Voice controlled home automation system using Natural Language Processing (NLP) and Internet of Things (IoT)

Rani, Paul Jasmin; Bakthakumar, Jason; Kumaar, B. Praveen; Kumaar, U. Praveen; Kumar, Santhosh

doi:10.1109/iconstem.2017.8261311

Cited by 75 publications

(28 citation statements)

References 6 publications

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“…A voice-controlled home automation system was proposed by Rani et al [6], which was based on artificial intelligence and natural language processing (NLP) techniques. To control home appliances, voice commands are issued over a mobile phone and interpreted using the predefined natural language processing medium.…”

Section: Related Literaturementioning

confidence: 99%

Internet of Things-Based Intelligent Smart Home Control System

Taiwo

Ezugwu

2021

Security and Communication Networks

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The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.

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Section: Related Literaturementioning

confidence: 99%

Internet of Things-Based Intelligent Smart Home Control System

Taiwo

Ezugwu

2021

Security and Communication Networks

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“…We no longer need to go near each device to manually operate it. Most researchers utilized artificial neural networks to classify user inputs to create a natural dialogue, giving users the ability to control appliances by voice or text commands [24,25]. Voice recognition based on AI provides audio-based interaction technology that lets the users have full control over their home environment [26].…”

Section: Second-round Selection Of Literaturementioning

confidence: 99%

Review on the Application of Artificial Intelligence in Smart Homes

et al. 2019

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Smart home and artificial intelligence technologies are developing rapidly, and various smart home products associated with artificial intelligence (AI) improved the quality of living for occupants. Although some studies discussed the application of artificial intelligence in smart homes, few publications fully considered the integration of literature and products. In this paper, we aim to answer the research questions of “what is the trend of smart home technology and products” and “what is the relationship between literature and products in smart homes with AI”. Literature reviews and product reviews are given to define the functions and roles of artificial intelligence in smart homes. We determined the application status of artificial intelligence in smart home products and how it is utilized in our house so that we could understand how artificial intelligence is used to make smart homes. Furthermore, our results revealed that there is a delay between literature and products, and smart home intelligent interactions will become more and more popular.

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“…Most such implementations for the Internet of Things offer control of home devices through the integrated NLP system of Android or iOS smartphones [7], or of simpler devices like Alexa by Amazon [8]. Many other implementations develop custom NLP systems for smart home automation with the whole project based on the NLP system design and its final implementation [9][10][11]. In the current project, the NLP system used is an external online service.…”

Section: Related Workmentioning

confidence: 99%

“…Give me information about microcontrollers. C. 10 How are you? Table 6 includes the response time from the NLP system (Dialogflow API) for each of the sample test commands of Table 5 under three different network throughputs.…”

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confidence: 99%

Control of Smart Home Operations Using Natural Language Processing, Voice Recognition and IoT Technologies in a Multi-Tier Architecture

Alexakis

Panagiotakis

Fragkakis

et al. 2019

Designs

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The Internet of Things (IoT) is an emerging Internet-based architecture, enabling the exchange of data and services in a global network. With the advent of the Internet of Things, more and more devices are connecting to the Internet in order to help people get and share data or program actions. In this paper, we introduce an IoT Agent, a Web application for monitoring and controlling a smart home remotely. The IoT Agent integrates a chat bot that can understand text or voice commands using natural language processing (NLP). With the use of NLP, home devices are more user-friendly and controlling them is easier, since even when a command or question/command is different from the presets, the system understands the user’s wishes and responds accordingly. Our solution exploits several available Application Programming Interfaces (APIs), namely: the Dialogflow API for the efficient integration of NLP to our IoT system, the Web Speech API for enriching user experience with voice recognition and synthesis features, MQTT (Message Queuing Telemetry Transport) for the lightweight control of actuators and Firebase for dynamic data storage. This is the most significant innovation it brings: the integration of several third-party APIs and open source technologies into one mash-up, highlighting how a new IoT application can be built today using a multi-tier architecture. We believe that such a tiered architecture can be very useful for the rapid development of smart home applications.

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Voice controlled home automation system using Natural Language Processing (NLP) and Internet of Things (IoT)

Cited by 75 publications

References 6 publications

Internet of Things-Based Intelligent Smart Home Control System

Internet of Things-Based Intelligent Smart Home Control System

Review on the Application of Artificial Intelligence in Smart Homes

Control of Smart Home Operations Using Natural Language Processing, Voice Recognition and IoT Technologies in a Multi-Tier Architecture

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