## 9 Challenges and Opportunities of Wearable and Seamlessly Integrated Devices  
The utilization of wearable IoT devices can expose users to potential risks, like cyberattacks, data theft, and malicious tracking. To ensure data privacy and security, it is essential to deploy advanced security measures, such as robust authentication protocols, encryption, and sophisticated data encryption algorithms [130]. Moreover, users need to be informed about basic security practices, including the importance of regularly updating passwords and exercising caution when dealing with suspicious links or messages. As the IoT market expands, wearable systems are expected to become increasingly significant. Addressing the critical challenges for their successful integration into the IoT ecosystem is paramount. These challenges encompass energy efficiency, data management and aggregation, device interoperability, user privacy and security, and scalability [131]. With the growing number of connected devices, managing these challenges becomes more complex, necessitating solutions tailored to IoT applications. Service providers should also focus on network security and reliability to ensure smooth user interactions [132]. Additionally, there is a need to make IoT systems more affordable to enhance accessibility and service quality. The emergence of 5G networks and cloud computing offers researchers a platform to develop cost-effective and efficient IoT solutions, focusing on power consumption and reduced latency. Wearable devices should support standardized, interoperable applications, calling for the development of open libraries and APIs, such as communication protocols for risk evaluation in low-power wireless systems [133]. These steps are vital for integrating and ensuring the functionality of various devices, crucial for delivering comprehensive and reliable user-centric services. This strategy allows for intricate customization and boosts user satisfaction through effective data analysis and processing. Recent advancements in wearable technology and the IoT have brought EEG into everyday applications through wearable and seamlessly integrated devices. This integration offers new opportunities for real-time monitoring and understanding of brain activity, with significant implications in healthcare, wellness, and lifestyle sectors. However, incorporating EEG into these devices presents several challenges. One primary challenge is designing wearable EEG devices that are comfortable and capable of capturing reliable signals. Accurate placement of EEG electrodes on the scalp is crucial for optimal signal quality [134; 135]. Developments in materials science and nanotechnology are leading to more user-friendly and efficient electrodes. Nanomaterials, for instance, enhance electrode conductivity and flexibility, improving signal acquisition. Additionally, the miniaturizationof EEG sensors facilitates their integration into wearable devices like headbands, helmets, or clothing, making EEG monitoring more accessible and convenient [136]. Processing and analyzing data from wearable EEG devices is another challenge. EEG signals are complex and often noisy, necessitating advanced signal processing techniques for extracting meaningful information. Real-time analysis requires low-latency processing, which can be addressed by edge computing. This approach, leveraging the processing capabilities of wearable devices and IoT connectivity, allows local data processing and analysis, reducing reliance on cloud-based solutions and minimizing latency. Privacy and security are critical when handling EEG data from wearable and integrated devices, as the data contain sensitive information about the individuals' brain activity and cognitive states. Robust data encryption, authentication, and authorization mechanisms are essential to protect data privacy and integrity. Strict access control measures should be implemented to ensure that only authorized individuals access and manipulate EEG data [137,138].