1. SystemArchitecture
Isha Pathania M.E. Dept. of Computer Science and Engineering, Chandigarh University, Gharuan ***
Key Words: Internet of Things, Natural Language Processing, Technology, Smart Home Operations, Voice recognitionINTRODUCTION
A growing Internet based architecture is IOT(Internet Of Things), it usually enables the data exchange and also the services that are present in a global network. Along with the arrival of the IOT(Internet of Things),many devices are attaching with theInternet with the aim toprovide help to many people. Inthispaper,we generally introducedanIoT Agent, which is usuallyaWebapplicationfor observingand managinga smart home to a certain extent. TheIoT Agent initiatesachatwhichisusedtorecognizethe voiceortext commandsusing NLP(NaturalLanguageProcessing).Alongwith theusage ofNaturalLanguageProcessing(NLP),homedevicesareevenmuch moreuser friendlyandmanaging themisa littlebit easier,evenwhenacommandor thecommand/question isdissimilar fromthepresets,thesystemappreciatesthe user’s desires and act upon accordingly. The solution exploits some of the available APIS(Application Programming Interfaces), whose name are: the Dialogflow API for the well organized integration of Natural Language Programming(NLP),theMessageQueuingTelemetryTransport(MQTT)forthelightweightmanagementofthe Firebaseand manyactuatorsforthepurposeof dynamicdatastorage. Inthispaper,Ihaveproposed an applicationfor managingthe smarthometoacertainextent.Inmy applicationIobtained thevaluesofsensorsand to managethe actuators I used natural language. In addition, any person could also even use the chatbot present in that main page of my application, with the purpose to communicate with it using free text. For the purpose of training of my NLP (Natural Language Processing) system, I had used an API which is DialogflowApplicationProgrammingInterface.
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056 Volume: 09 Issue: 03 | Mar 2022 www.irjet.net p ISSN: 2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page222
Using Natural Language Processing(NLP), Voice Recognition and Internet of Things(IoT) Technologies in the Multi-Tier Architecture for Controlling Smart Home Operations
Figure 1 which is shown below depicts the comprehensive architecture of my ecosystem, which is comprised of manysubparts.Theusermakesuseof theIoTAgentanda webapplicationwhichcan host allofthefunctionality,could monitorandcontrolthe actuatorsandthesensors,that areunifiedinto thesmarthome.
Abstract- AlongwiththearrivaloftheIOT(InternetofThings),many devicesareattaching with theInternet withtheaim toprovide help to many people. Inthispaper,Igenerally introducedanIoTAgent, which is usuallyaWebapplicationfor observingand managingasmart home toacertain extent.TheIoTAgentinitiatesachatwhichisusedtorecognizethe voice ortext commandsusing NLP(NaturalLanguageProcessing).Alongwith theusage ofNaturalLanguageProcessing(NLP), home devices are even much moreuser friendly andmanaging themis a little bit easier,evenwhenacommandor the command/question isdissimilar fromthepresets,thesystemappreciatestheuser’sdesiresandactuponaccordingly.The solution exploits some of the available APIS(Application Programming Interfaces), whose name are: the Dialogflow API for the well organized integration of Natural Language Programming(NLP),the Message Queuing Telemetry Transport(MQTT)forthe lightweight management of the Firebase and many actuators for the purpose of dynamic data storage.
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056 Volume: 09 Issue: 03 | Mar 2022 www.irjet.net p ISSN: 2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page223 Figure1. Mainsystemarchitecture. Figure2. IoTAgent’swelcomepage
3. MicrocontrollerImplementation
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Generic
2.
Figure3. interconnectionof andsensorswithmicrocontrollers.
My system is an extension of the usage of the NLP(Natural Language Processing). NLP(Natural Language Processing) is a part of AI( Artificial Intelligence) which uses computational techniques to understand, it observe and renewhumannaturalspeech TheIoTAgentusesNLP(NaturalLanguageProcessing)fortheuseofvoice chatfeature,and forits text chatsystemtoo Dialogflowisaveryamazing solutionfor NLP’sconvenientintegrationin the IoTsystem. DialogflowAPIisalsoprovidedbyGoogleandit usestechniquesofmachine learningforthetrainingprocess.
This section represent the most important logic of the microcontroller’s code which are at the maximum edge of mysystem.Thecodeforbothofthedifferent microcontrollersiswrittenat theArduinoIDE.Ihad dividedmy codeinto twoseparatecodeblocks.
NaturalLanguageProcessing(NLP)System
actuators
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056 Volume: 09 Issue: 03 | Mar 2022 www.irjet.net p ISSN: 2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page225 4. WebApplicationImplementation ThemainWebapplicationismadebytheuseof theAngularframework.Angularis thecommon framework whichisalso developedbyGoogleforthe purposeofcreatingsingle pageapplicationswhichcan beusedfordesktop, webor mobile also.
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056 Volume: 09 Issue: 03 | Mar 2022 www.irjet.net p ISSN: 2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page226 Figure9. TheIoTAgentloginscreen.
Figure10. TheIoTAgentChatbotenvironment
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Figure11.TheIoTAgentDashboard. Below is the sample of test commands, by using these commands we will find decision making time of IOT Agent, responsetimeofvariouscontrollersandtotalresponsetime.
Table1. Sampleoftestcommands. 12:Givenbelowillustratestheresults. Figure12. ResponsetimeofNLPenginepernetworkbandwidth
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Figure
Table2. Dataprocessinganddecision makingtimeoftheIoTAgentunderdifferentaccessnetworks. C./B. ADSL(D.:3.93) Fast 3G Slow3G(D.:0.36 Mbps/U.:0.57 Mbps) Mbps/U.:0.45 Mbps) Mbps/U.:0.26 Mbps) C.1 4millisecond 7millisecond 5millisecond C.2 2millisecond 2millisecond 2millisecond C.3 1millisecond 1millisecond 1millisecond C.4 1millisecond 1millisecond 1millisecond C.5 4millisecond 4millisecond 6millisecond C.6 3millisecond 3millisecond 7millisecond C.7 1millisecond 1millisecond 1millisecond C.8 1millisecond 1millisecond 1millisecond C.9 0.5millisecond 0.5millisecond 0.5millisecond C.10 0.5millisecond 0.5millisecond 0.5millisecond
Volume: 09 Issue: 03 | Mar 2022 www.irjet.net p ISSN: 2395 0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 results Figure13 Data makinganddataprocessingtimeoftheIoTAgent.
Table3. Responsetimeofvariousmicrocontrollersundermany accessnetworks. C./B. ADSL (D.:3.93 Mbps/U.:0.57Mbps) Fast 3G (D.:1.51 Mbps/U.:0.45Mbps) Slow 3G Mbps(D.:0.36 / Mbps)U.:0.26 C.1 20 millisecond 70millisecond 730 millisecond C.2 30 millisecond 100millisecond 720 millisecond C.5 40 millisecond 50millisecond 156 millisecond C.6 30 millisecond 30millisecond 720 millisecond
Figure14. Responsetimeofmicrocontrollersunderdifferentaccessnetworks. Table4:Totalresponsetime
C./S. Response Time Of NLP DataProcessingTime Response Time Of Microcontroller C.1 2001millisecond 5millisecond 730millisecond C.2 2001millisecond 2millisecond 720millisecond C.3 2002millisecond 1millisecond 0millisecond C.4 2001millisecond 1millisecond 0millisecond
Certified Journal | Page229 Figure13illustratesthe
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2.Wortmann,F.;Flüchter,K.InternetofThings.Bus.Inf.Syst.Eng. 2015
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1.Ashton,K.That“InternetofThings”thing.RFIDJ. 2009
C.5 2003millisecond 6millisecond 156millisecond C.6 2003millisecond 7millisecond 720millisecond C.7 2002millisecond 1millisecond 0millisecond C.8 2002millisecond 1millisecond 0millisecond C.9 2002millisecond 0.5millisecond 0millisecond C.10 2001millisecond 0.5millisecond 0millisecond
The IoT Agent initiates a chat which is used to recognize the voice or text commands using NLP(Natural Language Processing).Alongwith theusage ofNaturalLanguageProcessing(NLP),homedevicesareevenmuch moreuser friendly andmanaging themisalittlebit easier,evenwhenacommandor thecommand/question isdissimilar fromthepresets,the system appreciates the user’s desires and act upon accordingly. The solution exploits some of the available APIS(Application Programming Interfaces), whose name are: the Dialogflow API for the well organized integration of NaturalLanguageProgramming(NLP),theMessageQueuingTelemetryTransport(MQTT)forthelightweightmanagementof the Firebaseandmanyactuatorsforthepurposeof dynamicdatastorage.Inthispaper,Ihaveproposedan applicationfor managingthe smart home to a certain extent. In my application I obtained the values of sensors and to manage the actuatorsIused naturallanguage.Inaddition,anypersoncould alsoevenusethe chatbotpresent inthat mainpageof myapplication,withthepurposetocommunicatewithitusingfreetext.For thepurposeof trainingof my NLP(Natural LanguageProcessing)system,Ihad usedan APIcalledDialogflowApplicationProgrammingInterface.
MysystemisanextensionoftheusageoftheNLP(Natural LanguageProcessing).NLP(Natural LanguageProcessing)isa part of AI( Artificial Intelligence) which uses techniques that are computational to understand, it observe and renew humannaturalspeech.TheIoTAgentusesNLP(NaturalLanguageProcessing)fortheuseofvoice chatfeature,and forits text chatsystemtoo.DialogflowisaveryamazingsolutionforNLP’sconvenientintegrationinthe IoTsystem.Dialogflow APIisalsoprovidedbyGoogleanditusestechniquesofmachine learningforthetrainingprocess.
Figure15 End to endResponseTimeForManySampleCommands.
REFERENCES
Conclusions
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