Predicting parking occupancy via machine learning in the web of things

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

4 Citations (Scopus)

179 Downloads (Pure)

Keywords

@article{b24cd27a7c884693bae3aad94ef56bf8,

title = "Predicting parking occupancy via machine learning in the web of things",

keywords = "UT-Hybrid-D",

author = "Provoost, {Jesper C.} and Andreas Kamilaris and Wismans, {Luc J.J.} and {van der Drift}, {Sander J.} and {van Keulen}, Maurice",

note = "Elsevier deal",

year = "2020",

month = dec,

doi = "10.1016/j.iot.2020.100301",

language = "English",

volume = "12",

pages = "100301",

journal = "Internet of Things",

issn = "2543-1536",

publisher = "Elsevier",

}

TY - JOUR

T1 - Predicting parking occupancy via machine learning in the web of things

AU - Provoost, Jesper C.

AU - Kamilaris, Andreas

AU - Wismans, Luc J.J.

AU - van der Drift, Sander J.

AU - van Keulen, Maurice

N1 - Elsevier deal

PY - 2020/12

Y1 - 2020/12

KW - UT-Hybrid-D

U2 - 10.1016/j.iot.2020.100301

DO - 10.1016/j.iot.2020.100301

M3 - Article

VL - 12

SP - 100301

JO - Internet of Things

JF - Internet of Things

SN - 2543-1536

ER -