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Electronics
Special Issues
IoT Sensing and Generalization
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IoT Sensing and Generalization

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 1824

Special Issue Editors

Dr. Jianwei Liu

E-Mail Website
Guest Editor
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
Interests: mobile computing; wireless sensing; IoT security; artificial intelligence
Dr. Han Ding

E-Mail Website
Guest Editor
Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
Interests: AIOT; smart sensing; human-centric applications
Special Issues, Collections and Topics in MDPI journals
Dr. Ge Wang

E-Mail Website
Guest Editor
Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
Interests: AIoT; multi-modality fusion; intelligent decision
Special Issues, Collections and Topics in MDPI journals
Dr. Fei Wang

E-Mail Website
Guest Editor
School of Software Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Interests: machine learning; deep learning; sensors; signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

IoT sensing technologies (e.g., millimeter-wave radar, Wi-Fi, UWB, RFID, acoustic, and 5G/6G signals) have revolutionized environmental and human activity perception by leveraging ubiquitous electromagnetic signals as sensing media.

Despite rapid advancements, ​the capability for generalization remains a critical bottleneck for IoT sensing systems. Environmental dynamics (e.g., layout changes, multipath interference) and human variability (e.g., posture, motion patterns) often degrade sensing accuracy, limiting real-world deployment.

This Special Issue seeks to address these challenges by soliciting research on the following topics:

  1. Synthetic data generation;
  2. ​Self-supervised learning;
  3. Generalizable representation learning;
  4. Continuous learning;
  5. Wireless sensing with LLMs;
  6. ​Cross-domain adaptation;
  7. Multimodal wireless sensing;
  8. Explainable wireless sensing;
  9. Novel applications;
  10. ​Integrated sensing and communication.

We look forward to receiving your contributions.

Dr. Jianwei Liu
Dr. Han Ding
Dr. Ge Wang
Dr. Fei Wang
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 250 words) can be sent to the Editorial Office for assessment.

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.

Keywords

  • wireless sensing
  • domain adaption
  • cross-domain
  • domain generalization
  • data generation
  • LLM

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Published Papers (2 papers)

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15 pages, 2735 KB  
Article
IBPS—A Novel Integrated Battery Protection System Based on Novel High-Precision Pressure Sensing
by Meiya Dong, Biaokai Zhu, Fangyong Tan and Gang Liu
Electronics 2026, 15(5), 1013; https://doi.org/10.3390/electronics15051013 - 28 Feb 2026
Viewed by 234
Abstract
Nowadays, thermal runaway accidents involving lithium batteries in new energy vehicles and energy storage power stations occur frequently, with battery deformation pressure as the core precursor signal. Traditional battery protection schemes suffer from limitations, including wired connections, limited real-time remote monitoring, and insufficient [...] Read more.
Nowadays, thermal runaway accidents involving lithium batteries in new energy vehicles and energy storage power stations occur frequently, with battery deformation pressure as the core precursor signal. Traditional battery protection schemes suffer from limitations, including wired connections, limited real-time remote monitoring, and insufficient sensing accuracy, rendering them unable to meet the safety monitoring needs of large-scale battery modules. Therefore, a high-precision pressure-sensing battery protection system based on the Internet of Things has been developed. This paper selects a MEMS high-precision pressure sensor with an accuracy of ±0.1 kPa to design an IoT sensing node based on the STM32L431 and LoRa/Wi-Fi 6, integrating pressure sensing and wireless communication. It proposes a sliding-average filtering and wavelet denoising algorithm, as well as a temperature-compensation calibration model, to optimize sensing accuracy. Additionally, it constructs a hierarchical early warning model based on pressure thresholds. The experiment demonstrates that the sensor achieves a detection accuracy of 99.2%, a response delay of less than 50 ms, a transmission packet loss rate of less than 0.5%, an end-to-end delay of less than 200 ms, and an early warning accuracy rate of 99.2% under battery overcharge/overtemperature conditions. The innovation of this study lies in the first integration of high-precision pressure sensing and IoT communication for battery protection. A low-power IoT sensing node tailored for battery aging scenarios has been designed, validating the novel application value of IoT sensing in the safety monitoring of new energy equipment. This system fills a gap in IoT pressure-sensing technology for battery protection, enabling practical applications and serving as a reference for implementing integrated sensing and communication technology. Full article
(This article belongs to the Special Issue IoT Sensing and Generalization)
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26 pages, 885 KB  
Article
LORA-to-LEO Satellite—A Review with Performance Analysis
by Alessandro Vizzarri
Electronics 2026, 15(1), 46; https://doi.org/10.3390/electronics15010046 - 23 Dec 2025
Cited by 1 | Viewed by 1262
Abstract
The Satellite Internet of Things (IoT) sector is undergoing rapid transformation, driven by breakthroughs in satellite communications and the pressing need for seamless global coverage—especially in remote and poorly connected regions. In locations where terrestrial infrastructure is limited or non-existent, Low Earth Orbit [...] Read more.
The Satellite Internet of Things (IoT) sector is undergoing rapid transformation, driven by breakthroughs in satellite communications and the pressing need for seamless global coverage—especially in remote and poorly connected regions. In locations where terrestrial infrastructure is limited or non-existent, Low Earth Orbit (LEO) satellites are proving to be a game-changing solution, delivering low-latency and high-throughput links well-suited for IoT deployments. While North America currently dominates the market in terms of revenue, the Asia-Pacific region is projected to lead in growth rate. Nevertheless, the development of satellite IoT networks still faces hurdles, including spectrum regulation and international policy alignment. In this evolving landscape, the LoRa and LoRaWAN protocols have been enhanced to support direct communication with LEO satellites, typically operating at altitudes between 500 km and 2000 km. This paper offers a comprehensive review of current research on LoRa/LoRaWAN technologies integrated with LEO satellite systems, also providing a performance assessment of this combined architecture in terms of theoretical achievable bitrate, Bit Error Rate (BER), and path loss. The results highlight the main performance trends of LoRa LR-FHSS in direct-to-LEO links. Path loss increases sharply with distance, reaching approximately 150 dB at 500 km and 165–170 dB at 2000 km, significantly reducing achievable data rates. At 500 km, bitrates range from approximately 7–8 kbps for SF7 to below 2 kbps for SF12. BER follows a similar trend: below 200 km, values remain low (10−4–10−3) for all spreading factors. At 1000 km, BER rises to approximately 3.9×10−3 for SF7 and 1.5×10−3 for SF12. At 2000 km, BER reaches approximately 4.7×10−2 for SF7 but stays below 2×10−2 for SF12, showing a 2–3× improvement with higher spreading factors. Overall, many links exhibit path loss above 160 dB and BER in the 10−3–10−2 range at long distances. These results underscore the importance of adaptive spreading factor selection and LR-FHSS gain for reliable long-range satellite IoT connectivity, highlighting the trade-off between robustness and spectral efficiency. Full article
(This article belongs to the Special Issue IoT Sensing and Generalization)
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