Prof. Fang Xu | Gas Detector | Best Researcher Award

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Prof. Fang Xu | Gas Detector | Best Researcher Award 

Prof. Fang Xu, Shenzhen Technology University,China

Prof. Fang Xu is an Associate Professor and Master’s Supervisor, serving as the Head of the Department of Applied Physics. She is a Shenzhen Overseas High-level Talent (Peacock Program Category C) with expertise in semiconductor gas sensors, optoelectronic devices, solar cells, and biosensors. She has published 15 SCI papers in high-impact journals such as Advanced Materials, Advanced Energy Materials, and Sensors and Actuators B: Chemical as the first or corresponding author. She holds three national invention patents and actively contributes as a guest editor and reviewer for several scientific journals. Dr. [Name] earned her Ph.D. in Electrical Engineering from The Chinese University of Hong Kong (2018) and a Bachelor’s degree in Applied Physics from Huazhong University of Science and Technology (2012). She has received multiple awards, including First Prize in the National Final of the “China University Students Mechanical Engineering Innovation and Creativity Competition” as an instructor and the Outstanding Oral Presentation Award at the 15th National Conference on Gas and Humidity Sensing Technology.

Professional Profile:

ORCID

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Suitability for Best Researcher Award

Fang Xu is a highly accomplished researcher whose expertise spans semiconductor gas sensors, optoelectronic devices, solar cells, and biosensors. Her extensive contributions to these fields, particularly through high-impact publications, patents, and leadership roles, make her a strong candidate for the Best Researcher Award.

🎓 Education

📍 Ph.D. in Electrical Engineering (2013.8 – 2018.11)
🔹 The Chinese University of Hong Kong (CUHK)

📍 B.Sc. in Applied Physics (2008.9 – 2012.6)
🔹 Huazhong University of Science and Technology (HUST)

🏢 Work Experience

👩‍🏫 Associate Professor / Master’s Supervisor
📌 Head of the Department of Applied Physics
🌍 Shenzhen Overseas High-level Talents (Peacock Program Category C)

🏆 Achievements

🔬 Research on semiconductor gas sensors, optoelectronic devices, solar cells, biosensors, and more
📑 15 SCI papers in top journals (Advanced Materials, Advanced Energy Materials, etc.) as first/corresponding author
📜 3 National Invention Patents granted
📝 Guest Editor & Reviewer for several scientific journals

🎖 Awards & Honors

🥇 First Prize – China University Students Mechanical Engineering Innovation and Creativity Competition “Akashi Cup” (Guangdong Province)
🥇 First Prize – National Final of “Akashi Cup” (Instructor)
🥈 Second Prize – International Sensor Innovation and Entrepreneurship Competition, South China Region (Instructor)
🏅 2 Outstanding Poster Awards – 1st Smart Gas Sensor Innovation & Cross-border Application Development Forum (Instructor)
🥉 Third Prize – Physics Experiment Competition for College Students, Shenzhen University of Technology (Instructor)
🏆 Crystal Award – Shenzhen University of Technology Science and Technology Innovation Award (Instructor)
📜 Outstanding Undergraduate Thesis Design – Shenzhen University of Technology (Instructor)
🎤 Outstanding Oral Presentation Award – 15th National Conference on Gas and Humidity Sensing Technology and Academic Exchange

Publication Top Notes:

Advanced wearable strain sensors: Ionic double network hydrogels with exceptional stretchability, adhesion, anti-freezing properties, and sensitivity

 

Dual-Gas Sensor Based on the Pt NPs/AlGaN/GaN High Electron Mobility Transistor for H and NH Gases Detection<sub /> <sub />

 

Halide perovskites and high-pressure technologies: a fruitful encounter

One-step synthesis of various burr-like TiO2 nanostructures: Nanotubes, nanorods, nanotetrapods, nano-urchins

 

A Bidirectionally Focus-Tunable Optofluidic Microlens With Miniature Thermoelectric Coolers

 

 

Prof. Dezhi Zheng | Sensitive Mechanism Awards | Best Researcher Award

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Prof. Dezhi Zheng | Sensitive Mechanism Awards | Best Researcher Award

Prof. Dezhi Zheng, Beijing Institute of technology, China

Professor Dezhi Zheng is a prominent researcher and doctoral supervisor at the Advanced Research Institute of Multidisciplinary Sciences at Beijing Institute of Technology. With a robust academic background, he earned both his Ph.D. and B.S. degrees in Precision Instruments and Machinery and Mechanical Engineering and Automation from Beihang University. Since 2020, he has been a professor at Beijing Institute of Technology, and prior to this role, he served as a visiting scholar in the Mechanical Engineering Department at the University of Victoria and held various academic positions at Beihang University. Professor Zheng’s research interests focus on collaborative awareness technology, airborne information detection, extreme signal measurement technology, and sensor sensitivity mechanisms. His groundbreaking work in accurate perception technology has led to significant advancements in resonant sensors, ultra-low frequency vibration sensors, and wearable sensing devices for human bioelectrical signals, notably improving measurement accuracy and practical applications in fields like aviation and smart technology. With over 30 national key scientific research projects and more than 70 academic publications to his name, along with over 30 authorized invention patents, Professor Zheng is recognized as a leader in the field of sensors and sensing technology.

Professional Profile:

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Summary of Suitability for the Best Researcher Award: Dezhi Zheng

Dezhi Zheng is an accomplished researcher and educator with a distinguished record in the fields of sensing technology and precision instrumentation, making him an excellent candidate for the Best Researcher Award. His extensive academic background and impactful contributions in both research and technology application underscore his qualifications.

Education 🎓

  • Ph.D. in Precision Instruments and Machinery
    Beihang University, 2000-2006
  • B.S. in Mechanical Engineering and Automation
    Beihang University, 1996-2000

Work Experience 🏢

  • Professor
    Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology (2020 – Present)
  • Visiting Scholar
    Mechanical Engineering, University of Victoria (2014 – 2015)
  • Researcher
    Research Institute for Frontier Science, Beihang University (2006 – 2020)
  • Associate Professor
    School of Instrumentation and Optoelectronic Engineering, Beihang University (2006 – 2020)
  • Lecturer
    School of Instrumentation and Optoelectronic Engineering, Beihang University (2006 – 2006)

Achievements 🏆

  • Conducted research on resonant sensors, improving measurement accuracy of aircraft flight height by nearly an order of magnitude. ✈️
  • Developed ultra-low frequency vibration sensors and calibration technology, achieving accurate calibration of 0.01Hz sensors. 📏
  • Researched wearable sensing devices and intelligent sensing technology for weak human bioelectrical signals, leading to practical applications in wearable brain-computer interfaces. 🧠
  • Participated in over 30 major national key scientific research projects. 🔬
  • Published more than 70 academic papers. 📚
  • Authorized more than 30 invention patents. 💡

Awards and Honors 🥇

  • Recognized for contributions to the development of resonant sensors and smart helmets, addressing key challenges in sensor technology. 🛠️
  • Achievements in the field of collaborative awareness technology and extreme signal measurement technology. 🌟

Publication Top Notes:

Hybrid Knowledge-Data Driven Channel Semantic Acquisition and Beamforming for Cell-Free Massive MIMO

Integrated Sensing and Communication With mmWave Massive MIMO: A Compressed Sampling Perspective

Joint Activity Detection and Channel Estimation for Massive IoT Access Based on Millimeter-Wave/Terahertz Multi-Panel Massive MIMO

Next-Generation Massive URLLC with Massive MIMO: A Unified Semi-Blind Detection Framework for Sourced and Unsourced Random Access

Robust phase unwrapping via non-local regularization

Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

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Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.

Publication Top Notes:

Title: Dense Pedestrian Detection Based on GR-YOLO

 

 

 

Assoc. Prof. Dr. Wan Zakiah Wan Ismail | Electronic sensors Awards | Best Researcher Award

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Assoc. Prof. Dr. Wan Zakiah Wan Ismail | Electronic sensors Awards | Best Researcher Award

Assoc. Prof. Dr. Wan Zakiah Wan Ismail , Universiti Sains islam Malaysia, Malaysia

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail is an Associate Professor at the Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM). She holds a PhD in Lasers and Quantum Electronics from Macquarie University, Australia, a Master’s in Electronics (Telecommunication) from the University of Melbourne, and a Bachelor’s in Electronics from Universiti Multimedia. Her research expertise spans across various fields including random lasers, biosensing, and quantum-based technologies. Dr. Wan Zakiah has led and participated in numerous research projects funded by both national and international grants, focusing on advanced technologies and their applications in medical and environmental fields. She is actively involved in supervising postgraduate students and contributing to significant research initiatives at USIM.

Professional Profile:

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Evaluation of Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail for Best Researcher Award

Summary of Suitability:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail is a highly qualified academic with a Ph.D. in Lasers and Quantum Electronics from Macquarie University, Australia, and a Master’s degree in Electronics (Telecommunication) from the University of Melbourne. Her expertise spans electronics, quantum electronics, and advanced research in biosensing, medical applications, and sustainable technologies.

🎓Education:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail earned her PhD in Lasers and Quantum Electronics from Macquarie University, Australia, in 2016. Prior to that, she completed her Master’s in Electronics (Telecommunication) at the University of Melbourne in 2007. Her academic journey began with a Bachelor’s degree in Electronics from Universiti Multimedia, awarded in 2005.

🏢Work Experience:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail has served as an Associate Professor at the Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM) since 2017. In her role, she teaches undergraduate and postgraduate courses, supervises both PhD and Master’s students, and leads research initiatives. Additionally, she is actively involved as a researcher and co-researcher on various projects funded by national and international grants, with a focus on advanced technologies such as random lasers, biosensing, quantum-based technologies, and environmental applications.

🏆Awards:

Prof. Madya Ts. Dr. Wan Zakiah Binti Wan Ismail has been recognized for her outstanding research contributions by various institutions and conferences. Her significant work in the fields of lasers, quantum electronics, and advanced biosensing technologies has garnered accolades, reflecting her impact and expertise in these areas.

Publication Top Notes:

  • Investigation of Photometric Distribution of LED and HSPV for Road Lighting
  • Developing a Portable Spectrometer to Detect Chemical Contaminants in Irrigation Water
  • Design and Analysis of Water Quality Monitoring and Filtration System for Different Types of Water in Malaysia
  • Integration of Sensing Framework with a Decision Support System for Monitoring Water Quality in Agriculture
  • Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review

 

 

 

Prof Dr. Chia-Yen Lee | Environmental Sensors Award | Best Researcher Award

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Prof Dr. Chia-Yen Lee | Environmental Sensors Award | Best Researcher Award 

Prof Dr. Chia-Yen Lee, National Pingtung University of Science and Technology, Taiwan

Prof. Chia-Yen Lee is a distinguished academic in the field of Mechanical Engineering with a focus on micro-sensors, micro-electro-mechanical systems (MEMS), HVAC systems, and indoor environment monitoring. He completed his B.S. and M.S. degrees in Mechanical Engineering at National Taiwan University, Taipei, Taiwan, in 1991 and 1993, respectively. He earned his Ph.D. in Engineering Science from National Cheng Kung University, Tainan, Taiwan, in 2004. Prof. Lee has held significant academic positions at National Pingtung University of Science and Technology (NPUST), where he served as a Professor from August 2010 to July 2021 and as a Distinguished Professor from August 2018. Prior to his tenure at NPUST, he was an Associate Professor at Da-Yeh University and a Visiting Scholar at the California Institute of Technology in 2007. His professional career also includes roles in industry as a Section Head at DiCon Fiberoptics, Inc., and senior engineering positions at TECO Electric and Machinery Co., Ltd.

Professional Profile:

 

Summary of Suitability for the Best Researcher Award:

  • Professor Lee’s research expertise includes micro-sensors, MEMS technology, and indoor environment monitoring. His recent work involves the development of infrared sensors based on ZnO thin films, MEMS-based pyroelectric infrared sensors, and Hall sensor arrays for magnetic field mapping.

Education:

🎓 B.S. in Mechanical Engineering
Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan (1987-1991)

🎓 M.S. in Mechanical Engineering
Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan (1991-1993)

🎓 Ph.D. in Engineering Science
Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan (2001-2004)

Professional History:

👨‍🏫 Distinguished Professor
National Pingtung University of Science and Technology, Taiwan (Aug 2018 – Jul 2021)

👨‍🏫 Professor
Department of Materials Engineering, National Pingtung University of Science and Technology, Taiwan (Aug 2010 – Jul 2018)

👩‍🏫 Associate Professor
Department of Materials Engineering, National Pingtung University of Science and Technology, Taiwan (Aug 2008 – Jul 2010)

👩‍🏫 Associate Professor
Department of Mechanical and Automation Engineering, Da-Yeh University, Taiwan (Aug 2007 – Jul 2008)

🌍 Visiting Scholar
Department of Electrical Engineering, California Institute of Technology, CA, U.S.A. (Jul 2007 – Aug 2007)

👨‍🏫 Assistant Professor
Department of Mechanical and Automation Engineering, Da-Yeh University, Taiwan (Aug 2004 – Jul 2007)

Publication top Notes:

Positioning System of Infrared Sensors Based on ZnO Thin Film

Positioning System of Infrared Sensors Based on ZnO Thin Film

Effect of Substrate-Thickness on Voltage Responsivity of MEMS-Based ZnO Pyroelectric Infrared Sensors

Design and Application of MEMS-Based Hall Sensor Array for Magnetic Field Mapping

Mr. Yi Sun | Sensor Fabrication | Excellence in Innovation

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Mr. Yi Sun | Sensor Fabrication | Excellence in Innovation 

Mr. Yi Sun, Dalian Jiaotong University, China

Yi Sun is a Master of Science student in Mechanical Engineering, currently participating in a joint training program between Tsinghua University and Dalian Jiaotong University. His research focuses on the conversion relationships between thermal, mechanical, and electrical energy at the nanoscale. Yi has conducted dynamic response observations of thin-film thermocouples and developed mathematical models for heat transfer, leading to publications as the first author in notable journals. His work includes significant projects at the Provincial Key Laboratory of Modern Sensors and Actuators and the State Key Laboratory of Tribology, where he explores advanced topics such as thin-film thermocouple performance and tribological behavior in specialized atmospheres. Yi’s contributions are marked by his strong analytical skills and innovative approach to sensor technology and thermal dynamics.

Professional Profile:

SCOPUS

ORCID

 

Education:

  • Tsinghua University & Dalian Jiaotong University (M.E., 2022 – Present) 🎓
  • Dalian Jiaotong University (B.E., 2018 – 2022) 🎓
Research Interests:
Yi is passionate about nanoscale energy conversions and has conducted advanced research on thin-film thermocouples, contributing valuable insights into dynamic calibration and heat transfer. 🔍⚙️

Work Experience:

  1. Provincial Key Laboratory of Modern Sensors and Actuators, Dalian Jiaotong University
    Position: Researcher
    Duration: June 2023 – January 2024
    Responsibilities:

    • Studied the mechanism of large creep adhesion in wheel-rail braking at 400 km/h.
    • Contributed to the National Natural Science Foundation of China (NNSFC) projects on the effect of multi-component doped solid solution alloy on thin-film thermocouple performance and the design of transparent conductive oxide molecular-like structural units.
  2. State Key Laboratory of Tribology, Tsinghua University
    Position: Researcher
    Duration: January 2024 – Present
    Responsibilities:

    • Conducting research on the tribological behavior of foil bearings in non-oxidizing atmospheres.
  3. Dalian Jiaotong University
    Position: Master’s Student Researcher
    Duration: 2018 – 2022
    Responsibilities:

    • Developed mathematical models for heat transfer and observed dynamic responses of thin-film thermocouples on the nanoscale and nanosecond scale.
    • Published a research paper as the first author on thermoelectric electromotive force oscillation of thin-film thermocouples.

Publication top Notes:

Nanosecond-level second-order characteristics in dynamic calibration of thin film thermocouples by short-pulse laser

Preliminary Investigation of Thermoelectric Electromotive Force Oscillation of NiCr/NiSi Thin Film Thermocouple in Dynamic Calibration

Best Sensor for Smart Cities

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Introduction Best Sensor for Smart Cities

Welcome to the Best Sensor for Smart Cities Award, recognizing innovative sensor technologies that contribute to the development of smarter and more sustainable cities.

Award Eligibility:

This award is open to individuals, teams, and organizations worldwide who have developed sensor technologies specifically designed for use in smart city applications. There are no age limits or specific qualifications required to apply. Publications related to the development or application of the sensor technology are encouraged but not mandatory.

Requirements:

Applicants must submit a detailed description of their sensor technology, including its design, functionality, and potential impact on smart city development. Additionally, applicants should provide any relevant supporting materials, such as videos, images, or technical documentation.

Evaluation Criteria

Submissions will be evaluated based on the level of innovation, practicality, and potential impact of the sensor technology on smart city development.

Submission Guidelines:

Submissions should be sent via email to awards@bestsensorforsmartcities.com by the deadline specified on the website. Please include “Best Sensor for Smart Cities Award Submission” in the subject line.

Recognition:

Winners of the Best Sensor for Smart Cities Award will receive a cash prize, a certificate of recognition, and media coverage highlighting their achievement.

Community Impact:

The Best Sensor for Smart Cities Award aims to promote the use of sensor technologies in smart city development, ultimately improving quality of life and sustainability in urban areas.

Biography:

The award committee is comprised of experts in the fields of sensor technology and smart city development who are dedicated to recognizing and promoting excellence in this area.

Abstract and Supporting Files:

In addition to the application form, applicants should submit an abstract of their sensor technology and any supporting files that may help illustrate its functionality and potential impact.

 

 

Best Sensor for Robotics

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Introduction Best Sensor for Robotics

Welcome to the Best Sensor for Robotics Award, an initiative aimed at recognizing outstanding innovations in sensor technology that enhance robotic capabilities.

Award Eligibility:

This award is open to individuals and teams worldwide who have developed sensors or sensor-related technologies specifically designed for use in robotics. There are no age limits or specific qualifications required to apply. Publications related to the development or application of the sensor technology are encouraged but not mandatory.

Requirements:

Applicants must submit a detailed description of their sensor technology, including its design, functionality, and potential impact on robotics. Additionally, applicants should provide any relevant supporting materials, such as videos, images, or technical documentation.

Evaluation Criteria:

Submissions will be evaluated based on the level of innovation, practicality, and potential impact of the sensor technology on the field of robotics.

Submission Guidelines :

Submissions should be sent via email to awards@bestsensorforrobotics.com by the deadline specified on the website. Please include “Best Sensor for Robotics Award Submission” in the subject line.

Recognition:

Winners of the Best Sensor for Robotics Award will receive a cash prize, a certificate of recognition, and media coverage highlighting their achievement.

Community Impact:

The Best Sensor for Robotics Award aims to foster innovation and collaboration within the robotics community, ultimately advancing the field and benefiting society as a whole.

Biography:

The award committee is comprised of experts in the field of robotics and sensor technology who are dedicated to recognizing and promoting excellence in this area.

Abstract and Supporting Files:

In addition to the application form, applicants should submit an abstract of their sensor technology and any supporting files that may help illustrate its functionality and potential impact.

 

 

Best Sensor for Food Safety

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Introduction Best Sensor for Food Safety

In a world where food safety is paramount, recognizing the best sensor for ensuring food safety is crucial. This award aims to honor innovative solutions that enhance food safety monitoring, contributing to a healthier and more secure food supply chain.

Award Eligibility:
  • Age Limits: No age restrictions.
  • Qualification: Open to individuals, teams, and organizations worldwide.
  • Publications: No specific publication requirements.
  • Requirements: Submissions must demonstrate a novel sensor technology or application in the field of food safety.
Evaluation Criteria:

Submissions will be evaluated based on innovation, impact on food safety, scalability, and potential for widespread adoption.

Submission Guidelines:
  • Submissions should include a detailed description of the sensor technology or application.
  • Supporting documentation, such as research papers or case studies, may be included.
  • Abstracts and supporting files must be submitted online by the specified deadline.
Recognition:

Winners will receive a certificate of recognition and be featured in industry publications and events.

Community Impact:

The winning sensor technology will contribute to enhancing food safety standards, benefiting consumers and the food industry alike.

Biography:

The award aims to recognize individuals, teams, and organizations driving innovation in food safety through sensor technology.

Abstract and Supporting Files:

Submissions should contain a concise abstract summarizing the sensor technology’s impact on food safety. Supporting files may include research papers, case studies, or technical specifications.