IoT-Enhanced Localization: Smart Technologies and Systems for Intelligent Environments

Dear Colleagues,

The rapid diffusion of the Internet of Things (IoT) has transformed commercial buildings into complex, interconnected ecosystems. Indoor localization—the process of determining the position of people or objects within indoor environments—has emerged as a key enabler of a wide range of applications and services, from guiding pedestrians within large buildings such as shopping malls, airports, and hospitals, to improving emergency response times and enhancing asset tracking efficiency. IoT also supports a broad array of location-based services tailored to users’ positions.

While outdoor localization typically relies on the Global Positioning System (GPS)—which is considered the de facto standard—indoor localization presents several challenges such as signal attenuation, multipath effects, and complex architectural layouts. These challenges affect the accuracy of indoor localization systems and have stimulated the development of innovative solutions leveraging heterogeneous IoT devices and infrastructures, machine learning technologies, edge and cloud computing, and other state-of-the-art techniques to optimize performance.

This Special Issue, titled “IoT-Enhanced Localization: Smart Technologies and Systems for Intelligent Environments”, aims to synthesize high-quality research that explores how IoT paradigms are reshaping the landscape of indoor localization systems.

_______________________________________________

Scope
We invite submissions addressing a broad spectrum of topics related to indoor localization in the context of IoT, including, but not limited to, the following:

• IoT Architectures for Indoor Localization: the design and deployment of IoT infrastructures supporting accurate and scalable indoor localization systems.
• IoT Sensor Fusion and Data Integration: combining multi-modal IoT data streams to enhance the precision, reliability, and robustness of indoor positioning systems.
• AI for IoT-based Localization: the development of AI-driven approaches—such as deep learning, reinforcement learning, and hybrid models—that leverage IoT devices and infrastructures for localization.
• Temporal and Dynamic Indoor Localization: addressing challenges posed by changing indoor layouts, crowd movements, and environmental changes, and developing strategies to account for these dynamics.
• Benchmarking, Standards, and Datasets: the evaluation of publicly available datasets and the creation of new, high-quality benchmarks for comparative research.
• Energy-Aware and Low-Latency Systems: the optimization of energy consumption and latency for battery-powered and real-time IoT-based localization systems.
• Privacy and Security in IoT-Enabled Localization: ensuring secure localization, user anonymity, and privacy-preserving data processing in smart environments.
• Use Cases and Real-World Deployments: case studies and pilot projects in hospitals, industrial sites, shopping centers, museums, public buildings, and other locations.

We look forward to receiving your contributions and insights.

Dr. Gaetano La Delfa
Dr. Salvatore Monteleone
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• indoor localization
• real-time positioning
• Internet of Things (IoT)
• IoT infrastructure
• sensor fusion
• smart environments
• machine learning
• artificial intelligence (AI)
• edge computing
• location-based services
• privacy and security
• indoor localization benchmark datasets