Article
Agriculture, Multidisciplinary
Sibo Xia, Xinyuan Nan, Xin Cai, Xumeng Lu
Summary: A fusion strategy for temperature monitoring system in intelligent greenhouses is proposed, utilizing a hierarchical wireless sensor network to achieve real-time data fusion, improving the efficiency and accuracy of the system.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Engineering, Electrical & Electronic
Xiaoli Zhang, Chunfeng Fan, Bianlian Zhang, Yali Guo, Shaofei Dong, Guangle Yang
Summary: This paper studies the collaboration and decision-making strategy for a multi-agent optical fiber intelligent health monitoring system based on the Delphi method. The proposed system consists of an optical fiber sensing agent, intelligent evaluation agent, and system collaborative decision-making agent. Through multiple rounds of collaboration and decision-making, the evaluation accuracy and reliability of the monitored mechanical structural damage are significantly improved.
JOURNAL OF SENSORS
(2022)
Article
Engineering, Electrical & Electronic
Wei Chen, Xuzhou Wang
Summary: This study explores the principles, design, and feasibility of using wireless sensor network technology in coal mine safety monitoring, proposes solutions to the problem of low intelligence level in coal mine safety monitoring systems, and validates the reliability and stability of the proposed design through experiments.
IEEE SENSORS JOURNAL
(2021)
Article
Construction & Building Technology
Jinyoung Kim, Seongah Kim, Seongjin Bae, Manjun Kim, Yoonboum Cho, Kyu-In Lee
Summary: This study describes the development of a real-time and easy monitoring system for indoor environment and energy consumption, and its application in a living lab. The system uses Raspberry Pi and embedded sensors to collect indoor air quality-related data, which can be stored safely and easily accessed by residents.
BUILDING AND ENVIRONMENT
(2022)
Article
Computer Science, Information Systems
Andrea Augello, Salvatore Gaglio, Giuseppe Lo Re, Daniele Peri
Summary: This paper proposes a method for modeling and verifying distributed applications on wireless sensor networks, allowing for direct testing and reprogramming on deployed network devices. Experimental results demonstrate the feasibility and effectiveness of the proposed method.
Article
Nanoscience & Nanotechnology
Zhongyi Li, Kun Wang, Chaojian Hou, Chunyang Li, Fanqing Zhang, Wu Ren, Lixin Dong, Jing Zhao
Summary: This article introduces a novel artificial intelligence (AI) microrobot that can respond to changes in the external environment without an onboard energy supply and transmit signals wirelessly in real time. It can enhance the local radiofrequency (RF) magnetic field and achieve a large penetration sensing depth and high spatial resolution. The research is of great significance for early disease discovery and accurate diagnosis, and has the potential for large-scale production of functional microrobots.
MICROSYSTEMS & NANOENGINEERING
(2023)
Article
Chemistry, Physical
Bing Li, Casey M. Jones, Thomas E. Adams, Vikas Tomar
Summary: This study presents a dynamic testing platform to analyze the performance degradation and safety issues of lithium-ion batteries during operation, by cycling batteries under various dynamic conditions. The sensor network can identify critical periods with high heat generation and stress accumulation rates, as well as the effects of boundary conditions on heat generation. Using this sensor network can help identify critical batteries with safety hazards.
JOURNAL OF POWER SOURCES
(2021)
Article
Computer Science, Artificial Intelligence
Pratik Goswami, Amrit Mukherjee, Bishal Sarkar, Lixia Yang
Summary: Wireless sensor networks play a huge role in connecting devices for smart applications in the Internet of things (IoT) paradigm. One of the key smart applications is the smart healthcare system, which includes remote health monitoring using sensors to provide different health statistics. This article proposes a novel method that utilizes artificial neural network-based technique self-organizing map (SOM) for clustering and distributed artificial intelligence (DAI) for power distribution in the nodes. The hybrid approach of SOM and multi-agent-based DAI outperforms existing methods in terms of performance.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Wael Doghri, Ahlem Saddoud, Lamia Chaari Fourati
Summary: The birth of Cyber-Physical Systems (CPS) marked the emergence of a new generation of systems that combine computational and physical capabilities. CPS has significant impact on Structural Health Monitoring System applications and is a promising domain for research. SHM based on wireless sensor networks (WSNs) offers cost-saving benefits for infrastructure maintenance, attracting attention for its diverse applications and importance in public safety.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Robotics
Jose A. Barreiros, Artemis Xu, Sofya Pugach, Narahari Iyengar, Graeme Troxell, Alexander Cornwell, Samantha Hong, Bart Selman, Robert F. Shepherd
Summary: Flesh has the ability to encode haptic information using mechanoreceptors on the human body. An engineered flesh using optical materials and machine learning can encode haptic stimuli into light and infer spatiotemporal information from it. The system demonstrates low error in estimating temperature, contact location, and forces.
Article
Computer Science, Artificial Intelligence
Gauri Kalnoor, S. Gowrishankar
Summary: The proposed work aims to design an intelligent intrusion detection system using machine learning models to identify and protect IoT networks from attacks. Experimental results show that the Markov model performs well in the I-IDS IoT network, achieving a 100% detection rate and low false alarm rate.
Article
Engineering, Electrical & Electronic
Jaeseung Baek, Taha J. Alhindi, Young-Seon Jeong, Myong K. Jeong, Seongho Seo, Jongseok Kang, Yoseob Heo
Summary: This paper presents a novel fire detection system that integrates fire sensing and detection phases to effectively monitor and detect indoor building fires at an early stage using diverse sensor signals. The system gathers sensor data from various sensor types sensitive to measuring components emitted from fires, and utilizes a similarity matching-based detection algorithm to capture shape patterns in sensor signals and reduce false alarms. Real-life sensor data and experimental results demonstrate the effectiveness of the proposed fire detection system.
IEEE SENSORS JOURNAL
(2021)
Review
Construction & Building Technology
Yongding Tian, Chao Chen, Kwesi Sagoe-Crentsil, Jian Zhang, Wenhui Duan
Summary: This review provides an overview of the current robotic systems used in structural health monitoring (SHM) of bridges, and explores the development trends of multimodal robots and soft robotics. It highlights the potential of integrating various Nondestructive Evaluation (NDE) tools with robotic systems for performing multiple inspection tasks, and emphasizes the advantages of lightweight and adaptable soft robots in special/space-confined environments.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Electrical & Electronic
Ying Shen
Summary: This paper presents a human behavior pattern analysis system based on mobile communication data, which uses base station trajectories to mine users' potential behavioral patterns, aiding analysts in discovering the behavioral characteristics of city residents.
JOURNAL OF SENSORS
(2021)
Article
Construction & Building Technology
Chuan Zhang, Qixiang Yan, Yifeng Zhang, Xiaolong Liao, Hanqing Zhong
Summary: This paper presents an intelligent methodology for monitoring and assessing the interfacial debonding damage process of concrete-rock composites through the piezoelectric-based ultrasonic testing method coordinated with convolutional neural network (CNN). The ultrasonic sensing method is successfully extended to monitoring the debonding of concrete-rock composites with different interfacial roughness for the first time. A CNN model is constructed and well trained to identify different debonding phases from image-based datasets of CWT spectra. Comparative analysis with three machine learning-based models demonstrates the superiority of the CNN model.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
