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14/10/2026

📢 Webinar Invitation!
📅 𝟭𝟰 𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟮𝟬𝟮𝟲 Today
⏰ 18:00 CEST | 12:00 EDT
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📢 Free Sensors Webinar Invitation!

🧠 𝗜𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗟𝗶𝘃𝗶𝗻𝗴: 𝗦𝗲𝗻𝘀𝗼𝗿-𝗔𝘀𝘀𝗶𝘀𝘁𝗲𝗱 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗖𝗮𝗿𝗲 𝗮𝗻𝗱 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲

📅 𝟭𝟰 𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟮𝟬𝟮𝟲
⏰ 18:00 CEST | 12:00 EDT
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Join Prof. Dr. Lili Liu and Dr. Antonio Miguel-Cruz as they host an insightful session on how sensors enable independent living and intelligent healthcare for older adults.

Highlights:
✅ EEG-based engagement monitoring in cognitive games
✅ Evaluation of high-accuracy home-monitoring systems for frailty
✅ Introduction to the related Special Issue + live Q&A

🆓 Completely free | Certificates available for live attendees

Register now 👉 https://sciforum.net/event/SENSORS-33

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14/10/2026

📢 Meet our Steering Committee Member for AIS 2027: Prof. Chwee Teck Lim 🌟

We are honored to welcome Prof. Chwee Teck Lim (National University of Singapore) as a Steering Committee Member of the 4th International Conference on AI Sensors and Transducers (AIS 2027).

📅 29 July – 3 August 2027 📍 Kunming, Yunnan, China

Prof. Lim is the NUS Society Chair Professor of Biomedical Engineering and Director of the Institute for Health Innovation and Technology (iHealthtech).

🏆 Celebrated for his research in mechanobiology, disease diagnostics, and the development of soft wearable sensors, with numerous prestigious awards and honors to his name.
Join AIS 2027 to connect with global experts and explore the future of AI sensors and intelligent systems!

📩 Abstract submission: https://sciforum.net/submissions/AIS2027/1
🌐 Website: https://sciforum.net/event/AIS2027

14/10/2026

📣📣📣 Call for Reading
𝐌𝐮𝐥𝐭𝐢𝐛𝐚𝐧𝐝 𝐀𝐧𝐭𝐞𝐧𝐧𝐚𝐬 𝐟𝐨𝐫 𝐌𝐨𝐝𝐞𝐫𝐧 𝐒𝐦𝐚𝐫𝐭𝐩𝐡𝐨𝐧𝐞𝐬 𝐚𝐧𝐝 𝐌𝐨𝐛𝐢𝐥𝐞 𝐃𝐞𝐯𝐢𝐜𝐞𝐬: 𝐀 𝐑𝐞𝐯𝐢𝐞𝐰
👨‍🏫 Yiming Fan; Changjiang Deng; et al.
🏫 Beijing Institute of Technology
💥 The rapid development of wireless communication systems has increased the complexity of smartphone antenna design. Modern terminals are required to simultaneously support Sub-1 GHz cellular bands, 5G New Radio (NR), millimeter-wave communication, satellite links, and emerging sensing services within limited physical space. As a result, multiband operation has become a central challenge for mobile terminals. This paper reviews the recent research advances in multiband smartphone antennas, organized according to the evolution from single-antenna to multi-antenna architectures and including both Sub-6 GHz and millimeter-wave applications. Single-antenna Sub-3 GHz techniques, multiband multi-antenna systems, dual-band millimeter-wave antennas, and integrated Sub-6 GHz/millimeter-wave architectures are systematically summarized. The key technologies, including multi-mode cooperation, characteristic-mode design, multiple-input multiple-output (MIMO) decoupling, and shared-aperture integration, are discussed. The emerging B5G/6G-oriented technologies are also highlighted. This review provides an overview of current design strategies and future trends for next-generation multiband smartphone antennas.
🔗 https://brnw.ch/21x6obW

The rapid development of wireless communication systems has increased the complexity of smartphone antenna design. Modern terminals are required to simultaneously support Sub-1 GHz cellular bands, 5G New Radio (NR), millimeter-wave communication, satellite links, and emerging sensing services within...

14/10/2026

📣📣📣 Call for Reading
𝐂𝐂𝐃 𝐏𝐢𝐱𝐞𝐥 𝐌𝐢𝐧𝐢𝐚𝐭𝐮𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐟𝐨𝐫 𝐒𝐩𝐚𝐭𝐢𝐚𝐥 𝐑𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭

👨‍🏫 Zhenyu Liu; Hao Xu; et al.
🏫 University of Electronic Science and Technology of China - UESTC
💥 Charge-coupled device (CCD) image sensors stand out for their high sensitivity, low noise, and strong radiation tolerance, which have established them as core components in high-end imaging fields such as astronomical observation, remote sensing, and defense and security. With increasingly stringent requirements for imaging system performance in emerging applications, including ultra-high resolution, intelligent sensing, and multimodal information fusion, CCD technology continues to evolve toward higher levels of integration and improved performance. Within a fixed sensor area, one of the most straightforward ways to raise image resolution is to shrink pixel size, that is, CCD pixel miniaturization. In this review, we provide a systematic survey of the major advances in CCD pixel miniaturization achieved in recent years. We first detail four mainstream CCD architectures—linear-array, full-frame, frame-transfer, and interline-transfer—along with several newly developed architectures, and compare their performance characteristics and application constraints. We then summarize the key technologies that enable pixel miniaturization and examine several closely related technological directions. Finally, we look at the current state of CCD pixel miniaturization and discuss its future development trends.🔗 https://brnw.ch/21x6o80

Charge-coupled device (CCD) image sensors stand out for their high sensitivity, low noise, and strong radiation tolerance, which have established them as core components in high-end imaging fields such as astronomical observation, remote sensing, and defense and security. With increasingly stringent...

14/10/2026

📣📣📣 Call for Reading
𝐀 𝐑𝐞𝐯𝐢𝐞𝐰 𝐨𝐟 𝐀𝐝𝐯𝐞𝐫𝐬𝐚𝐫𝐢𝐚𝐥 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐈𝐨𝐓 𝐒𝐞𝐧𝐬𝐨𝐫 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬: 𝐌𝐞𝐭𝐡𝐨𝐝𝐬, 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝 𝐄𝐝𝐠𝐞 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐂𝐨𝐧𝐬𝐭𝐫𝐚𝐢𝐧𝐭𝐬
👨‍🏫 Wenqiang Xu; Jian Li
🏫 Beijing University of Posts and Telecommunications
💥 Deep learning has been widely deployed in critical scenarios such as the Internet of Things (IoT), industrial sensing, network intrusion detection, and cyber-physical system monitoring, where model inference directly affects system security, operational reliability, and service continuity. However, existing adversarial example detection studies remain insufficient for practical IoT deployment, as their validation often overlooks endpoint resource constraints, heterogeneous data modalities, physical environmental interference, communication protocol specifications, adaptive attacks, and adversary capability models. Moreover, detection outcomes are rarely connected with deployment locations, computational overhead, formal security assurance, and subsequent response strategies, which limits their engineering applicability. To address these limitations, this review systematically synthesizes recent representative studies in adversarial example detection and constructs a unified analytical framework integrating detection evidence, IoT deployment feasibility, and adaptive-attack evaluation. Based on the source of detection evidence, existing methods are categorized into input-consistency-based, feature-statistics-based, predictive-uncertainty-based, model-reconstruction-based, runtime-context-aware, and multi-strategy fusion detection, while formal certification is discussed as an independent security-assurance dimension. The review further analyzes the principles, applicable conditions, limitations, compatibility conflicts with IoT deployment constraints, and typical failure modes of these methods. The analysis identifies four key challenges: the lack of IoT-native adaptive evaluation, limited anomaly-boundary identification and cross-modal generalization, insufficient deployment-time security assurance, and weak coordination between detection decisions and security responses. Future research should therefore emphasize feasible attack paradigms, hierarchical lightweight detection, reliable multimodal fusion, certifiable operational boundaries, and auditable end-to-end response mechanisms, thereby supporting the evaluation and deployment of adversarial example detection in IoT scenarios.
🔗 https://brnw.ch/21x6o7O

Deep learning has been widely deployed in critical scenarios such as the Internet of Things (IoT), industrial sensing, network intrusion detection, and cyber-physical system monitoring, where model inference directly affects system security, operational reliability, and service continuity. However, ...

14/10/2026

📣📣📣 Call for Reading
𝐒𝐞𝐧𝐬𝐨𝐫-𝐁𝐚𝐬𝐞𝐝 𝐓𝐫𝐚𝐜𝐤𝐢𝐧𝐠 𝐚𝐧𝐝 𝐋𝐨𝐜𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐈𝐧-𝐋𝐢𝐧𝐞 𝐈𝐧𝐬𝐩𝐞𝐜𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐬 𝐢𝐧 𝐎𝐢𝐥 𝐚𝐧𝐝 𝐆𝐚𝐬 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬: 𝐀 𝐑𝐞𝐯𝐢𝐞𝐰
👨‍🏫 Jianfeng Zheng; Bingfeng Ju; Anyu Sun
🏫 Zhejiang University, PipeChina Research Institute
💥 Accurate tracking and localization of in-line inspection (ILI) tools are essential for mileage calibration, defect mapping, and blockage prevention in oil and gas pipelines. This review summarizes sensor-based approaches for external ILI-tool localization, emphasizing how sensing physics, deployment geometry, and signal interpretation determine practical performance. Extremely low-frequency (ELF) magnetic tracking is first examined through dipole modeling, sensor evolution, and weak-signal recovery under steel-pipe and soil shielding. Distributed fiber-optic sensing is then reviewed as a continuous-tracking alternative, with attention to fading mitigation, spatiotemporal denoising, and trajectory extraction from distributed acoustic sensing data. Acoustic arrays and hybrid schemes are discussed as complementary options for subsea or cable-free environments. Finally, the review assesses how data fusion and lightweight artificial intelligence (AI) can improve robustness while noting unresolved issues in field data availability, edge computing, and uncertainty quantification. The synthesis indicates that next-generation ILI tracking should combine heterogeneous sensing, physics-aware signal processing, and deployment-aware model design rather than rely on a single high-sensitivity sensor.
🔗 https://brnw.ch/21x6o7z

Accurate tracking and localization of in-line inspection (ILI) tools are essential for mileage calibration, defect mapping, and blockage prevention in oil and gas pipelines. This review summarizes sensor-based approaches for external ILI-tool localization, emphasizing how sensing physics, deployment...

14/10/2026

📣📣📣 Call for Reading
𝐀 𝐑𝐞𝐯𝐢𝐞𝐰 𝐨𝐟 𝐏𝐡𝐲𝐬𝐢𝐜𝐬-𝐈𝐧𝐟𝐨𝐫𝐦𝐞𝐝 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐒𝐮𝐫𝐫𝐨𝐠𝐚𝐭𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐏𝐨𝐰𝐞𝐫 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐅𝐚𝐮𝐥𝐭 𝐃𝐢𝐚𝐠𝐧𝐨𝐬𝐢𝐬
👨‍🏫 Guangfen Wan; Kai Yang; et al.
🏫 Huazhong University of Science and Technology, China National Offshore Oil Corporation Ltd., Nanjing Tech University
💥 Power transformers are critical components of modern power grids, and their operational reliability directly affects power system security, stability, and continuity. With the increasing intelligence and complexity of power systems, condition monitoring and fault diagnosis of transformers have received growing attention. However, conventional diagnostic methods often face limitations such as complex modeling procedures, high computational costs, weak adaptability, and insufficient generalization under nonlinear and coupled operating conditions. In recent years, surrogate models have emerged as effective tools for transformer fault diagnosis because of their advantages in high-dimensional nonlinear mapping, rapid prediction, and data-driven approximation. This paper systematically reviews the research progress of surrogate models in transformer fault diagnosis and establishes a classification framework from the perspectives of model types, modeling strategies, data sources, and application scenarios. The principles, applicable conditions, and performance characteristics of representative surrogate models are comparatively analyzed. Furthermore, the advantages and limitations of different surrogate modeling approaches are discussed in terms of diagnostic accuracy, stability, generalization ability, interpretability, and computational efficiency. Although surrogate models show strong potential for intelligent transformer fault diagnosis, challenges remain in small-sample learning, data quality dependence, model interpretability, and cross-condition generalization. Future research should focus on multi-source information fusion, integration of physical mechanisms with data-driven learning, lightweight intelligent modeling, and standardized evaluation systems. This review aims to provide methodological guidance and technical references for the development of reliable, efficient, and interpretable transformer fault diagnosis methods.
🔗 https://brnw.ch/21x6o7q

Power transformers are critical components of modern power grids, and their operational reliability directly affects power system security, stability, and continuity. With the increasing intelligence and complexity of power systems, condition monitoring and fault diagnosis of transformers have recei...

14/10/2026

📣📣📣 Call for Reading
𝐑𝐞𝐜𝐞𝐧𝐭 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐬 𝐢𝐧 𝐅𝐥𝐞𝐱𝐢𝐛𝐥𝐞 𝐏𝐫𝐞𝐬𝐬𝐮𝐫𝐞 𝐒𝐞𝐧𝐬𝐨𝐫𝐬: 𝐌𝐞𝐜𝐡𝐚𝐧𝐢𝐬𝐦𝐬, 𝐌𝐚𝐭𝐞𝐫𝐢𝐚𝐥𝐬, 𝐃𝐞𝐬𝐢𝐠𝐧𝐬 𝐚𝐧𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
👨‍🏫 Xiuzhen Yang; Ying Yi; et al.
🏫 China University of Geosciences
💥 In recent years, the rapid development of flexible electronics, smart materials, and micro/nanofabrication technologies has greatly promoted the advancement of flexible pressure sensors. These sensors have achieved significant improvements in sensitivity, detection range, stability, and functional integration, demonstrating great potential for applications in wearable electronics, smart healthcare, and human–machine interaction. This review summarizes recent progress in flexible pressure sensors in terms of sensing mechanisms, functional materials, structural designs, and intelligent applications. First, the working principles and performance characteristics of typical sensing mechanisms, including piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, self-powered, and electrochemical sensing, are introduced and compared. Then, the development of key materials, such as flexible substrates, carbon-based nanomaterials, metal nanostructures, conductive hydrogels, and MXenes, is summarized. The effects of structural designs, including serpentine, three-dimensional porous, crack, wrinkle, and Kirigami structures, on flexibility, stretchability, sensitivity, detection range, and cycling stability are also discussed. Furthermore, the applications of flexible pressure sensors in pulse monitoring, blood pressure monitoring, human motion detection, cardiovascular health assessment, disease diagnosis, gesture recognition, human–machine interaction, and electronic skin are reviewed. Finally, the major challenges and future perspectives of flexible pressure sensors are discussed.
🔗 https://brnw.ch/21x6o79

In recent years, the rapid development of flexible electronics, smart materials, and micro/nanofabrication technologies has greatly promoted the advancement of flexible pressure sensors. These sensors have achieved significant improvements in sensitivity, detection range, stability, and functional i...

14/10/2026

📣📣📣 Call for Reading
𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 𝐂𝐨𝐧𝐠𝐞𝐬𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐄𝐧𝐚𝐛𝐥𝐢𝐧𝐠 𝐏𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐨𝐧 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐰𝐚𝐲𝐬 𝐃𝐮𝐫𝐢𝐧𝐠 𝐏𝐮𝐛𝐥𝐢𝐜 𝐇𝐨𝐥𝐢𝐝𝐚𝐲𝐬: 𝐀 𝐒𝐮𝐫𝐯𝐞𝐲 𝐨𝐟 𝐌𝐞𝐭𝐡𝐨𝐝𝐬, 𝐎𝐩𝐞𝐧 𝐈𝐬𝐬𝐮𝐞𝐬, 𝐚𝐧𝐝 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐬
👨‍🏫 Zheng Yang (Shanghai Jiao Tong University); Yizhe Wang (Tongji University); et al.
🏫 Shanghai Jiao Tong University, Tongji University, Jiangsu Runyang Bridge Development Co., Ltd.
💥 Expressway travel demand climbs steeply during public holidays, and the severe congestion that follows has become a principal constraint on both network operating efficiency and the quality of travel services. Dependable forecasting of holiday congestion, coupled with the practical realization of proactive management, accordingly carries considerable theoretical and practical weight for improving how expressways are operated and administered and for safeguarding efficient and safe public travel. Organized around the central theme of congestion prediction and proactive management for expressways over holiday periods, this paper reviews the progress of research across five interrelated areas: traffic speed and flow prediction methods; congestion state identification and forecasting; holiday travel characteristic analysis together with demand prediction; multi-source data fusion and congestion propagation mechanisms; and expressway traffic control together with traveler behavior guidance. Having surveyed the theoretical underpinnings, core technologies, and representative methods of each area, the paper concentrates in particular on the shortcomings and difficulties that existing studies encounter in coping with the hallmark features of holiday traffic, namely demand surges of short duration combined with pronounced spatiotemporal heterogeneity, and proceeds to outline promising avenues for subsequent research. Overall, the review seeks to provide wide-ranging literature support and a theoretical reference for developing technologies that predict and proactively manage congestion on expressways during public holidays.
🔗 https://brnw.ch/21x6o6E

Expressway travel demand climbs steeply during public holidays, and the severe congestion that follows has become a principal constraint on both network operating efficiency and the quality of travel services. Dependable forecasting of holiday congestion, coupled with the practical realization of pr...

13/10/2026

📌 Editor's Choice Highlight

The article "𝐒𝐞𝐜𝐨𝐧𝐝𝐬-𝐑𝐞𝐬𝐨𝐥𝐯𝐞𝐝 𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭𝐬 𝐨𝐟 𝐕𝐚𝐧𝐜𝐨𝐦𝐲𝐜𝐢𝐧 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐏𝐥𝐚𝐬𝐦𝐚 𝐭𝐨 𝐭𝐡𝐞 𝐈𝐧𝐭𝐞𝐫𝐬𝐭𝐢𝐭𝐢𝐚𝐥 𝐅𝐥𝐮𝐢𝐝 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭 𝐚 𝐏𝐚𝐭𝐡 𝐓𝐨𝐰𝐚𝐫𝐝𝐬 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐓𝐡𝐞𝐫𝐚𝐩𝐞𝐮𝐭𝐢𝐜 𝐃𝐫𝐮𝐠 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠" has been selected as an Editor's Choice article.

This work, by Julian Gerson, Kevin W. Plaxco and Tod E. Kippin from University of California, Santa Barbara, represents significant advancements in the field of real-time therapeutic drug monitoring.

Read the full article here: https://brnw.ch/21x6m7t

Continuous, in vivo drug and biomarker measurements could transform healthcare, enabling both the high-precision personalization of drug dosing and the real-time monitoring of health status. A practical realization of this vision, however, requires an improved understanding of the relationship betwe...