This conference paper delves into the transformative synergy of Environmental computing, Agricultural Engineering, and Artificial Intelligence (AI) to forge sustainable ICT applications in agriculture. By amalgamating...
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This paper discusses the theory of embedded database SQLite and its application development on ARM platform, analyzes the characteristics of embedded database in detail, and expounds the architecture of embedded datab...
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Industries can profit from automation by increasing rate of production and decreasing errors, improving safety and stabilising the manufacturing process. High levels of profitability, dependability and safety come wit...
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The intelligent fire detection and response system integrates three key components: Fire Type Identification, Fire Tracking, and Dynamic Nozzle control. The Fire Identification component uses a multi-sensor setup (tem...
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automation of complex technological and laboratory systems requires the creation of specialized mixed-critical computing systems. They must control the technological process at several levels (control subsystem) and m...
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作者:
Gao, ChenXian Univ
Sch Mech & Mat Engn Xian 710065 Shaanxi Peoples R China
Edge computing gateway automation system is integrated in edge computing gateway. One of the main functions of edge computing system is to connect industrial instruments and communication equipment in the process of i...
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Edge computing gateway automation system is integrated in edge computing gateway. One of the main functions of edge computing system is to connect industrial instruments and communication equipment in the process of industrial production. It provides real-time data monitoring and analysis, and initiates responses to predetermined logical events. The operation process includes separating and designing different processes in a certain order. The production and processing process is susceptible to problems such as long production and processing cycles, multiple types of monitoring data, large amounts of processing data, and data vulnerability to external interference, which leads to inaccurate and unsynchronized data. Based on this, this article investigated the analysis of data processing systems based on cloud computing, focusing on analyzing the system architecture and processing, and elaborating the design of data collectors. Then, this article analyzed the efficiency of AI (artificial intelligence) automatic control system and data processing unit. This article discussed the application of AI in collecting and processing data, the composition of the data management module of AI automatic control system, and the data processing in the data module of AI automatic control system. This paper also described the construction method and process of the automatic control system of edge computing gateway, and discussed from the following aspects: data preprocessing module, data classification processing module, data accumulation analysis module, automatic control algorithm logic module, and instruction execution control module. Experiments and investigations showed that the accuracy of data analysis by using the new AI automatic control system and data processing system was 0.11 higher than that of traditional automatic control systems and data processing systems. The data processing effectiveness of the new AI automatic control system and data processing system was 0.10 hi
In modern industrial systems, accurate fault identification is crucial for the early isolation of broken parts and for further system restoration. Furthermore, data-driven machine learning applications gain popularity...
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ISBN:
(纸本)9798350364309;9798350364293
In modern industrial systems, accurate fault identification is crucial for the early isolation of broken parts and for further system restoration. Furthermore, data-driven machine learning applications gain popularity because of the increased availability of sensor data and their effectiveness. Graph neural networks, which are neural processes that operate on graph-structured data, are ideal for representing non-Euclidean data captured from multiple sensors. In the current paper, we benefit from the representation ability of graph structures through the presentation of a novel neural graph model that utilizes residual connections and leverages the spatial structure of the graph and the local information of graph nodes. Adaptive structural information and temporal knowledge insight can be integrated by the suggested graph neural framework. The latter is accomplished by feeding the temporal encoding of the graph nodes into a spectral graph neural network for training. Simulation results on the widely used fault identification benchmark of the Tennessee Eastman industrial chemical process verify that the proposed method outperforms competitive machine learning methods and state-of-the-art graph neural models, strengthens graph neural network training, and can be used to accurately identify faults in real industrial scenarios.
The image low-pass filter is an effective solution for denoising and improving image quality. The stochastic computing is a novel method for number representation and calculation in stochastic domain. Aiming at the pr...
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In a decentralized process Management System, several process engines cooperate to execute a single process instance by using direct Machine-to-Machine communication and local coordination of the process flow. In this...
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ISBN:
(纸本)9789819608041;9789819608058
In a decentralized process Management System, several process engines cooperate to execute a single process instance by using direct Machine-to-Machine communication and local coordination of the process flow. In this paper, we analyze the software architecture elements of a decentralized process Management System. We explain the involved components, connectors, data, and the relationships between them. We also describe the state transitions of decentralized processes during execution.
This paper delves into almost sure input-to-state stability (ISS) and almost sure integral input-to-state stability (iISS) of randomly switched time-varying systems with time-delays. We provide definitions for almost ...
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ISBN:
(纸本)9798350350319;9798350350302
This paper delves into almost sure input-to-state stability (ISS) and almost sure integral input-to-state stability (iISS) of randomly switched time-varying systems with time-delays. We provide definitions for almost sure ISS and almost sure iISS, underlining their necessity with an example that shows the disparity between pth moment ISS and almost sure ISS. Following this, we derive criteria for almost sure ISS and almost sure iISS based on indefinite multiple Lyapunov functions and Razumikhin technique. Notably, these criteria give time-varying stability estimators which do not require subsystems to maintain ISS or iISS throughout the entire time interval. Finally, the effectiveness and advantages of our results are demonstrated through a numerical example.
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