Minghu Zhang | Environmental Engineering | Best Researcher Award

Lanzhou University of Technology,China🎓

Minghu Zhang is an Associate Professor at Lanzhou University of Technology and currently the Director of the Internet of Things Engineering Department in the School of Computer and Communication. His research advances environmental monitoring using drone-based IoT systems, with a focus on hydrological and environmental monitoring in extreme settings. Minghu has pioneered innovative techniques such as Large-scale Particle Image Velocimetry (LSPIV) and drone-mounted river flow measurement systems, contributing extensively to IoT, artificial intelligence, and computer vision.

Professional Profile

Scopus

Education 🎓:

Minghu received his Ph.D. from the University of Chinese Academy of Sciences in 2021. Since then, he has brought a strong academic foundation to his work in hydrological technology, integrating it with practical IoT applications and AI-driven environmental monitoring techniques.

Work Experience 💼:

As an Associate Professor and Director of the IoT Engineering Department, Minghu Zhang has led significant projects, serving as the Principal Investigator for seven projects funded by prestigious organizations like the National Natural Science Foundation of China and the Ministry of Science and Technology. His professional journey is highlighted by his work on UAV-IoT relay systems, facilitating accurate environmental data collection in challenging terrains.

Skills 🔍

Minghu’s skill set encompasses advanced research and practical applications in IoT systems, computer vision, drone-based monitoring, and environmental data analytics. His technical proficiencies include data processing, hydrological modeling, and digital twin technology, with practical knowledge in remote sensing, high-speed communication, and AI.

Awards and Honors 🏆

Minghu’s work on Large-scale Particle Image Velocimetry (LSPIV) technology has received widespread recognition. His innovative methods for measuring river surface velocity without ground control points earned him accolades, and he has been a prominent candidate for awards such as the Best Researcher Award, showcasing his commitment to groundbreaking technological solutions in environmental monitoring.

Teaching Experience 👩‍🏫:

Minghu is actively involved in academic mentorship, guiding students in the School of Computer and Communication at Lanzhou University of Technology. His teaching primarily focuses on IoT applications, AI, and environmental monitoring, nurturing future researchers in these cutting-edge fields.

Research Focus 🔬:

Minghu’s research emphasizes environmental monitoring and hydrological studies, with significant contributions to permafrost, glacier monitoring, and river flow assessment. His work in integrating IoT and remote sensing technologies for environmental applications bridges the gap between theoretical research and real-world environmental challenges, driving practical solutions for enhanced ecosystem monitoring.

Conclusion

In conclusion, Minghu Zhang’s pioneering work in IoT and AI for environmental and hydrological monitoring marks him as an exceptional candidate for the Best Researcher Award. His development of LSPIV and drone-based IoT relay systems exemplifies innovative solutions with real-world impact. With expanded international and industry partnerships, his research could further influence environmental science and practical applications. Overall, Minghu’s achievements align well with the criteria for the Best Researcher Award, reflecting his capacity to advance both the science and application of cutting-edge environmental technologies.

📚 Publilcation

Title: Security Assessment and Improvement of Smart Grid NIKE Protocol
Topic: Evaluates and proposes improvements for the NIKE protocol in smart grid security
Year: 2024
Journal: International Journal of Information Security
Title: Measuring Velocity and Discharge of High Turbidity Rivers Using an Improved Near-Field Remote-Sensing Measurement System
Topic: Develops a near-field remote-sensing system to measure river flow velocity in high turbidity conditions
Year: 2024
Journal: Water (Switzerland)
Title: Medium and Long-Term Traffic Flow Prediction Based on ACNN-Trans Model
Topic: Uses an ACNN-Trans model for predicting traffic flow in medium and long-term scenarios
Year: 2023
Journal: Journal of China Universities of Posts and Telecommunications
Title: Fetching Ecosystem Monitoring Data in Extreme Areas via a Drone-Enabled Internet of Remote Things
Topic: Employs a drone-enabled IoT system to collect ecosystem data from remote locations
Year: 2022
Journal: IEEE Internet of Things Journal
Title: Satellite-Enabled Internet of Remote Things Network Transmits Field Data from the Most Remote Areas of the Tibetan Plateau
Topic: Utilizes satellite-enabled IoT networks for transmitting data from remote areas in the Tibetan Plateau
Year: 2022
Journal: Sensors
Title: River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin
Topic: Designs a data control system for big data management in river basin environments
Year: 2021
Journal: Sensors
Title: Data-Driven Anomaly Detection Approach for Time-Series Streaming Data
Topic: Develops a data-driven method for detecting anomalies in time-series streaming data
Year: 2020
Journal: Sensors (Switzerland)
Title: Drone-Enabled Internet-of-Things Relay for Environmental Monitoring in Remote Areas Without Public Networks
Topic: Proposes a drone-based IoT relay system for monitoring environmental conditions in remote areas
Year: 2020
Journal: IEEE Internet of Things Journal
Title: An Adaptive Outlier Detection and Processing Approach Towards Time Series Sensor Data
Topic: Develops an adaptive method for detecting and processing outliers in time-series sensor data
Year: 2019
Journal: IEEE Access