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Cloud Platforms for Context-Adaptive Positioning and Localisation in GNSS-Denied Scenarios-A Systematic Review
Darwin Quezada-Gaibor1,2, Joaquín Torres-Sospedra3, Jari Nurmi2
1Institute of New Imaging Technologies, Universitat Jaume I, 12071 Castellon, Spain.
Sensors (Basel, Switzerland)
|January 11, 2022
Summary
This review systematically analyzes cloud-based positioning platforms for Global Navigation Satellite System (GNSS)-denied environments. It highlights limitations in computing, privacy, and fault tolerance, suggesting areas for future research in indoor positioning.
Area of Science:
- Computer Science
- Geomatics Engineering
- Ubiquitous Computing
Background:
- Cloud platforms offer essential capabilities like data redundancy, scalability, and security for businesses.
- Location-Based Services (LBS) frequently utilize cloud platforms for hosting positioning and localization systems.
- GNSS-denied environments present unique challenges for accurate positioning and localization.
Purpose of the Study:
- To systematically review current positioning platforms for GNSS-denied scenarios.
- To comprehensively analyze components of positioning and localization systems, including techniques, protocols, standards, and cloud services.
- To identify limitations and shortcomings in existing solutions, focusing on computing paradigms, privacy, and fault tolerance.
Main Methods:
- Systematic literature review of state-of-the-art positioning and localization systems.
- Comprehensive analysis of system components: techniques, protocols, standards, and cloud services.
- Identification and examination of limitations in computing paradigms, privacy, and fault tolerance.
Main Results:
- Existing positioning platforms in GNSS-denied scenarios exhibit limitations in computing paradigms, privacy, and fault tolerance.
- Analysis reveals a need for enhanced contributions in efficient computation, interoperability, and robust positioning/localization.
- Current solutions often overlook critical aspects rarely scrutinized in indoor positioning reviews.
Conclusions:
- Cloud platforms are crucial for LBS, but current solutions for GNSS-denied scenarios require significant improvements.
- Future research should address identified limitations to enhance the efficiency, privacy, and fault tolerance of cloud-based positioning systems.
- Addressing these challenges is vital for advancing reliable indoor positioning and localization technologies.
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