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El‑Sheimy and Li Satell Navig (2021) 2:7 Page 20 of 23

capabilities, the integration between PLAN and artifcial Conclusion
intelligence will become tighter. Tis article frst reviews the market value, including the
social benefts and economic values, of indoor navi-
gation, followed by the classifcation from the marker
Data crowdsourcing (e.g., co-location) perspective and the main players. Ten, it compares
Te data from numerous consumer electronics and sen- the state-of-the-art sensors, including navigation sen-
sor networks will make crowdsourcing (e.g., co-location) sors and environmental-perception (as aiding sensors
a reality. As mentioned in the HD map subsection, the for navigation), and techniques, including position-fx-
crowdsourcing technique may fundamentally change ing, dead-reckoning, database matching, multi-sensor
the mode of map and HD map generation. Furthermore, fusion, and motion constraints. Finally, it points out
using crowdsourced data can enhance PLAN perfor- several future trends, including the improvement of
mance. For example, the crowdsourced data contains sensors, the use of multi-platform, multi-device, and
more comprehensive information than an ego-only car in multi-sensor information fusion, the development of
teams of map availability and sensing range. On the other self-learning algorithms and systems, the integration
hand, as pointed out in (Li et al. 2019e), how to select with 5G/IoT/edge computing, and the use of HD maps
the most valuable data from the crowdsourced big data for indoor PLAN.
to update the database is still a challenge. It is difcult to
evaluate the reliability of data automatically by the soft-
ware in the absence of manual intervention and lack of Authors’ contributions
NE devised the article structure and general contents and structure and
evaluation reference. writing parts of the manuscript. YL assisted in summarizing and writing the
manuscript. Both authors have read and approved the fnal manuscript.
Authors’ information
Integration with 5G, IoT, and edge/fog computing Naser El‑Sheimy is a Professor at the Department of Geomatics Engineering,
As described in the 5G subsection, the development of the University of Calgary. He is a Fellow of the Canadian Academy of Engineer‑
5G and IoT technologies are changing PLAN. Te new ing and the US Institute of Navigation and a Tier‑I Canada Research Chair in
Geomatics Multi‑sensor Systems. His research expertise includes Geomatics
features (e.g., dense miniaturized base stations, mm- multi‑sensor systems, GPS/INS integration, and mobile mapping systems. He
wave MIMO, and device-to-device communication) is also the founder and CEO of Profound Positioning Inc. He published two
can directly enhance PLAN. Also, the combination of books, 6 book chapters, and over 450 papers in academic journals, conference
and workshop proceedings, in which he has received over 30 paper awards.
5G/IoT and edge/fog computing will bring new PLAN He supervised and graduated over 60 Masters and Ph.D. students. He is the
opportunities. Edge/fog computing allows data process- recipient of many national and international awards including the ASTech
ing as close to the source as possible, enables PLAN data “Leadership in Alberta Technology” Award, and the Association of Professional
Engineers, Geologists, and Geophysicists of Alberta (APEGGA) Educational
processing with faster speed, reduces latency, and gives Excellence Award.
overall better outcomes. Te review papers (Oteafy and
Hassanein 2018) and (Shi et al. 2016) provide detailed You Li is a Senior Researcher at the University of Calgary. He received Ph.D.
degrees from both Wuhan University and the University of Calgary in 2016
overviews of edge computing and fog computing, respec- and was selected for the national young talented project in 2020. His research
tively. Such techniques may be able to change the exist- focuses on ubiquitous internet‑of‑things localization. He has hosted/partici‑
ing operation mode on HD maps and for PLAN. It may pated in four national research projects, and co‑published over 70 academic
papers, and has over 20 patents pending. He serves as an Associate Editor for
become possible to online repair or optimize HD maps the IEEE Sensors Journal, a committee member at the IAG unmanned naviga‑
by using SLAM and artifcial intelligence technologies. tion system and ISPRS mobile mapping working groups. He has won four
best paper awards and a winner in the EvAAL international indoor localization
competition.
HD maps for indoor navigation Funding
HD maps will be extended from outdoors to indoors. Te This work was supported by Canada Research Chairs programs (Grant No.
RT691875).
cooperation among the manufacturers of cars, maps, 5G,
and consumer devices have already shown its importance Availability of data and materials
(Abuelsamid 2017). Te high accuracy and rich informa- Data sharing is not applicable to this article as no datasets were generated or
analyzed in this review article.
tion of the HD map make it a valuable indoor PLAN sen-
sor and even a platform that links people, vehicles, and Competing interests
the environment. Indoor and outdoor PLAN may need The authors declare that they have no competing interests.
diferent HD map elements. Terefore, diferent HD Received: 3 November 2020 Accepted: 9 February 2021
maps may be developed according to diferent scenarios.
Similar to outdoors, the standardization of indoor HD
maps will be important but challenging.