# An ML-Based Solution in the Transformation towards a Sustainable Smart City
## 2 AI in SSC
### AI in Selected Areas of SSCs
Currently, data aggregation within SSCs focuses on specific application areas, classifications or predictions, but the goal is to create conditions for a multi-layered \"common operational picture\" (military analogy) for imaging, analysis and management of data:  
1. data from various IoT sources: * Scattered; * Heterogeneous; * Non-linear; * Monitoring and tracking objects;
2. data analysed using various methods: * Mathematical (including probabilistic); * Computational (including artificial intelligence) [17]. This requires energy-efficient communication along with quality of service (QoS) optimisation [17]. The transformation towards sustainable AI-based management of renewable energy sources is becoming a reality, including for energy cooperatives, which is of great importance for SSCs. AI enables faster responses, optimised operations, improved efficiency, lower costs and a shift to cleaner and more sustainable energy sources [18; 19]. Production technologies in the areas of technology and materials take into account sustainable development through the selection of processing technologies (e.g., casting, machining, 3D printing, etc. ), materials, energy savings, emitted particles and waste, which is supported by AI-based management, thus enabling the assessment of equipment consumption (as part of predictive maintenance), materials, the amount of pollution and the waste generated by production lines, packaging and transport systems. Self-learning programs adapt to changes in near real time, complementing previously used metrics and software [20; 21]. Such systems collect data and analysis results, and draw conclusions to solve current and future problems, also allowing the support and education of people and specialists in creative design, and solving SSC issues. SSCs will have a better ability to respond quickly and with fewer errors to health threats, including mass threats such as poisonings and pandemics. Policies, strategies and actions based on AI technology enable crisis management, improve the health of residents and increase the resilience of SSCs. In particular, coping and recovery are possible through:  
* Improving and equalising access to digital SSC services;
* Improving the digital skills of residents (including children, elderly people and disabled people);* Improving physical and mental health;
* Increasing social participation and connections;
* Maintaining the functionality of educational and economic systems [22; 23; 24]. E-health, smart manufacturing and logistics, traffic monitoring and car sharing (and, in the future, autonomous driving) are all data-driven. This requires the implementation of three main functionalities:
* Real-time intelligence;
* Distributed intelligence;
* Law enforcement with privacy;  
Using technologies of the third decade of the 21 st century:
* 6G mobile networks (bit-pipe connectivity);
* Smart edges (realising the burden of intelligent computing as close as possible to the consumers of services);
* AI/ML  
Provides the Internet of Medical Things (IoMT, Figure 2) and electronic health records (EHR). In a sustainable, AI-powered smart city, the IoMT revolutionises healthcare by seamlessly integrating AI-powered insights with connected medical devices. Smart sensors and wearables continuously monitor the health of residents, transmitting real-time data to AI systems that analyse and predict potential health issues, thus enabling proactive interventions. These AI-powered insights optimise resource allocation, ensuring efficient healthcare delivery while minimising waste. Smart city infrastructure supports the IoMT network with renewable energy, reducing the environmental impact of healthcare operations.AI also enhances telemedicine by providing accurate diagnostics and personalised treatment plans, reducing the need for physical visits and lowering transportation emissions. Using machine learning, AI systems detect patterns in health data, therefore identifying public health trends and enabling a rapid response to potential disease outbreaks.