| id |
cdrf2019_124 |
| authors |
Maider Llaguno-Munitxa and Elie Bou-Zeid |
| year |
2020 |
| title |
Sensing the Environmental Neighborhoods Mobile Urban Sensing Technologies (MUST) for High Spatial Resolution Urban Environmental Mapping |
| source |
Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020) |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_12
|
| summary |
Given the benefits of fine mapping of large urban areas affordably, mobile environmental sensing technologies are becoming increasingly popular to complement the traditional stationary weather and air quality sensing stations. However the reliability and accuracy of low-cost mobile urban technologies is often questioned. This paper presents the design of a fast-response, autonomous and affordable Mobile Urban Sensing Technology (MUST) for the acquisition of high spatial resolution environmental data. Only when accurate neighborhood scale environmental data is affordable and accessible for architects, urban planners and policy makers, can design strategies to enhance urban health be effectively implemented. The results of an experimental air quality sensing campaign developed within Princeton University Campus is presented. |
| series |
cdrf |
| email |
m.llagunomunitxa@northeastern.edu |
| full text |
 file.pdf (4,115,115 bytes) |
| references |
Content-type: text/plain
|
| last changed |
2022/09/29 07:51 |
