Article
Engineering, Industrial
Geng Zhang, Chun-Hsien Chen, Bufan Liu, Xinyu Li, Zuoxu Wang
Summary: With the rapid development of information technologies, shared manufacturing is facing a growing need for monitoring and maintenance. Existing research primarily focuses on a resource-centric strategy for management, overlooking the experience data from users/customers. To fill this gap, a hybrid sensing-based approach is proposed for monitoring and maintenance of shared manufacturing resources.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Automation & Control Systems
Li Qin, Chudong Tong, Ting Lan, Yang Chen
Summary: The proposed just-in-time feature analysis (JITFA) algorithm allows for timely uncovering of deviations between online sampled data and normal operating datasets, enhancing the effectiveness of multivariate statistical process monitoring (MSPM). Compared to other methods, the JITFA-based MSPM approach demonstrates superior monitoring performance and ease of applicability due to its lack of predetermined model parameters.
CONTROL ENGINEERING PRACTICE
(2021)
Article
Computer Science, Information Systems
Wenjin Yu, Yuehua Liu, Tharam Dillon, Wenny Rahayu, Fahed Mostafa
Summary: This article proposes a practical framework that combines IoT techniques, a data lake, data analysis, and cloud computing for manufacturing equipment health-state monitoring and diagnostics in smart manufacturing. It addresses all aspects required for such a system and allows seamless interchange of data and functionality. In addition, it provides solutions for the specific characteristics and quality issues of IoT sensor data.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Chemistry, Analytical
Jie Wang, Xuanrui Xiong, Gaosheng Chen, Ruiqi Ouyang, Yunli Gao, Osama Alfarraj
Summary: The rapid growth of the Internet of Things (IoT) and big data has raised security concerns. To enhance IoT security, intrusion detection systems using traffic features have emerged, but they face difficulties due to varied traffic feature formats. A new model called LVW-MECO is introduced, which uses the LVW algorithm and multiple evaluation criteria to accurately identify relevant features, enhancing intrusion detection performance in the IoT environment.
Article
Automation & Control Systems
Keke Huang, Shijun Tao, Dehao Wu, Chunhua Yang, Weihua Gui, Shiyan Hu
Summary: Process monitoring is crucial for the reliable operation of industrial systems in the context of industrial Internet of Things (IIoT). However, due to the harsh environment and unreliable sensors and actuators, it is challenging to collect enough tagged and highly reliable data, leading to degraded performance and lack of trust in the monitoring results. To address this issue, a self-weighted dictionary learning process monitoring method is proposed, which incorporates label propagation classification, reweighting of classification loss and label-consistency constraints, and an iterative optimization algorithm for learning the classifier and dictionary.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Marco Gerardi, Francesca Fallucchi, Fabio Orecchini
Summary: This paper proposes a new system for electricity production metering that utilizes blockchain and IoT technologies, addressing the issues of traditional energy meters and improving efficiency, transparency, and traceability in energy metering, while reducing costs and enhancing user privacy.
Article
Computer Science, Artificial Intelligence
Xianyu Zhang, Xinguo Ming
Summary: With the advancement of various technologies, the industrial internet has evolved through different stages. However, there is a lack of a comprehensive research framework for studying the top-level planning of the Industrial Internet Platform (IIP). Additionally, there are few studies on the specific path and steps for implementing IIP in specific industries and enterprises.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Soumyajit Ghosh, Dulal Manna, Arunava Chatterjee, Debashis Chatterjee
Summary: The article introduces an innovative residential electrical load monitoring procedure based on multi-objective optimization and Artificial Bee Colony algorithm, which does not heavily rely on training data and works with real-time data. It also includes remote monitoring using an IoT based approach, demonstrating significant improvement.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Xianyu Zhang, Xinguo Ming
Summary: With the development of industrial Internet environment and intelligent technology, enterprises are focusing more on system platform, information sharing, network collaboration, personalized customization and service recommendation in designing, implementing and operating Industrial Internet Platforms (IIP). However, there is a lack of a comprehensive framework for studying the high-level planning of IIP implementation and few studies on the detailed path and steps of IIP implementation in specific industries. The research aims to study the general model, reference architecture, service evaluation index system, implementation path and application verification for IIP to provide guidance for government and industry in planning, designing, implementing and promoting IIP.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Jungyoon Kim, Songhee Cheon, Jihye Lim
Summary: Mental health disorders, specifically dementia, are common among elderly populations, and early diagnosis and control are crucial. This study proposes an unobtrusive dementia-prediction system that monitors physical activities using passive infrared motion sensors. The system effectively predicts dementia risk using various classification models, making it valuable for long-term monitoring and early symptom detection systems.
Review
Computer Science, Information Systems
Abderahman Rejeb, Karim Rejeb, Steve Simske, Horst Treiblmaier, Suhaiza Zailani
Summary: This study examines the application of the IoT in smart cities in the current academic literature using bibliometric techniques. The research shows significant growth of IoT research in recent years, with applications including smart buildings, transportation, healthcare, and more. This review provides scholars and practitioners with an overview of existing research and identifies research gaps at the intersection of the IoT and the smart city.
INTERNET OF THINGS
(2022)
Article
Computer Science, Information Systems
Shiyi Jiang, Farshad Firouzi, Krishnendu Chakrabarty, Eric B. Elbogen
Summary: The conventional mental healthcare regime lacks continuity and personalization. This research proposes a wearable Internet of Things-based stress monitoring solution that combines edge models and cloud computing to assess stress in real time, improving performance and energy efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Automation & Control Systems
Shanzhi Li, Chudong Tong, Yang Chen, Ting Lan
Summary: The novel online discriminative dynamic feature analysis (ODDFA) algorithm is used for dynamic process monitoring, seeking for projecting directions to discriminate deviations between online sampled data and normal operating dataset. Compared to traditional multivariate analytical algorithms, ODDFA algorithm is activated online with stacking time-serial samples into a matrix form for better discriminative features.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Green & Sustainable Science & Technology
Rafael Gomes Alves, Rodrigo Filev Maia, Fabio Lima
Summary: This paper presents a digital twin model of a smart irrigation system, which utilizes an internet of things platform and a discrete event simulation model to enable automatic data flow and interaction. The system allows farmers to evaluate the behavior and test different irrigation strategies, leading to improvements in agricultural operations and water usage reduction.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Electrical & Electronic
Halil Cimen, Emilio Jose Palacios Garcia, Morten Kolbaek, Nurettin Cetinkaya, Juan C. Vasquez, Josep M. Guerrero
Summary: Peter Norvig believes that having more data leads to better decision-making and foresight. With the advancement of IoT technology, data collection has become easier, with tools like social media and smartphones serving as data generators.
IEEE INDUSTRIAL ELECTRONICS MAGAZINE
(2021)
Article
Engineering, Chemical
Jangwon Lee, Jesus Flores-Cerrillo, Jin Wang, Q. Peter He
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2020)
Review
Engineering, Chemical
Q. Peter He, Jin Wang
Article
Biotechnology & Applied Microbiology
Kiumars Badr, William Whelan, Q. Peter He, Jin Wang
Summary: Recent research has shown that synthetic methanotroph-photoautotroph cocultures have great potential for converting biogas into valuable products. An experimental-computational protocol has been proposed to quantitatively characterize these cocultures and determine key parameters accurately and efficiently.
BIOTECHNOLOGY AND BIOENGINEERING
(2021)
Editorial Material
Engineering, Chemical
Q. Peter He, Jin Wang
Article
Engineering, Environmental
Kiumars Badr, Q. Peter He, Jin Wang
Summary: By developing an experimental-computational protocol, a kinetic model for M-P cocultures was established to accurately predict growth dynamics under various conditions. The study confirmed the presence of additional emergent metabolic exchanges within the coculture and quantified their impact on the growth of both species in the model coculture, supporting further research in metabolic engineering.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Biotechnology & Applied Microbiology
Jangwon Lee, Ankur Kumar, Jesus Flores-Cerrillo, Jin Wang, Q. Peter He
Summary: Pressure swing adsorption (PSA) is widely used for gas product separation, but monitoring the process can be challenging due to its complexity and lack of steady state. To address these challenges, a feature-based statistical process monitoring (SPM) framework called feature space monitoring (FSM) is proposed, which demonstrates superior performance in early fault detection compared to traditional SPM methods.
FRONTIERS IN CHEMICAL ENGINEERING
(2022)
Proceedings Paper
Automation & Control Systems
Kiumars Badr, Q. Peter He, Jin Wang
Summary: The study investigates the potential emergent metabolic interactions within a Methanotroph-Photoautotroph (M-P) coculture through experiments and semi-structured kinetic modeling. The researchers successfully confirmed the existence of additional interspecies metabolic interactions and developed a genome-scale model for the M-P coculture. The findings provide insights into the metabolic dynamics and growth enhancement of the coculture.
Proceedings Paper
Automation & Control Systems
Jangwon Lee, Zhuoxiong Sun, Tai B. Tan, Jorge Mendez, Jesus Flores-Cerrillo, Jin Wang, Q. Peter He
Summary: Rotating machines, such as pumps and compressors, are critical components in refinery and chemical plants. Estimating the remaining useful life (RUL) of bearings is crucial for reducing production losses and avoiding machine damage. Data-driven approaches have been widely used due to the complexity and stochastic nature of bearing failure mechanisms.
Article
Multidisciplinary Sciences
Kiumars Badr, Q. Peter He, Jin Wang
Summary: This paper presents the matlab implementation details of a novel semi-structured kinetic model for methanotroph-photoautotroph cocultures. The model is validated using a wide range of experimental conditions and accurately predicts the growth of the coculture and changes in gas composition over time. It explicitly models the exchange of in situ produced O-2 and CO2 within the coculture and considers the self-shading effect on the growth of photoautotroph.
Proceedings Paper
Automation & Control Systems
Jangwon Lee, Jesus Flores-Cerrillo, Jin Wang, Q. Peter He
2020 AMERICAN CONTROL CONFERENCE (ACC)
(2020)
