Research on the Construction Mode of Mechanical and Electrical Integration of Intelligent Control System based on Multi-agent Technique

In this paper, we conduct research on the construction mode of mechanical and electrical integration of intelligent control system based on the multi-agent technique. The development of the modem science and technology has greatly promoted the cross of different subjects and infiltration, caused the technological transformation and revolution in the field of engineering. In the field of mechanical engineering, because of rapid development of microelectronics technology and computer technology to the mechanical industry and its mechanical and electrical integration, which is formed by the penetration of the technology of mechanical industry structure, product, organization, function and structure, mode of the production and management system, great changes have taken place in industrial production by the mechanical electrification ＂ushered in the development of＂ mechatronics ＂as the characteristics of the stage. Our research combines the multi-agent technique to propose the new paradigm for mechanical and electrical integration which is innovative.

Controller Design of Intelligent Lighting Network

Studied are the controller design and basic principles of intelligent lighting network. TI’s MSP430F123 is used as a main controller. By using the ZigBee modules(Xbee/Xbee-PRO) and the GSM module(SIM300C) for wireless communications, the lighting control is enabled to access wireless network. This system uses a mobile phone to achieve light on-off directly, which can accomplish wireless control of intelligent lighting in families.

Intelligent 3-Way Priority-Driven Traffic Light Control System for Emergency Vehicles

The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in instances where emergency situations occur at traffic light intersections that are consistently congested with a high volume of vehicles. This implementation of a traffic light controller system is designed with the intention of addressing this problem. The purpose of the system was to facilitate the operation of a 3-way traffic control light and provide priority to emergency vehicles using a Radio Frequency Identification (RFID) sensor and Reduced Instruction Set Computing (RISC) Architecture Based Microcontroller. This research work involved designing a system to mitigate the occurrence of accidents commonly observed at traffic light intersections, where vehicles often need to maneuver in order to make way for emergency vehicles following a designated route. The research effectively achieved the analysis, simulation and implementation of wireless communication devices for traffic light control. The implemented prototype utilizes RFID transmission, operates in conjunction with the sequential mode of traffic lights to alter the traffic light sequence accordingly and reverts the traffic lights back to their normal sequence after the emergency vehicle has passed the traffic lights.

Semantics Interaction Control for Constructing Intelligent Ecology of Internet of Things and Critical Component Research

Intelligent equipment is a kind of device that is characterized by intelligent sensor interconnections, big data processing, new types of displays, human-machine interaction and so on for the new generation of information technology. For this purpose, in this paper, first, we present a type of novel intelligent deep hybrid neural network algorithm based on a deep bidirectional recurrent neural network integrated with a deep backward propagation neural network. It has realized acoustic analysis, speech recognition and natural language understanding for jointly constituting human-machine voice interactions. Second, we design a voice control motherboard using an embedded chip from the ARM series as the core, and the onboard components include ZigBee, RFID, WIFI, GPRS, a RS232 serial port, USB interfaces and so on. Third, we take advantage of algorithms, software and hardware to make machines “understand” human speech and “think” and “comprehend” human intentions to structure critical components for intelligent vehicles, intelligent offices, intelligent service robots, intelligent industries and so on, which furthers the structure of the intelligent ecology of the Internet of Things. At last, the experimental results denote that the study of the semantics interaction controls based on an embedding has a very good effect, fast speed and high accuracy, consequently realizing the intelligent ecology construction of the Internet of Things.

Future trends in intelligent lighting control systems:Integrated technologies,multi-system linkage and AI integration

Lighting energy consumption accounts for a considerable proportion of the total electricity consumption of a building;therefore,the lighting system of a building has great potential for energy saving.With the development of technology,intelligent lighting control systems are widely used in buildings and have good energy-saving effects.Previous reviews of intelligent lighting control systems have analyzed the research progress,advantages,and limitations of a single technology in depth,but have not yet summarized the combination of various technologies and the scope of application.Therefore,this study starts from the components of intelligent lighting control system and focuses on the data acquisition module and control module.Researches on these two modules are analyzed from the aspects of multi-technology combination,combination with artificial intelligence and multi-system considerations,and the application scope and limitations of the related technologies are summarized to provide references for future engineering practice.Finally,based on the development overview of current research,this study explores research directions that can be further expanded in intelligent lighting control systems to handle future development trends.

Application Strategy of PLC Technology in Energy-Saving Control of Tunnel Lighting

In this study,we investigated on the application of planar lightwave circuit(PLC)technology in energy-saving control of tunnel lighting.The application status of PLC in the field of energy saving followed by the necessity of energy saving in tunnel lighting was analyzed.Finally,the application of PLC in tunnel lighting energy-saving control around the three dimensions of system overall architecture design,control scheme,and program control process was investigated.The results showed that the system meets the requirements of control effect,robustness,and visual effect after trial operation,and is suitable for practical applications.

Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control

This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.

Researches On The Optimal Design Of Intersection Signal Lights Fuzzy Control

Fuzzy control is an important branch of intelligent control, and this paper describes the application of fuzzy pattern study in intelligent control, begins with a brief overview introduction for development of intelligent control, and then describes the main components of the fuzzy model and its characteristics and fuzzy pattern control system.Fuzzy pattern applications in the intersection signal intelligent control showed fuzzy mode control can effectively reduce the single intersection average vehicle delay time, making the intersection more unobstructed to pass.

Analysis of Current Research and Future Development Trends of Applying Solar Energy in Street Lighting

In the context of promoting green energy transition and addressing climate change globally,solar energy,as a clean and renewable energy source,has gradually become a hot topic for research.Solar streetlight systems realize energy self-sufficiency and environment-friendly lighting by integrating photovoltaic power generation technology and efficient LED lighting technology.By comprehensively analyzing the current status of the application of solar streetlights at home and abroad,this paper discusses its technical advantages,market penetration,and challenges in its development.In terms of technical characteristics,this paper focuses on analyzing the key technologies such as energy conversion efficiency and intelligent control systems of solar streetlights.

Neural Network-Powered License Plate Recognition System Design

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

Technology improvements and management innovations in construction of Xiluodu hydropower station on Jinsha River

Developer and owner:China Three Gorges Corporation(CTG)Engineering management:China Three Gorges Projects Development Corporation(CTGPC)Designer:Chengdu Engineering Corporation Co.,Ltd.,Power

Key technical innovations in the construction of Baihetan Hydropower Station Project

1 Project positioning Baihetan Hydropower Station is classified as the second of the four hydropower cascades in the lower reaches of the Jinsha River:Wudongde,Baihetan,Xiluodu and Xiangjiaba.As an important backbone project for China to implement the strategy of West-to-East Power Transmission and optimize the energy structure,it constitutes an important part of the Yangtze River flood control system.Located at the junction of Ningnan County,Sichuan Province and Qiaojia County,Yunnan Province,the hydropower station is the largest hydropower project under construction in the world,with a unit capacity of million-kilowatts ranking the highest in the world and a total installed capacity of 16 million kW,second only to the Three Gorges Project,ranking the second in the world.

堆石混凝土坝概述及下一代混凝土坝施工技术展望

Over the past few decades,one of the most significant advances in dam construction has been the inven-tion of the rock-filled concrete(RFC)dam,which is constructed by pouring high-performance self-compacting concrete(HSCC)to fill the voids in preplaced large rocks.The innovative use of large rocks in dam construction provides engineers with a material that requires less cement consumption and hydration heat while enhancing construction efficiency and environmental friendliness.However,two fundamental scientific issues related to RFC need to be addressed:namely,the pouring compactness and the effect of large rocks on the mechanical and physical properties of RFC.This article provides a timely review of fundamental research and innovations in the design,construction,and quality control of RFCdams.Prospects for next-generation concrete dams are discussed from the perspectives of envi-ronmental friendliness,intrinsic safety,and labor savings.

Intelligent and Predictive Vehicular Networks

Seeking shortest travel times through smart algorithms may not only optimize the travel times but also reduce carbon emissions, such as CO2, CO and Hydro-Carbons. It can also result in reduced driver frustrations and can increase passenger expectations of consistent travel times, which in turn points to benefits in overall planning of day schedules. Fuel consumption savings are another benefit from the same. However, attempts to elect the shortest path as an assumption of quick travel times, often work counter to the very objective intended and come with the risk of creating a “Braess Paradox” which is about congestion resulting when several drivers attempt to elect the same shortest route. The situation that arises has been referred to as the price of anarchy! We propose algorithms that find multiple shortest paths between an origin and a destination. It must be appreciated that these will not yield the exact number of Kilometers travelled, but favourable weights in terms of travel times so that a reasonable allowable time difference between the multiple shortest paths is attained when the same Origin and Destinations are considered and favourable responsive routes are determined as variables of traffic levels and time of day. These routes are selected on the paradigm of route balancing, re-routing algorithms and traffic light intelligence all coming together to result in optimized consistent travel times whose benefits are evenly spread to all motorist, unlike the Entropy balanced k shortest paths (EBkSP) method which favours some motorists on the basis of urgency. This paper proposes a Fully Balanced Multiple-Candidate shortest path (FBMkP) by which we model in SUMO to overcome the computational overhead of assigning priority differently to each travelling vehicle using intelligence at intersections and other points on the vehicular network. The FBMkP opens up traffic by fully balancing the whole network so as to benefit every motorist. Whereas the EBkSP reserves some routes for cars on high priority, our algorithm distributes the benefits of smart routing to all vehicles on the network and serves the road side units such as induction loops and detectors from having to remember the urgency of each vehicle. Instead, detectors and induction loops simply have to poll the destination of the vehicle and not any urgency factor. The minimal data being processed significantly reduce computational times and the benefits all vehicles. The multiple-candidate shortest paths selected on the basis of current traffic status on each possible route increase the efficiency. Routes are fewer than vehicles so possessing weights of routes is smarter than processing individual vehicle weights. This is a multi-objective function project where improving one factor such as travel times improves many more cost, social and environmental factors.

软件工程专业“智能控制系统”课程建设

随着智能控制技术的快速发展,智能控制系统在各个领域都得到了广泛应用。面向广阔的人才需求,各大高校纷纷开设了“智能控制系统”课程。针对软件工程专业特点,分析了传统“智能控制系统”课程教学存在的问题。结合自身课程建设经验,从多个方面介绍了“智能控制系统”课程建设方案。实践证明,课程建设方案适用于软件工程专业,有利于培养学生智能控制系统软硬件开发能力。

基于ZigBee技术的无线灯光智能控制系统设计

全球经济快速发展,电力能源紧缺,传统照明模式不能满足现有的照明和节能需求。针对此问题,文章设计了一种基于ZigBee技术的新型智能灯光控制系统,实现了教室照明系统分散与集中管理、本地与远程监控管理相结合的功能,具有一定的理论价值和实践意义。

基于物联网的交通信号灯控制系统

随着城市化进程的不断加速,交通拥堵问题成为制约城市可持续发展的一大挑战。在智能交通系统中,交通信号灯作为关键组成部分,对道路交通的管理和优化发挥着至关重要的作用。为提高交通效率、减少交通拥堵,文章探讨了基于物联网的智能交通信号灯控制系统。首先,介绍了交通信号灯的系统组成。其次,针对交通信号灯控制的优化需求,提出一种基于物联网的自适应控制算法。最后,构建了交通信号灯仿真界面,并设计了交互控制按钮。实验结果表明,所提出的自适应控制算法能够有效提升道路通行效率,降低交通拥堵程度,为智能交通系统的进一步优化与发展提供了重要参考。

基于大数据的地铁全线建设投资智能控制研究

研究目的:地铁建设项目投资消耗因素具有复杂性、时序性、空间性和开放性,导致现有的定额投资控制模式已远远达不到投资随机性和非线性演变的要求,亟需改革地铁投资控制管理模式。由此本文综合运用BIM、Python技术与模糊数学、BP神经网络、已获价值理论和PDCA循环法,构建地铁全线建设投资智能预测和控制方法。研究结论:(1)建立了地铁全线建设投资基础数据库,同时构建地铁工程投资问题原因对策库;(2)运用SPSS因子分析、粗糙集理论、模糊数学结合BP神经网络得到全线施工总目标;(3)综合PDCA循环、已获价值理论对重点管控工程进行投资动态优化控制,显著提高了项目整体的管理效率和水平;(4)建立了地铁全线建设投资计算机辅助智能控制软件并应用在成都地铁建设实例中;(5)本研究成果可为地铁全线建设投资控制提供可行性方案。

人工智能囊胚形态评估数据集构建与质控专家共识

囊胚形态人工智能(AI)评估是AI医疗器械发展的新兴方向,也是AI在辅助生殖领域的重要应用。AI在新领域应用的起步阶段,数据集的构建与质控对产品质量有重要影响。目前,囊胚形态学AI评估在数据采集、标注、质控等方面尚未形成统一的规范。在参考AI医疗器械、辅助生殖医疗器械现有国家行业标准的基础上,本文以囊胚形态AI评估数据集为主题,对数据集构建与质控要求进行了探讨,对数据集质量特性进行了解析,旨在指导数据集制造责任方加强数据集全生命周期管理,更好地为产品研发、测试、临床试验等环节提供质量保障,助力产业发展。