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2020 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)最新文献

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Modernized Compartment With Safety Measures in Railways 铁路现代化车厢与安全措施
The presented methodology is to monitor endlessly cracks in tracks, obstacles on rail tracks and any other train running on the same track oppositely by using sensors. When identified, the device will send an alert to the driver to prevent the accidents. The flame sensor detects it and sends a signal to the microcontroller and driver when the train compartment catches fire, then triggers the servo motor to disconnect the compartments. With the help of this paper we try to overcome few of the issues in railways as well as modernize the compartment.
提出的方法是利用传感器监测轨道上的裂缝、轨道上的障碍物以及在同一轨道上相反运行的任何其他列车。识别后,该设备将向驾驶员发送警报,以防止事故发生。当车厢着火时,火焰传感器检测到并向微控制器和驾驶员发送信号,然后触发伺服电机断开车厢。通过本文的研究,我们试图克服铁路中存在的一些问题,实现车厢的现代化。
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引用次数: 0
Performance Analysis of EPAR, DSR and MTPR in MANET’S MANET系统中EPAR、DSR和MTPR的性能分析
The fast development in the field of mobile data processing is driving another option route in which cell phones frame a self-creating, self-overseeing, and self-sorting out remote frameworks called Mobile Ad hoc Networks (MANETs). One of the main issues in MANET routing protocols is the development of energy efficient protocols because of limited battery life and bandwidth of the nodes. The versatile center points in MANETs have differing transmission power and power heterogeneity. This paper separates the execution appraisal of three Energy Efficient Routing Protocols are Efficient Power Aware Routing Convention (EPAR), Minimum total Transmission Power Routing (MTPR) and DSR (Dynamic Source Routing). The Energy Efficient Routing Protocols mainly considers the center point restricts by its leftover battery control and the typical imperativeness spent for sending information dependable. EPAR utilizes min-max definition technique for the choice of maximum packet delivery ratio at the smallest Residual Battery Power. With different network scenarios, EPAR is comparatively good than other methods.
移动数据处理领域的快速发展推动了另一种选择路线,即手机构建一个自创建、自监督、自排序的远程框架,即移动自组织网络(manet)。由于有限的电池寿命和节点带宽,MANET路由协议的主要问题之一是开发节能协议。多用途的manet中心点具有不同的传输功率和功率异构性。本文分别对三种节能路由协议EPAR (Efficient Power Aware Routing Convention)、MTPR (Minimum total Transmission Power Routing)和DSR (Dynamic Source Routing)进行了执行评价。高效节能路由协议主要考虑了中心点的剩余电池控制限制和典型的强制发送信息的可靠性。EPAR利用最小-最大定义技术在最小剩余电池电量下选择最大数据包传输比。在不同的网络场景下,EPAR的性能相对较好。
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引用次数: 0
A secured and automated Vehicle Surveillance System 一个安全的自动车辆监控系统
Security of vehicle has become a necessary component at all places in the society. In addition due to faster development in technology, resource utilization and crisis management also plays a major role. A secured and automated vehicle surveillance system is a project that incorporate the concepts of image processing and Internet of Things (IoT) to provide security for the vehicle by integrating it with face recognition system and messaging system as an added feature. Vehicle enhancement is equipped with automation of vehicle headlight based on the surrounding brightness and controlling the over speed of vehicle based on the speedometer reading. Realization of this system will be a step forward in refinement of the society towards better socio-economic by utilization of resource on automating headlight and ethical prosperity by preventing thefts and accidents.
车辆安全已成为社会各个场所必不可少的组成部分。此外,由于技术的快速发展,资源利用和危机管理也起着重要作用。安全自动化车辆监控系统是将图像处理和物联网(IoT)的概念与人脸识别系统和信息系统相结合,为车辆提供安全保障的项目。车辆增强系统根据周围环境的亮度自动调节车辆前照灯,根据车速表的读数自动控制车辆超速。这一系统的实现将是社会的一个进步,通过自动化车头灯的资源利用和防止盗窃和事故的道德繁荣,使社会经济得到改善。
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引用次数: 1
Design and Development of Precoding Algorithm 预编码算法的设计与开发
Proposed work carries out the study of the Pre-coder and basic Transmitter – Receiver model. Transmitter and Receiver Simulink model is developed by estimating and equalizing channel. With this channel state information (CSI) Pre-coder is developed. Additive White Gaussian Noise (AWGN) channel is implemented in Simulink. Transmitter – Receiver model is built for simulation and performance evaluation. Suitable channel estimation and equalization algorithms are used for simulation. QPSK modulation is used, similarly demodulation techniques are used at the receiver. For different Signal to Noise Ratio (SNR) values Bit Error Rate (BER) is plotted. Least Square (LS) estimation and Zero Forcing (ZF) equalization algorithm for MIMO is implemented in Simulink.
提出的工作进行了预编码器和基本的发射器-接收器模型的研究。通过信道估计和均衡,建立了收发Simulink模型。在此基础上开发了信道状态信息(CSI)预编码器。加性高斯白噪声(AWGN)信道在Simulink中实现。建立了发射机-接收机模型,进行了仿真和性能评估。采用合适的信道估计和均衡算法进行仿真。使用QPSK调制,在接收器上使用类似的解调技术。对于不同的信噪比(SNR)值,绘制了误码率(BER)。在Simulink中实现了MIMO的最小二乘估计和零强迫均衡算法。
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引用次数: 1
Early Detection of Flood Monitoring and Alerting System to Save Human Lives 洪水监测预警系统的早期发现,拯救人类生命
Climatic changes have an adverse effect on certain factors of nature like temperature, humidity, rainfall etc. Also, because of convective activity, there is more rainfall in certain areas during monsoon seasons which might flood the areas near rivers or dam. Another reason for flood is cyclone. While cyclones appear to be natural calamities, they are in essence required by nature to maintain the balance of temperature. It is when the oceans become warm that cyclones form to cool them down. Our activities which are distorting the balance of nature, we can expect more inclement weather, stronger storms to form. Climate change is real and must seriously paid attention to. In the end, it is all about balance and our relationship with nature. This paper deals with proactive measures taken to not be affected by flood and hence give precaution to common man. Updates about the current weather and different parameters that are related to water is continuously monitored. This paper also incorporates communication of the information collected effectively by using ESP32 microcontroller, GSM and IoT (Blynk).
气候变化对某些自然因素如温度、湿度、降雨等有不利影响。此外,由于对流活动,在季风季节,某些地区的降雨较多,可能会淹没河流或水坝附近的地区。洪水的另一个原因是气旋。虽然飓风看起来是自然灾害,但本质上它们是大自然维持温度平衡所必需的。当海洋变暖时,就会形成气旋使其降温。我们的活动正在扭曲大自然的平衡,我们可以预期更恶劣的天气,更强的风暴将形成。气候变化是真实存在的,必须认真对待。最后,一切都是关于平衡和我们与自然的关系。本文论述了为避免洪水的影响而采取的积极措施,从而为普通人提供预防措施。不断监测当前天气和与水有关的不同参数的更新。本文还利用ESP32单片机、GSM和物联网(Blynk)技术对采集到的信息进行了有效的通信。
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引用次数: 5
IoT based Smart Water Quality Monitoring and Flow Control System 基于物联网的智能水质监测和流量控制系统
Quality of water may be an advanced exploration and production fundamental concept. The water quality is based on so many factors. Water infection is surely one of the essential crucial fears for the green globalization. With a view to deliver safe and secure water, real-time quality has to be monitored. The current system comprises a sensor network which is utilized to gauge both physical and synthetic boundaries of the water that are temperature, PH, turbidity, water glide sensor can be measured. These measured values from the sensors are processed via the Arduino UNO controller. Finally, the sensor values may be regarded using Wi-Fi module. This paper presents a cost efficient system for real time quality monitoring using Internet of Things (IoT).
水质可能是一个先进的勘探和生产的基本概念。水质是由很多因素决定的。水感染无疑是绿色全球化最重要的担忧之一。为了提供安全可靠的水,必须实时监测水质。目前的系统包括一个传感器网络,用于测量水的物理和合成边界,温度,PH值,浊度,水滑动传感器可以测量。这些来自传感器的测量值通过Arduino UNO控制器进行处理。最后,可以使用Wi-Fi模块来考虑传感器值。本文提出了一种基于物联网的高性价比的质量实时监控系统。
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引用次数: 7
Design and Implementation of Automated Fire Fighting and Rescuing Robot 自动灭火救援机器人的设计与实现
Fire environments are dangerous and constantly changing. Although fire fighting is an extremely hard task, it is still carried by human operations to rescue and protect the victims. In order to help people; machine tools the robotic architecture has become extremely important. Fire protection robot is therefore intended to assist individuals using autonomous system in any damaging burned situation. The use of various sensors like ultrasonic, fire, smoke and motion sensor increases the robot capabilities. The gripper is mounted onto the robot to clear the obstacles on the way of the victims. The use of IP camera improvised the robot functionality by providing bi-directional communication between the controlling area and the burnt area. The robot is further improvised using BLYNK application which is linked to the microcontroller ESP32 via Wi-Fi SoC to provode alert message to the person on duty and to the residents.
火灾环境是危险且不断变化的。尽管灭火是一项极其艰巨的任务,但它仍然是由人类行动来拯救和保护受害者。为了帮助别人;机床和机器人的结构已经变得极其重要。因此,消防机器人旨在协助个人在任何破坏性的烧伤情况下使用自主系统。超声波、火灾、烟雾和运动传感器等各种传感器的使用增加了机器人的能力。抓手被安装在机器人上,用来清除受害者路上的障碍物。通过在控制区域和烧伤区域之间提供双向通信,IP摄像机的使用改进了机器人的功能。该机器人使用BLYNK应用程序进行了进一步的改进,该应用程序通过Wi-Fi SoC连接到微控制器ESP32,以向值班人员和居民发出警报信息。
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引用次数: 0
Predicting Employees under Stress for Pre-emptive Remediation using Machine learning Algorithm 利用机器学习算法预测压力下员工的先发制人补救
With the ongoing COVID-19 pandemic, businesses and organizations have acclimated to unconventional and different working ways and patterns, like working from home, working with limited employees at office premises. With the new normal here to stay for the recent future, employees have also adapted to different working environments and customs, which has also resulted in psychological stress and lethargy for many, as they adapt to the new normal and adjust their personal and professional lives. In this work, data visualization techniques and machine learning algorithms have been used to predict employees stress levels. Based on data, we can develop a model that will assist to predict if an employee is likely to be under stress or not. Here, the XGB classifier is used for the prediction process and the results are presented showing that the method facilitates getting a more reliable model performance. After performing interpretation utilizing XGB classifier it is determined that working hours, workload, age, and, role ambiguity have a significant and negative influence on employee performance. The additional factors do not hold much significance when associated to the above discussed. Therefore, It is concluded that concluded that increasing working hours, role ambiguity, the workload would diminish employee representation in all perspectives.
随着COVID-19大流行的持续,企业和组织已经适应了非常规和不同的工作方式和模式,例如在家工作,在办公场所与有限的员工一起工作。随着新常态的持续,员工也适应了不同的工作环境和习俗,这也导致了许多人在适应新常态和调整个人和职业生活时的心理压力和嗜睡。在这项工作中,数据可视化技术和机器学习算法被用来预测员工的压力水平。基于数据,我们可以开发一个模型来帮助预测员工是否可能处于压力之下。本文将XGB分类器用于预测过程,结果表明该方法有助于获得更可靠的模型性能。利用XGB分类器进行口译后,确定工作时间、工作量、年龄和角色模糊对员工绩效有显著的负向影响。当与上述讨论联系在一起时,其他因素就没有多大意义了。因此,我们得出结论,增加工作时间,角色模糊,工作量会减少员工在各个方面的代表性。
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引用次数: 4
A FLC based Automated CC-CV Charging through SEPIC for EV using Fuel Cell 基于FLC的燃料电池电动汽车SEPIC自动充电
Energy extraction from renewable sources and its utilization in Electric Vehicles (EVs) have paved the way for greener transportation options. Battery charging is the present-day challenge in EVs. Constant Current (CC) and Constant Voltage (CV) charging methods have many advantages over other EV battery charging techniques. A fuel cell, being one of the ways of producing DC energy, can be directly used to charge batteries in EVs. With the fuel cell being the DC source, the on-board fast charging can be easily achieved by various power converters, but the Single-Ended Primary Inductor Converter (SEPIC) would serve most efficiently for the aforementioned scenario. In CC method, battery may overcharged if battery reaches full charge mode as current is constant and similarly in CV method in initial stages current drawn by battery is high which may cause temperature to rise to undesired values. To overcome these disadvantages the CC-CV charging can be switched according to the requirements using automated Fuzzy Logic Controller (FLC). The CC-CV charging of the EV battery using SEPIC with the help of a fuel cell through FLC has been proposed and simulated using MATLAB/Simulink software, and the results have been discussed.
从可再生能源中提取能源及其在电动汽车(ev)中的利用为绿色交通选择铺平了道路。电池充电是当今电动汽车面临的挑战。恒流(CC)和恒压(CV)充电方法与其他电动汽车电池充电技术相比具有许多优点。燃料电池是产生直流能量的方式之一,可以直接用于电动汽车电池的充电。由于燃料电池是直流电源,车载快速充电可以很容易地通过各种功率转换器实现,但单端初级电感转换器(SEPIC)将最有效地为上述场景服务。在CC方法中,由于电流恒定,如果电池达到完全充电模式,电池可能会过度充电;同样在CV方法中,在初始阶段,电池所吸取的电流很高,可能导致温度上升到不希望的值。为了克服这些缺点,可以使用自动模糊逻辑控制器(FLC)根据要求切换CC-CV充电。利用MATLAB/Simulink软件,提出了燃料电池通过FLC使用SEPIC对电动汽车电池进行CC-CV充电的方法,并对结果进行了讨论。
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引用次数: 7
Handwritten Text Recognition using Deep Learning 使用深度学习的手写文本识别
There are many researchers working on handwritten text recognition (HTR) and also contributing to HTR domain. Even though many research methods are existing for HTR, there is a need for some more improvements in the accuracy of the HTR systems. This paper is a contribution of the application of the Deep Learning algorithm for the HTR system. In this paper first we will collect the data for training the handwritten texts, later features have been extracted from those text datasets and perform training of the model using Deep Learning approach. In this work we are going to use the strategy to recognize in terms of words rather those characters so that accuracy will be improved. The built model using LSTM deep model achieves a very good accuracy. Lastly, this developed approach of the HTR system is integrated into the OCR system and comparison of results are reported in this paper. Two approaches have been compared in this paper on IAM handwritten data set, and found that 2DLSTM based approach outperforms the other approach.
手写体文本识别(HTR)领域有许多研究人员,他们对手写体文本识别领域也做出了贡献。尽管已有许多研究方法,但HTR系统的精度还有待进一步提高。本文是深度学习算法在HTR系统中应用的一个贡献。在本文中,我们首先收集用于训练手写文本的数据,然后从这些文本数据集中提取特征,并使用深度学习方法对模型进行训练。在这项工作中,我们将使用该策略来识别单词而不是那些字符,从而提高准确性。利用LSTM深度模型建立的模型达到了很好的精度。最后,本文将HTR系统的开发方法与OCR系统相结合,并对结果进行了比较。本文在IAM手写数据集上比较了两种方法,发现基于2DLSTM的方法优于另一种方法。
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引用次数: 36
期刊
2020 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)
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