An Implementation of Polyglot Voice Supervise Home Device Using Raspberry Pi

Most of us tend to enjoy the ease of living by doing the bare minimum. The same applies while operating the devices at home by just a few touches or by using our voice in the preferred language. A smart home is an Internet of Things (IoT) platform that uses the internet to control the devices at our home, and this technology has grown enormously over the past few years encouraging new ideas. And with that thought, this system will be implementing Home Automation with Raspberry Pi and Google Assistant by controlling the appliances like lights, fans, air conditioners, temperature sensors, and more, in any preferred language.  Platforms like If This Then That (IFTTT), Adafruit, Message Queueing Telemetry Transport (MQTT), and Raspberry Pi IO are used to connect the hardware with the software that is a common path for devices that are connected to the Relay module and the Google Assistant. The IFTTT platforms are easily available on our smartphones or a website that makes it easy for us to access different devices at different parts of the house or anywhere. Home automation minimizes the manual switching  ON/OFF of the appliances whilst being controlled by the commands that are given by the users. This project builds an automation system that uses the range of Wifi or Bluetooth, which is easily accessible by the users to connect their devices and control them by voice through Google Assistant. This makes it easy for the users to access their devices wherever they are.  Home automation comes as an advantage for older people and especially the physically disabled. The main objective of this proposed project is to provide a comfortable and a digitalized environment to use the day-to-day appliances with added security

AmIE: An Ambient Intelligent Environment for Assisted Living

In the modern world of technology Internet-of-things (IoT) systems strives to provide an extensive interconnected and automated solutions for almost every life aspect. This paper proposes an IoT context-aware system to present an Ambient Intelligence (AmI) environment; such as an apartment, house, or a building; to assist blind, visually-impaired, and elderly people. The proposed system aims at providing an easy-to-utilize voice-controlled system to locate, navigate and assist users indoors. The main purpose of the system is to provide indoor positioning, assisted navigation, outside weather information, room temperature, people availability, phone calls and emergency evacuation when needed. The system enhances the user's awareness of the surrounding environment by feeding them with relevant information through a wearable device to assist them. In addition, the system is voice-controlled in both English and Arabic languages and the information are displayed as audio messages in both languages. The system design, implementation, and evaluation consider the constraints in common types of premises in Kuwait and in challenges, such as the training needed by the users. This paper presents cost-effective implementation options by the adoption of a Raspberry Pi microcomputer, Bluetooth Low Energy devices and an Android smart watch.Comment: 6 pages, 8 figures, 1 tabl

Personal Assistant Robot

Since the boom in science and technology, humans have been trying to invent machines that could reduce their efforts in day to day activities. In this paper, we develop a personal assistant robot that could pick up objects and return it to the user. The robot is controlled using an android application in mobile phones. The robot can listen to user’s command and then respond in the best way possible. The user can command the robot to move to given location, capture images and pick objects. The robot is equipped with ultrasonic sensor and web camera that helps it to move to different location effectively. It is also equipped with sleds that play important role in object picking process. The robot uses a tiny YOLOv3 model which is rigorously trained on several images of the object. There are some possible improvements that can be achieved which could help this robot to be used in several other fields as well

Smart Mirror for Home Automation

Smart Mirror for Home Automation This research describes the design, construction and working of the smart mirror. Every morning our day begins by watching ourselves at least once in mirror before leaving our homes. We interact with it psychologically to find out how we look and how our attire is. Smart Mirror or Magic Mirror is one of the applications of Raspberry Pi. A computer screen embedded in mirror looks very futuristic. The Raspberry Pi stays at back scenes and controls the data displayed on mirror. While looking at mirror, the user can look at various notifications from social sites as well news, weather forecast and more things. Such mirrors can be programmed to work as control home appliances by voice input. The Raspberry Pi is connected to monitor via HDMI as well as it also has built-in Wi-Fi and Bluetooth interfaces so we can just swipe music and videos to mirror

Hardware Architecture and Implementation of an AI Pet Robot

The concept of AI companionship is gaining popularity in recent times. Ourproject is an attempt to create a robotic companion that can act just like apet. We created a Pet Robot that can perform various functions like recognisepeople, recognise objects, recognise emotions, play games, follow a personaround, listen to voice commands, dance and so on. This paper focuses on thehardware aspect of the robot and the working of the Core program (Kernel). Itfurther discusses the algorithm that was implemented in this architecture andcompares the final version with other variations. Our work was able to createa fully functioning AI pet robot by using just cheap commercially availabledevelopment boards, motors and a Desktop PC

PROPOSING MODEL OF HANDLING LANGUAGE FOR SMART HOME SYSTEM CONTROLLED BY VOICE

Voice interaction control is a useful solution for smart homes. Now it helps bring the house closer to people. In recent years, many smart home-based voice control solutions have been introduced (for example: Google Assistant, Alexa Amazon etc.). However, most of these solutions do not really serve Vietnamese people. In this paper, we study and develop Vietnamese language processing model to apply to smart home system. Specifically, we propose language processing methods and create databases for smart homes. Our main contribution of the paper is the Vietnamese language processing database for smart-home system

Development of a Miniature Smart Home Testbed for Research and Education.

We present a cloud based smart home testbed using a miniature doll house. In particular, we use this testbed to demonstrate the energy conservation system with the interconnected network of devices, the robust security system with face recognition feature, and the home assistant robot with voice-controller. The test bed consists of a smart home server, a home controller, a smart home assistant robot, a security camera, and appliances communicating with each other using web-socket and existing Social Network Software SDKs. The proposed testbed allows research and education in areas such as smart-grid, wireless sensor networks, machine learning, pattern recognition, embedded programming, natural language processing, social media sharing etc. We also propose a security system based on face recognition. In particular, we develop this system for giving access into a home for authenticated people. The classifier is trained using a new adaptive learning method. The training data is initially collected from social networks and the accuracy of the classifier is incrementally improved as the user starts using this system. A novel method has been introduced to improve the classifier model by human interaction and social media. By using a deep learning framework - TensorFlow, it will be easy to reuse the framework to adapt with many devices and applications.Electrical Engineerin

Design of passive SD modulator for ESP32

This thesis addresses the problem of voice recognition, by studying how to build a lowcost solution for data acquisition, presents the analysis, design implementation and simulation of a low-cost continuous-time(CT) passive sigma-delta modulator(SDM) with signal-to-noise-plus-distortion ratio(SNDR) > 86dB to increase fidelity in voice recognition applications. Employing passive RC integrators and a differential signal structure, the CT passive SDM is optimized to work as independently from a specific comparator module as possible, by decreasing the necessary gain of the comparator in the modulator gain. Nevertheless, the loop gain is restricted by the comparator’s noise, aggravated by the high attenuation of the passive RC integrators on the signal, causing low voltage swing at the comparator’s input. It is discussed the viability of utilizing a microprocessor (μP) as substitute of the comparator block in a CT passive SDM, specifically, the esp32. Due to hardware limitations and the high-frequency requirements of the CT passive SDM, it is proven this substitution is not viable. Along the course of the design implementation a comparison in the performance of three different simulation software is presented, these software being, the open-source LTspice VII, the open-source Ngspice and the private Cadence Virtuoso. As it was necessary to change simulation software at different stages in the design of the circuit