{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:51:13Z","timestamp":1760230273199,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T00:00:00Z","timestamp":1658188800000},"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>The goal of this work is to present a systematic literature mapping (SLM) identifying algorithms for the search for data, determining the best path and types of communication between the local server and the drone, as well as possible simulators to validate proposed solutions. The concept, here considered as IoT Off-Grid, is characterized by being an environment without commercial electrical infrastructure and without communication connected to the internet. IoT equipment generates data to be stored on a local server. It collects these data through a drone that searches each local server for later integration with the commercial internet environment. As a result, we have algorithms to determine the best path based on the TSP\u2014travelling salesman problem. Different types of communication between the drone and the server contain the data, predominantly WiFi 802.11. As a simulator, OMNeT++ stands out.<\/jats:p>","DOI":"10.3390\/s22145374","type":"journal-article","created":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T08:28:25Z","timestamp":1658219305000},"page":"5374","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Data Collection in an IoT Off-Grid Environment Systematic Mapping of Literature"],"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"}]},{"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","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":[[2022,7,19]]},"reference":[{"key":"ref_1","unstructured":"Keele, S. 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