SCC-IRG Track 1: Strengthening Elderly Mobility in Urban Landscapes: Towards Age-Inclusive and Equitable Communities
- Institution
- Northeastern University, MA
- Principal investigator
- Qi Wang
- Funding
- $1.6M
- Duration
- 2024–2027
Moonbase score
Still being scored
Abstract
This Smart & Connected Communities (SCC) project supports research to address the crucial challenge of urban mobility for aging population by leveraging artificial intelligence (AI) and virtual reality (VR) technologies. Enabled by realistic urban simulations, this project aims to improve how cities accommodate the mobility needs of older adults, making urban environments more accessible and inclusive. The novelty lies in the methodology for transforming infrastructure planning, design, and operation through advanced technologies while emphasizing social equity and user experience. The project outcomes could be used to foster inclusivity in civil infrastructure systems, enhance quality of life for the elderly, and provide educational opportunities to inspire the next generation of engineers and scientists. This research tackles an often-overlooked problem in many cities that older adults face when navigating complex urban spaces. It becomes increasingly critical as the global population ages and civil infrastructures remain underfunded. The project employs a novel data-driven framework that integrates temporal point process-based deep learning (TPP-DL) with VR to self-generate dynamic, immersive simulations. These tools not only reflect the actual mobility challenges experienced by older adults but also allow for identification and mitigation of biases in infrastructure planning, design, and operation. By incorporating community feedback and utilizing edge computing for real-time data processing, the project ensures that the solutions being developed are both effective and practical. The long-term goal is to create smarter, more inclusive cities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Qi WangPI
- Jing Du
- Yanzhi Wang
- Chen Chen
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