## 8 Limitations and Future Scope of Research  
In this section, we critically reflect upon the inherent challenges and limitations encountered in the creation and utilization of the DELTA dataset, along with the strategies adopted to address these issues and enhance the dataset's applicability and robustness for future research and applications in urban mobility. We acknowledge that the DELTA dataset's initial geographic scope may not fully capture the vast diversity of urban environments, potentially impacting its generalizability across varied urban landscapes and the dynamic interactions within them. Furthermore, the environmental conditions during data collection were not entirely representative of the diverse scenarios encountered in urban settings, such as fluctuating weather conditions. These limitations are crucial for the dataset's performance and reliability, given the significant impact of environmental factors on sensor-based data acquisition. To mitigate these concerns, future endeavors will aim at broadening the geographic and environmental scope of the dataset. This includes plans to extend data collection efforts beyond the cold season in Estonia, which had initially restricted our ability to capture a wide array of urban settings and pedestrian behaviors. Incorporating data from various seasonal contexts and extending collection efforts to include different times of day and days of the week are pivotal steps toward ensuring that the dataset reflects the variability in environmental conditions and pedestrian activities throughout the year.  
By diversifying the temporal and seasonal coverage, we aim to craft a dataset that offers a holistic view of urban pedestrian environments. This effort will significantly bolster the dataset's diversity, scalability, and applicability for large-scale research and testing across a broad spectrum of urban contexts worldwide. Such enhancements are vital for developing technologies that are adaptable to the complex dynamics of urban environments, thereby supporting the advancement of urban planning, autonomous navigation, and the development of pedestrian-friendly urban infrastructure.  
Our aspiration is for the DELTA dataset to act as a catalyst for further research and methodological innovation in the study of urban environments. We understand the critical need for precise metrics to gauge the dataset's effectiveness for particular research initiatives. Therefore, we aim to foster a collaborative environment with the research community, working together to establish these essential benchmarks.  
Moving forward, our strategy to enhance the comprehensiveness and applicability of the DELTA dataset involves two key initiatives: Firstly, we plan to augment our data collection efforts by incorporating a fleet of e-scooters. This decision stems from the success of using an e-scooter platform, which has proven exceptionally agile and efficient in navigating a variety of urban environments. The e-scooter's ability to access narrow pathways, pedestrian zones, and cycling tracks enables us to capture a more diverse array of urban settings, enriching the dataset with a comprehensive view of urban pedestrian environments. Secondly, to ensure the dataset remains current and reflective of the ever-changing urban landscapes, we will implement a schedule of regular data collection sessions. The flexibility and rapid deployment capabilities of the e-scooter platform make it an ideal tool for frequent updates, allowing us to maintain the dataset's relevance and accuracy over time. By expanding to a fleet of e-scooters for data collection, we anticipate significant increases in the volume and diversity of data captured.  
Our commitment to these future directions is aimed at continuously improving the DELTA dataset, ensuring that it becomes an even more valuable resource for urban studies, particularly in the domains of pedestrian behavior analysis, autonomous navigation, and urban planning.