjiv Sam Gambhir, who passed away on July 18, 2020, from cancer, the very disease he wanted to defeat with his life-long vision of precision health. As Dr. Gambhir would say—"Welcome to the revolution.”

Author contributions

S.-m.P., S.H., and K.A.J. conceived the original concept of DigitalMe. All authors discussed and materialized DigitalMe in a smart city framework. All authors also participated in drafting and revising the manuscript.

Declaration of interests

One of the co-authors, K.A.J., has recently moved to LG CNS. K.A.J.’s current involvement with LG CNS is unrelated to the examples provided in this article.
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