Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890437568> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2890437568 endingPage "139" @default.
- W2890437568 startingPage "130" @default.
- W2890437568 abstract "The knowledge of spatial distributions of physical quantities, such as radio-frequency (RF) interference, pollution, geomagnetic field magnitude, temperature, humidity, audio, and light intensity, will foster the development of new context-aware applications. For example, knowing the distribution of RF interference might significantly improve cognitive radio systems [1], [2]. Similarly, knowing the spatial variations of the geomagnetic field could support autonomous navigation of robots (including drones) in factories and/or hazardous scenarios [3]. Other examples are related to the estimation of temperature gradients, detection of sources of RF signals, or percentages of certain chemical components. As a result, people could get personalized health-related information based on their exposure to sources of risks (e.g., chemical or pollution). We refer to these spatial distributions of physical quantities as spatial fields. All of the aforementioned examples have in common that learning the spatial fields requires a large number of sensors (agents) surveying the area [4], [5]." @default.
- W2890437568 created "2018-09-27" @default.
- W2890437568 creator A5006962534 @default.
- W2890437568 creator A5015328771 @default.
- W2890437568 creator A5064176463 @default.
- W2890437568 creator A5070127242 @default.
- W2890437568 date "2018-09-01" @default.
- W2890437568 modified "2023-10-12" @default.
- W2890437568 title "Crowd-Based Learning of Spatial Fields for the Internet of Things: From Harvesting of Data to Inference" @default.
- W2890437568 cites W1486103344 @default.
- W2890437568 cites W1978200836 @default.
- W2890437568 cites W1980701825 @default.
- W2890437568 cites W1981120211 @default.
- W2890437568 cites W1994500462 @default.
- W2890437568 cites W1999479532 @default.
- W2890437568 cites W2005420066 @default.
- W2890437568 cites W2022649085 @default.
- W2890437568 cites W2028082528 @default.
- W2890437568 cites W2034377106 @default.
- W2890437568 cites W2083888899 @default.
- W2890437568 cites W2084501074 @default.
- W2890437568 cites W2110820763 @default.
- W2890437568 cites W2117206394 @default.
- W2890437568 cites W2147573544 @default.
- W2890437568 cites W2164729653 @default.
- W2890437568 cites W2166315077 @default.
- W2890437568 cites W2329460483 @default.
- W2890437568 cites W2506048546 @default.
- W2890437568 cites W2600064692 @default.
- W2890437568 cites W2622833445 @default.
- W2890437568 cites W2658814799 @default.
- W2890437568 cites W2753687595 @default.
- W2890437568 cites W2762342550 @default.
- W2890437568 cites W2807931621 @default.
- W2890437568 cites W2808674840 @default.
- W2890437568 doi "https://doi.org/10.1109/msp.2018.2840156" @default.
- W2890437568 hasPublicationYear "2018" @default.
- W2890437568 type Work @default.
- W2890437568 sameAs 2890437568 @default.
- W2890437568 citedByCount "21" @default.
- W2890437568 countsByYear W28904375682019 @default.
- W2890437568 countsByYear W28904375682020 @default.
- W2890437568 countsByYear W28904375682021 @default.
- W2890437568 countsByYear W28904375682022 @default.
- W2890437568 countsByYear W28904375682023 @default.
- W2890437568 crossrefType "journal-article" @default.
- W2890437568 hasAuthorship W2890437568A5006962534 @default.
- W2890437568 hasAuthorship W2890437568A5015328771 @default.
- W2890437568 hasAuthorship W2890437568A5064176463 @default.
- W2890437568 hasAuthorship W2890437568A5070127242 @default.
- W2890437568 hasBestOaLocation W28904375682 @default.
- W2890437568 hasConcept C110875604 @default.
- W2890437568 hasConcept C119857082 @default.
- W2890437568 hasConcept C136764020 @default.
- W2890437568 hasConcept C154945302 @default.
- W2890437568 hasConcept C2522767166 @default.
- W2890437568 hasConcept C2776214188 @default.
- W2890437568 hasConcept C3018396927 @default.
- W2890437568 hasConcept C41008148 @default.
- W2890437568 hasConcept C49774154 @default.
- W2890437568 hasConcept C81860439 @default.
- W2890437568 hasConceptScore W2890437568C110875604 @default.
- W2890437568 hasConceptScore W2890437568C119857082 @default.
- W2890437568 hasConceptScore W2890437568C136764020 @default.
- W2890437568 hasConceptScore W2890437568C154945302 @default.
- W2890437568 hasConceptScore W2890437568C2522767166 @default.
- W2890437568 hasConceptScore W2890437568C2776214188 @default.
- W2890437568 hasConceptScore W2890437568C3018396927 @default.
- W2890437568 hasConceptScore W2890437568C41008148 @default.
- W2890437568 hasConceptScore W2890437568C49774154 @default.
- W2890437568 hasConceptScore W2890437568C81860439 @default.
- W2890437568 hasIssue "5" @default.
- W2890437568 hasLocation W28904375681 @default.
- W2890437568 hasLocation W28904375682 @default.
- W2890437568 hasOpenAccess W2890437568 @default.
- W2890437568 hasPrimaryLocation W28904375681 @default.
- W2890437568 hasRelatedWork W151193258 @default.
- W2890437568 hasRelatedWork W2355862304 @default.
- W2890437568 hasRelatedWork W2379418341 @default.
- W2890437568 hasRelatedWork W2511279186 @default.
- W2890437568 hasRelatedWork W2767782444 @default.
- W2890437568 hasRelatedWork W2961085424 @default.
- W2890437568 hasRelatedWork W3030475315 @default.
- W2890437568 hasRelatedWork W4200634454 @default.
- W2890437568 hasRelatedWork W4286629047 @default.
- W2890437568 hasRelatedWork W4224009465 @default.
- W2890437568 hasVolume "35" @default.
- W2890437568 isParatext "false" @default.
- W2890437568 isRetracted "false" @default.
- W2890437568 magId "2890437568" @default.
- W2890437568 workType "article" @default.