Nowadays multiple wireless communication systems operate in industrial environments side by side.In such an environment performance of one wireless network can be degraded by the collocated hostile wireless network ha...Nowadays multiple wireless communication systems operate in industrial environments side by side.In such an environment performance of one wireless network can be degraded by the collocated hostile wireless network having higher transmission power or higher carrier sensing threshold.Unlike the previous research works which considered IEEE 802.15.4 for the Industrial Wireless communication systems(iWCS)this paper examines the coexistence of IEEE 802.11 based iWCS used for delay-stringent communication in process automation and gWLAN(general-purpose WLAN)used for non-real time communication.In this paper,we present a Markov chain-based performance model that described the transmission failure of iWCS due to geographical collision with gWLAN.The presented analytic model accurately determines throughput,packet transaction delay,and packet loss probability of iWCS when it is collocated with gWLAN.The results of the Markov model match more than 90%with our simulation results.Furthermore,we proposed an adaptive transmission power control technique for iWCS to overcome the potential interferences caused by the gWLAN transmissions.The simulation results show that the proposed technique significantly improves iWCS performance in terms of throughput,packet transaction,and cycle period reduction.Moreover,it enables the industrial network for the use of delay critical applications in the presence of gWLAN without affecting its performance.展开更多
Industrialized buildings,characterized by off-site manufacturing and on-site installation,offer notable improvements in efficiency,cost-effectiveness,and material use.This transition from traditional construction meth...Industrialized buildings,characterized by off-site manufacturing and on-site installation,offer notable improvements in efficiency,cost-effectiveness,and material use.This transition from traditional construction methods not only accelerates building processes but also enhances working efficiencies globally.Despite its widespread adoption,the performance of industrialized building manufacturing(IBM)can still be optimized,particularly in enhancing time efficiency and reducing costs.This paper explores the integration of Artificial Intelligence(AI)and robotics at IBM to improve efficiency,cost-effectiveness,and material use in off-site assembly.Through a narrative literature review,this study systematically categorizes AI-based Robots(AIRs)applications into four critical stages—Cognition,Communication,Control,and Collab-oration and Coordination,and then investigates their appli-cation in the factory assembly process for industrialized buildings,which is structured into distinct stages:compo-nent preparation,sub-assembly,main assembly,finishing tasks,and quality control.Each stage,from positioning components to the integration of larger modules and subsequent quality inspection,often involves robots or human-robot collaboration to enhance precision and effi-ciency.By examining research from 2014 to 2024,the review highlights the significant improvements AI-based robots have introduced to the construction sector,identifies existing challenges,and outlines future research directions.This comprehensive analysis aims to establish more effi-cient,precise,and tailored construction processes,paving the way for advanced IBM.展开更多
Tracking mobile nodes in dynamic and noisy conditions of industrial environments has provided a paradigm for many issues inherent in the area of distributed control systems in general and wireless sensor networks in p...Tracking mobile nodes in dynamic and noisy conditions of industrial environments has provided a paradigm for many issues inherent in the area of distributed control systems in general and wireless sensor networks in particular. Due to the dynamic nature of the industrial environments, a practical tracking system is required that is adaptable to the changes in the environment. More specifically, given the limited resources of wireless nodes and the challenges created by harsh industrial environments there is a need for a technique that can modify the configuration of the system on the fly as new wireless nodes are added to the network and obsolete ones are removed. To address these issues, two cluster-based tracking systems, one static and the other dynamic, are proposed to organize the overall network field into a set of tracking zones, each composed of a sink node and a set of corresponding anchor nodes. To manage the wireless nodes activities and inter and intra cluster communications, an agent-based technique is employed. To compare the architectures, we report on a set of experiments performed in JADE （Java Agent Development Environment）. In these experiments, we compare two agent-based approaches （dynamic and static） for managing clusters of wireless sensor nodes in a distributed tracking system. The experimental results corroborate the efficiency of the static clusters versus the robustness and effectiveness of the dynamic clusters.展开更多
基金This research was supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1D1A1B07049758).
文摘Nowadays multiple wireless communication systems operate in industrial environments side by side.In such an environment performance of one wireless network can be degraded by the collocated hostile wireless network having higher transmission power or higher carrier sensing threshold.Unlike the previous research works which considered IEEE 802.15.4 for the Industrial Wireless communication systems(iWCS)this paper examines the coexistence of IEEE 802.11 based iWCS used for delay-stringent communication in process automation and gWLAN(general-purpose WLAN)used for non-real time communication.In this paper,we present a Markov chain-based performance model that described the transmission failure of iWCS due to geographical collision with gWLAN.The presented analytic model accurately determines throughput,packet transaction delay,and packet loss probability of iWCS when it is collocated with gWLAN.The results of the Markov model match more than 90%with our simulation results.Furthermore,we proposed an adaptive transmission power control technique for iWCS to overcome the potential interferences caused by the gWLAN transmissions.The simulation results show that the proposed technique significantly improves iWCS performance in terms of throughput,packet transaction,and cycle period reduction.Moreover,it enables the industrial network for the use of delay critical applications in the presence of gWLAN without affecting its performance.
文摘Industrialized buildings,characterized by off-site manufacturing and on-site installation,offer notable improvements in efficiency,cost-effectiveness,and material use.This transition from traditional construction methods not only accelerates building processes but also enhances working efficiencies globally.Despite its widespread adoption,the performance of industrialized building manufacturing(IBM)can still be optimized,particularly in enhancing time efficiency and reducing costs.This paper explores the integration of Artificial Intelligence(AI)and robotics at IBM to improve efficiency,cost-effectiveness,and material use in off-site assembly.Through a narrative literature review,this study systematically categorizes AI-based Robots(AIRs)applications into four critical stages—Cognition,Communication,Control,and Collab-oration and Coordination,and then investigates their appli-cation in the factory assembly process for industrialized buildings,which is structured into distinct stages:compo-nent preparation,sub-assembly,main assembly,finishing tasks,and quality control.Each stage,from positioning components to the integration of larger modules and subsequent quality inspection,often involves robots or human-robot collaboration to enhance precision and effi-ciency.By examining research from 2014 to 2024,the review highlights the significant improvements AI-based robots have introduced to the construction sector,identifies existing challenges,and outlines future research directions.This comprehensive analysis aims to establish more effi-cient,precise,and tailored construction processes,paving the way for advanced IBM.
文摘Tracking mobile nodes in dynamic and noisy conditions of industrial environments has provided a paradigm for many issues inherent in the area of distributed control systems in general and wireless sensor networks in particular. Due to the dynamic nature of the industrial environments, a practical tracking system is required that is adaptable to the changes in the environment. More specifically, given the limited resources of wireless nodes and the challenges created by harsh industrial environments there is a need for a technique that can modify the configuration of the system on the fly as new wireless nodes are added to the network and obsolete ones are removed. To address these issues, two cluster-based tracking systems, one static and the other dynamic, are proposed to organize the overall network field into a set of tracking zones, each composed of a sink node and a set of corresponding anchor nodes. To manage the wireless nodes activities and inter and intra cluster communications, an agent-based technique is employed. To compare the architectures, we report on a set of experiments performed in JADE （Java Agent Development Environment）. In these experiments, we compare two agent-based approaches （dynamic and static） for managing clusters of wireless sensor nodes in a distributed tracking system. The experimental results corroborate the efficiency of the static clusters versus the robustness and effectiveness of the dynamic clusters.
