preprints_ui: gnhvr_v1
Data license: ODbL (database) & original licenses (content) · Data source: Open Science Framework
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gnhvr_v1 | Good use of big data: building a home for everyone | The ongoing COVID-19 pandemic should teach us some lessons at health, environmental and human levels toward more fairness, human cohesion and environmental sustainability. At a health level, the pandemic raises the importance of housing for everyone particularly vulnerable and homeless people to protect them from the disease and other similar airborne pandemics. Here, I propose to make good use of big data along with 3D construction printers to solve major and pressing needs of housing worldwide. Big data can be used to calculate how many people do need accommodations and 3D construction printers to build houses accordingly and swiftly. The combination of such facilities- big data and 3D printers- can help solve global housing crises more efficiently than traditional and unguided construction plans. This is particularly urgent under environmental and major health crises where health and housing are tightly interrelated. | 2020-08-26T12:01:46.168629 | 2023-10-02T21:33:18.930139 | 2020-08-26T12:10:12.219200 | https://doi.org/10.1016/j.cities.2020.102903 | arabixiv | 1 | accepted | 1 | 1 | https://doi.org/10.31221/osf.io/gnhvr | No license | 3D construction; 3D house printer; big data; big data use; city construction; city development plan; coronavirus; covid; covid6-19; homelessness; house construction; housing crisis | ["3D construction", "3D house printer", "big data", "big data use", "city construction", "city development plan", "coronavirus", "covid", "covid6-19", "homelessness", "house construction", "housing crisis"] | Khaled Moustafa | [{"id": "zp23m", "name": "Khaled Moustafa", "index": 0, "orcid": "", "bibliographic": true}] | Khaled Moustafa | Business; Architecture; Physical Sciences and Mathematics; Medicine and Health Sciences; Arts and Humanities; Life Sciences; Social and Behavioral Sciences; Education; Engineering; Law | [{"id": "5a57d9cd076808000d815256", "text": "Business"}, {"id": "5a57d9cf076808000d815263", "text": "Architecture"}, {"id": "5a57d9d0076808000d815268", "text": "Physical Sciences and Mathematics"}, {"id": "5a57d9d0076808000d81526c", "text": "Medicine and Health Sciences"}, {"id": "5a57d9d0076808000d81526e", "text": "Arts and Humanities"}, {"id": "5a57d9d3076808000d8152a2", "text": "Life Sciences"}, {"id": "5a57d9d3076808000d8152b5", "text": "Social and Behavioral Sciences"}, {"id": "5a57d9d3076808000d8152b7", "text": "Education"}, {"id": "5a57d9d4076808000d8152e3", "text": "Engineering"}, {"id": "5a57d9d5076808000d8152f4", "text": "Law"}] | https://osf.io/download/5f464f3cbacde802db340e86 | 0 | not_applicable | not_applicable | [] | 2025-04-09T20:04:07.409618 |