Z
Zhibo Pang
Researcher at Royal Institute of Technology
Publications - 192
Citations - 5784
Zhibo Pang is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Wireless sensor network & Wireless. The author has an hindex of 32, co-authored 169 publications receiving 4052 citations.
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Journal ArticleDOI
A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor, and Intelligent Medicine Box
Geng Yang,Li Xie,Matti Mäntysalo,Xiaolin Zhou,Zhibo Pang,Li Da Xu,Sharon Kao-Walter,Qiang Chen,Li-Rong Zheng +8 more
TL;DR: The proposed iHome Health-IoT platform seamlessly fuses IoT devices with in-home healthcare services for an improved user experience and service efficiency.
Journal ArticleDOI
Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges
Sumit Majumder,Emad Aghayi,Moein Noferesti,Hamidreza Memarzadeh-Tehran,Tapas Mondal,Zhibo Pang,M. Jamal Deen +6 more
TL;DR: A comprehensive review on the state-of-the-art research and development in smart home based remote healthcare technologies is presented.
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A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment
TL;DR: A new method is proposed to design a reconfigurable smart sensor interface for industrial WSN in IoT environment, in which complex programmable logic device (CPLD) is adopted as the core controller and the standard of IEEE1451.2 intelligent sensor interface specification is adopted.
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Massive Internet of Things for Industrial Applications: Addressing Wireless IIoT Connectivity Challenges and Ecosystem Fragmentation
TL;DR: The article addresses the main challenges standing in the way of realizing the full potential of the IIoT, namely attaining secure connectivity and managing a vastly fragmented ecosystem of connectivity solutions and platforms.
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Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion
TL;DR: A value-centric business-technology joint design framework is proposed as well as examples about acceleration data processing, self-learning shelf life prediction and real-time supply chain re-planning and three-tier information fusion architecture are proposed.