# Integration of AI in Self-Powered IoT Sensor Systems
## 3 Domain Identification in the Literature Using IoT Sensors
[14] discuss the potential of smart cities to transform medical services by integrating these modern technologies. The smart mobility sector overlaps with smart cities, as most works address the optimization of urban and airport traffic. However, the works targeting this field explicitly focus on combining IoT sensors and AI for transportation analysis. For this reason, the authors of the present work have treated the field as separate from smart city, which focuses more on the quality of human life and less on algorithms targeting traffic. Thus, [PERSON] et al. [8] analyze the integration of IoT sensors and AI algorithms into an architecture aimed at the electric vehicle charging infrastructure. The paper identifies research directions for the experimental validation of the proposed infrastructures in future studies. [PERSON] and [PERSON] [10] investigate the transformation of urban mobility by integrating AI, IoT, and predictive analytics in traffic management. The paper identifies a reduction in delays of up to 30% when AI models are integrated with IoT sensors at the traffic level. Refs. [12,41] review smart parking systems, discussing the challenge of detecting parking spaces under various conditions of size, brightness, and obstacles and proposing techniques based on video devices mounted on a vehicle's windshield (dashcam) and neural networks (NNs) for identifying available spaces. The paper by [PERSON] et al. [13] addresses smart airports and IoT services implemented through automation techniques. The analysis of the specialized literature shows that the fields overlap because they examine common elements that target the quality of human life. In Figure 4, the way in which different technological domains related to IoT intersect and influence each other is suggested. At the center of all these domains, smart cities are identified as the main element of interconnection, as all the different domains contribute to the development of this field. Smart cities employ technologies from all other domains through the integration of wearable sensors for medical monitoring systems, the integration of sensors that influence traffic, the integration of sensors that affect air quality and soil quality, which reflects in the health of the food consumed by the population, etc. Therefore, all these elements contribute to improving the quality of life for citizens. Wearable devices focus on the use of wearable sensors to monitor individual health. These devices operate in the healthcare IoT and smart cities sectors because the collected data is integrated into urban systems that facilitate access to personalized services [42]. The industrial IoT sector aims to optimize industrial processes, which eases the work of the employed staff. Thus, from this perspective, the citizens' quality of life is also influenced by an indirect action in the area of smart cities. Additionally, optimizing industrial processes through IoT sensors influences the field of environmental monitoring by monitoring environmental parameters affected by industrial activity. The smart homes domain focuses on creating smart houses that facilitate human activity by creating a pleasant ambient environment, replacing time-consuming processes, optimizing resource usage, and ensuring enhanced comfort and advanced safety. This is made possible by the IoT-AI components that operate in the smart homes area, which also directly influence Smart Cities, as smart homes are part of larger communities. Environmental monitoring uses AI and IoT to detect pollution and prevent ecological disasters, among other elements influencing smart cities and industrial IoT. Healthcare IoT collects medical data and collaborates with wearable devices and smart cities. Additionally, smart mobility, which focuses exclusively on optimizing urban traffic and managing transportation infrastructure, influences smart cities, industrial IoT, and environmental monitoring by reducing or exacerbating gas emissions. Figure 4 highlights the interdisciplinary of these fields in an IoT-AI approach.