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However, in-person home deployment poses limitations around scalability and is not a feasible method in the context of the COVID-19 pandemic. The smart home research community is now facing the need to reshape and innovate research methods and design approaches. This study introduces a scalable smart home platform prototype that demonstrates possible solutions to address issues and limitations posed by the pandemic, such as improving package design, enabling user-driven installation, and facilitating remote evaluation and maintenance. The prototype uses off-the-shelf products with specially designed packaging to ensure interoperability as well as ease of shipping and installation. In this study, the prototype kits were shipped to participants' homes to understand and evaluate user perceptions and experiences around installation and initial use. Responses to a post-installation questionnaire and remote monitoring of system status showed that the participants easily completed their self-installation of the prototype without any on-site support. The study also showed potential for a scenario-based evaluation of the prototype using a remote, contactless research procedure.<\/jats:p>","DOI":"10.1145\/3512961","type":"journal-article","created":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T16:54:59Z","timestamp":1649350499000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Reshaping the Smart Home Research and Development in the Pandemic Era: Considerations around Scalable and Easy-to-Install Design"],"prefix":"10.1145","volume":"6","author":[{"given":"Heesuk","family":"Son","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaiwoo","family":"Lee","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shabnam","family":"FakhrHosseini","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenghung","family":"Lee","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph F.","family":"Coughlin","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Rudnik","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,4,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445122"},{"key":"e_1_2_1_2_1","volume-title":"Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675","author":"Abu-El-Haija Sami","year":"2016","unstructured":"Sami Abu-El-Haija , Nisarg Kothari , Joonseok Lee , Paul Natsev , George Toderici , Balakrishnan Varadarajan , and Sudheendra Vijayanarasimhan . 2016. 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