{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T08:19:45Z","timestamp":1763367585883,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T00:00:00Z","timestamp":1663977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>IoT encompasses various objects, technologies, communication standards, sensors, actuators in powered environments, and networked communication. The concept adopted here, IoT off-grid, considers an environment without commercial electricity and commercial internet. Managing various utilities with IoT and collecting the relevant information from this environment is the purpose of this project. It uses machine learning to select relevant data. These data are collected safely using a drone that travels through the off-grid stations. A systematic literature mapping is presented, identifying the state of the art. The result is a software architecture proposal with configurations in the drone and off-grid stations that contemplate data collection from the IoT off-grid environment. The results are also presented with different selection algorithms used in machine learning and final execution in the prototype.<\/jats:p>","DOI":"10.3390\/s22197241","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T03:34:17Z","timestamp":1664163257000},"page":"7241","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["IoT Off-Grid, Data Collection from a Machine Learning Classification Using UAV"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0087-5360","authenticated-orcid":false,"given":"Ademir","family":"Goulart","sequence":"first","affiliation":[{"name":"Computer Science Graduate Program, Federal University of Santa Catarina, Florian\u00f3polis 88040-370, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex Sandro Roschildt","family":"Pinto","sequence":"additional","affiliation":[{"name":"Computer Science Graduate Program, Federal University of Santa Catarina, Florian\u00f3polis 88040-370, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4758-2063","authenticated-orcid":false,"given":"Ad\u00e3o","family":"Boava","sequence":"additional","affiliation":[{"name":"Computer Science Graduate Program, Federal University of Santa Catarina, Florian\u00f3polis 88040-370, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kalinka R. L. J. Castelo","family":"Branco","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, Universidade de S\u00e3o Paulo, S\u00e3o Carlos 13566-590, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,24]]},"reference":[{"key":"ref_1","unstructured":"Watts, S. (2016). The Internet of Things (IoT): Applications, Technology, and Privacy Issues, Nova Publisher\u2019s."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Vijayalakshmi, S., and Muruganand, S. (2020, May 10). Wireless Sensor Networks: Architecture\u2014Applications\u2014Advancements. (Mercury Learning & Information 2018). Available online: http:\/\/search.ebscohost.com\/login.aspx?direct=true&db=nlebk&AN=1809144&lang=pt-br&site=ehost-live.","DOI":"10.1515\/9781683923275"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Di Francesco, M., Das, S.K., and Anastasi, G. (2011). 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