Cloud Computation Based Urban Management System Using Ros

Megalingam, Rajesh Kannan; Sathi, Sarveswara Reddy; Pula, Bhanu Teja; Chandrika, Dega; Reddy, Nara Sainath

doi:10.1109/icoei.2019.8862790

Cited by 7 publications

(1 citation statement)

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“…In this way, the central processing unit is able to monitor and control the different sensor modules and send appropriate noti cations to the mobile phone by means of SMS messaging. The research aims to automate watering greeneries, reduce water wastage, monitor waste in dustbins, send alerts during emergencies like oods and res, and implement a smart street light network using SMS services [7]. Incorporate steps such as Feature Engineering, Feature Selection, Exploratory Data Analysis (EDA), Model Training, etc.…”

Section: Literature Surveymentioning

confidence: 99%

A Proposed Cognitive Framework Model for a Student Support Voice based Chatbot using XAI

Ghosh¹,

Ghatak²,

Paul³

2023

Preprint

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As the calling agent directly calls and makes interaction (checking for valid phone numbers before calling) with the user such as using a pie event, even the agent can also record the conversation and transcribe information. The other voice chat agent is capable of taking voice input as well as text input. The user's information can be interpreted by it. And lastly, make a CSV or xlsx file of the user's input. The model has been designed in such a way that it can convert the voice provided as input by the user and analyze the sentiments contained in it by converting it into text using the speech-to-text module of the pyaudio package in Python. In the case of data cleaning, special characters have been removed from the .JSON file and provided to the NLTK tokenizer. When the model has been successfully built, users can enter their queries through voice and text, and the model will predict based on the text entered. The model first deciphers the voice entered quantitatively and ascertains the pitch, decibel, and amplitude, and enumerates a categorical cross-validation of the voice with the parameters that are set. It undergoes polarity checking under the positive and negative polarity counter and then the values of the positive and negative polarities of the text are stored in the program. When the agent finally works, it takes into account all the aspects with which it is trained, and provides the perfect outcome. If the user also enters the incorrect dialogue on their phone, the call will instantly cease. After that, we'll use an api post request to create and establish a connection. When it comes to encouraging different individuals to call for admission-related or medical-related reasons, the calling agent has a huge effect on that issue. In some cases, the user's number has been used. In this paper we have designed and implemented automation testing framework for testing web applications. This new automation testing framework has been implemented using selenium WebDriver tool. Using this framework tester can easily write their test cases efficiently and in less time. Tester need not to study the selenium web driver tool in detail. This framework is helpful to developer to analyze their code due to screen shot property of framework. This framework produces the customized test report to tester. It is very easy to maintain and repair the test suite for new release of the application using this framework. Software organizations are more committed to creating high-quality software solutions at lower costs. Previously, manual testing was used, but due to the increased complexity of the program, testing automation is now required. Selenium, GUI testing, Cross Browser testing, and Web automation are used more effectively. we used Selenium web driver Python to accomplish Web Automation testing.

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Section: Literature Surveymentioning

confidence: 99%