Regional Ecosystems Driven by Mobile Big Data/Services
From the perspectives of spatial informatics and mobile computing, this research aims to develop and implement IT technologies that help re-evaluate the diversity, appeal, and civic pride of local communities. In particular, as rural areas face population decline, sustainable community development increasingly depends on collaboration among residents, visitors, and local organizations. This study explores methodologies for building a people-centered information infrastructure for community development, utilizing AI and big data to integrate and leverage local history and wisdom, while also facilitating human-to-human collaboration throughout the process.
Thematic Heatmapping and Scoring Methods for Developments of Walking Routes (2021–)
Establishing a cost-effective digital feedback system that contributes to the development of walking model routes, considering both spots and walking paths, is a challenge in fostering sustainable regional tourism. This study discusses a feedback system that contributes to the evaluation and improvement of existing model routes by mapping tourists’ access (attention) to tourist resources based on the automatic collection and analysis of mobile sensor data, which is standardly equipped on smartphones and other devices.
Sasaki et al. (2020). Articulated Trajectory Mapping for Reviewing Walking Tours. ISPRS Int. J. Geo-Inf. 9(10):610.
DOI: 10.3390/ijgi9100610
Sasaki et al. (2023). Mobile Collaborative Heatmapping to Infer Self-Guided Walking Tourists’ Preferences for Geomedia. ISPRS Int. J. Geo-Inf. 12(7):283.
DOI: 10.3390/ijgi12070283
Automatic Geofencing Design for Scalable Location-Based Services (2023–)
The core technology of proactive location-based services is known as geofencing. Geofencing utilizes virtual boundaries, i.e., geofences, to monitor user’s entry and exit, and then triggers place-related services such as sending coupons and playing audio guides automatically. The purpose of this research is to formulate geofence design problems for tourists' mobility and to develop data-driven computational solutions. These solutions leverage mobile sensor data to comprehend dynamic and complex human mobility patterns.
Sasaki et al. (2020). Data-Driven Geofencing Design for POI Notifiers Utilizing Genetic Algorithm. ISPRS Int. J. Geo-Inf. 13(6):174
DOI: 10.3390/ijgi13060174
Onsite Radio App — Generative Audio Guide Driven by Hierarchical Geofencing and Large Language Models (2024–)
POI-based guide applications face challenges in local cities. When walking in areas with fewer notable spots, the opportunities for user interaction decrease, often resulting in silence due to a lack of content. Additionally, some tourists may deviate from the intended routes, disrupting the optimal flow designed to enhance regional experiences. Our proposal, incorporating hierarchical geofencing and conversation generation techniques, provides more flexible and continuous guide interactions through the Onsite Radio App. Simply press the play button, slip your smartphone into your pocket, and start walking. Every step you take will be transformed into captivating storytelling delivered by virtual characters.
Sasaki et al.(2024). Hierarchical Geofencing for Location-Aware Generative Audio Tours. Urban Informatics, 3, 33, Springer Nature.