Human mobility modeling has many applications in location-based services, mobile networking, city management, and epidemiology. Previous sensing approaches for human mobility are mainly categorized into two types: stationary sensing systems (e.g., surveillance cameras and toll booths) and mobile sensing systems (e.g., smartphone apps and vehicle tracking devices). However, stationary sensing systems only provide mobility information of human in limited coverage (e.g., camera-equipped roads) and mobile sensing systems only capture a limited number of people (e.g., people using a particular smartphone app). In this work, we design a novel system Mohen to model human mobility with a heterogeneous sensing system. The key novelty of Mohen is to fundamentally extend the sensing coverage of a large-scale stationary sensing system with a small-scale sensing system. Based on the evaluation on data from real-world urban sensing systems, our system outperforms them by 35% and achieves a competitive result to an Oracle method.
We introduce a method for gas sensing without performing direct spectrum measurement using broadband mid-infrared optical parametric oscillators, and experimentally demonstrate proof-of-concept carbon dioxide sensing.
more » « less- Award ID(s):
- 1846273
- NSF-PAR ID:
- 10417281
- Date Published:
- Journal Name:
- Optical Sensors 2022
- Page Range / eLocation ID:
- SM1E.1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1364/SENSORS.2022.SM1E.1
