Advanced Sensors and Techniques for Indoor Positioning and Localization
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".
Deadline for manuscript submissions: 25 November 2025 | Viewed by 47
Special Issue Editors
Interests: indoor localization; wireless communications; IoT and machine learning for communications
Special Issues, Collections and Topics in MDPI journals
Interests: indoor localization; machine learning; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Accurate indoor positioning is a promoting field with diverse applications across various domains. Depending on the required precision, it can support tasks such as line traceability, telemanipulation, telemedicine, and drone control. By addressing the limitations of outdoor GNSS, indoor positioning technologies enable seamless indoor/outdoor tracking and serve as key enablers for IoT and Industry 4.0.
A wide range of methods have been explored in the literature, yet no single solution proves optimal for all scenarios. Different physical parameters can be utilized, including inertial data, ultrasound signals, radiofrequency electromagnetic waves, and visual data. These measurements can be deployed using various approaches such as fingerprinting or more advanced artificial intelligence techniques.
System design further introduces additional degrees of freedom, allowing for dedicated infrastructure deployment. Trade-offs between accuracy and cost can also be managed by leveraging existing RF infrastructures such as Wi-Fi and Bluetooth networks. Moreover, modern devices—including smartphones and tablets equipped with cameras, sensors, wireless connectivity, and powerful processors—present new opportunities for advancing indoor positioning technologies.
This Special Issue invites innovative contributions that push the boundaries of indoor positioning, measurement techniques, estimation methods, system architectures, devices, and applications.
Dr. Wafa Njima
Dr. Iness Ahriz
Guest Editors
Manuscript Submission Information
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Keywords
- sensors
- indoor localization
- internet of things
- accuracy
- energy consumption
- sensing
- communication
- artificial intelligence
- machine learning
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