ABSTRACT
Companion bots such as chatbots in cyberspace or robots in real space gained popularity during the COVID-19 pandemic as a means of comforting humans and reducing their loneliness. These bots can also help enhance the lives of elderly people. In this paper, we present how to design and implement a quick prototype of companion bots for elderly people. A companion bot named "Hello Steve"that is able to send emails, open YouTube to provide entertainment, and remember the times an elderly person must take medicine and remind them is designed and implemented as a quick prototype. In addition, the bot combines the features of a mobile robot and a chatbot. The experimental results show the effectiveness of the design through its very high accuracy when navigating mobile-robot-like tasks and responding to chatbot-like tasks via voice commands. © 2023 MYU K.K.
ABSTRACT
A smart home is a component of the Internet of Things (IoT) technology implementations that help people with their daily activities. To link devices to the Internet of Things, a variety of communication methods can be used. Impairments restrict the activities that disabled people can participate in. This paper proposes an automation system that enables disabled people to control televisions (TVs), lights, and fans, any other electrical devices at home, using just voice commands without moving. The Google Assistant feature for mobile phones is used to achieve voice recognition on electronic components. This system also contains the concept of human temperature measurement where the temperature sensor, fixed to the door, checks the temperature of the person and opens when it is normal. This prevents the user from getting infected by the illness, keeping in mind the present situation of covid19. © 2023 IEEE.
ABSTRACT
Speech recognition systems have made remarkable progress in the last few decades but most of the work has been done for adult speech. The rise of online learning during Covid-19 pandemic highlights the need for voice-enabled assistants for children so that they can navigate the menus and interfaces seamlessly. Speech recognition for children will also be very useful to develop automated reading assessment tools. However, such technology for children is challenging for a country like India where differences in accents, diction and enunciation is significant but available children speech data is limited. Through this paper, I tried various approaches to recognize hindi word audios. Commercially available Google Speech-to-Text performs poorly with only 49.7% accuracy at recall of 0.24 while recognising audio samples containing hindi words spoken by children. Using the same dataset, I experimented with clustering algorithm and logistic regression and found that the accuracy improves upto 81% with logistic regression. The paper also highlights the importance of data preprocessing by performing noise reduction using Butterworth low pass filters. © ICNLSP 2021. All Rights Reserved.
ABSTRACT
The outbreak of the Covid-19 pandemic has resulted in a surge in the generation of medical waste. Due to the transmissible nature of the Virus and the lack of effort at proper disposal, the safety of the front-line health workers, as well as the disposer, is at risk. Hence, to mitigate the spread of infectious diseases, a system is proposed that uses a robotic arm for segregating medical waste automatically. The robotic arm is operable through voice commands, and the segregating operation could function in automatic and manual mode. The system uses the YOLOv3 (You Only Look Once) algorithm to detect and classify the medical waste and then uses the Robot Operating System (ROS) platform to pick up and drop the waste object into color-coded bins. For this research, the medical waste has been categorized into 4 types, and for each type, a color-coded bin has been used for segregation. Our system has achieved 94% training accuracy for the YOLOv3 model on a custom dataset, whereas the system's overall accuracy in automated mode was 82.1%, derived after 30 trials. In the case of manual mode, an average accuracy of 82.5% has been achieved for the same number of trials. © 2022 IEEE.
ABSTRACT
COVID-19 has shocked the retail industry, customers’ concerns for their health and safety are taking business away from shopping malls. Mall owners are thinking of finding new ways to bring their business back in this post-pandemic world. How to protect customers from COVID-19 in shopping malls has been a problem. This study presents an enhanced mall security system to help enforce wearing masks and proper social distancing in shopping malls using augmented reality (AR). We created a novel visualization way: Radar vision to display detected people in the perspective of mall guards, to help guards react quickly to violations, and better enforce the mandatory rules. When the mall guards wearing hololens activate the radar vision function, they can see all people violating wearing masks or social distance mandates through the wall. Mall guards can use gaze to select the target person and then use the voice command to activate the navigation arrow to help them quickly go to the scene. In addition to helping mall guards to enforce mandates, the system also provides assisted functions to protect customers. When the violation situation appears around a customer, the system will alert them to avoid and show an avoidance arrow until the user goes in the correct direction. We demonstrated a preliminary system with four surveillance cameras in our school building area. The pilot study shows that our system can effectively detect and display radar images, increasing the efficiency of mall guards and reducing customer safety concerns. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Humans start their day by looking in the mirror at least once before leaving their homes every morning. In addition, they waste some considerable time of their busy workload in front of the mirror. To make this time more productive and useful, there ought to be a system that can be readily conducted, user-friendly, and smart according to the constant progress on the Internet of Things. The intelligent mirror is a new addition to the smart device family, which is a straightforward concept. There will be a screen placed behind a two-way mirror, and this Intelligent Mirror turns our room or bathroom mirror into a personal assistant with artificial intelligence. The purpose is to develop a smart mirror that can automate working humans' busy daily routines and manage their tasks when they spend their time in front of a mirror. To make the most of this moment, users can securely access all the relevant details of the day by looking in the mirror simultaneously. The intelligent mirror, which a single voice command can activate, will significantly help disabled persons and the general. Raspberry Pi has been used to build the proposed intelligent mirror, linked to the digital world via the Internet. The mirror can communicate with the user through voice commands and reply appropriately. The monitoring of emotions and health measuring function will provide a distinctive experience to the users. The mirror will reflect important elements such as weather, date & time, covid-19 situation reports, local news, To-do list, water reminder, home workouts, and meal plans. The mirror can also handle specialized functions such as automating and controlling home IoT devices. © 2021 IEEE.
ABSTRACT
In this project, a low-cost voice operated vending machine (VOVM) is designed using a V3 voice recognition module which is a touchless base vending system. The basic vending machine represents an automatic seller machine where the buyer puts the money in terms of coin or banknote into the vending machine. Then, the required product will be vending out from the machine after selecting the item which is store inside the system. After analysing several vending machines, it is found that the proposed VOVM is more advanced than the other existing vending machine as it can select the items without any contact with the system. This VOVM may also be useful to this current pandemic situation of COVID-19 because of its unique features. The main objective is to upgrade the touchbased vending machine to voice operated system as one can select any items in the vending machine using voice command. This system will make it easier for the user to interact with the machine for everyone and also it can be deployed in every corner of the workplace, hospital, airport, schools, railway station, etc. for selling different kinds of products efficiently. © 2021 IEEE.
ABSTRACT
Nowadays, all countries around the globe are trying their best to prevent the spread of Covid-19 from reaching their people. However, the virus spread is through the transmission of close contact with the infected person and touching a surface that already contains the virus. This project presents Voice User Interface (VUI) Smart Office Door System that interact with the Internet of Things (IoT) to execute the command given by the user. This project use Raspberry Pi as microcontroller which Thonny Python software used for running the coding script of the system. The electrical components such as dc motors and LEDs are connected to General-Purpose Input Output (GPIO) pin of Raspberry Pi and motor driver. One of the dc motors used for controlling the lock and another one used for controlling the door. Blue LED used as locked door notification while green LED used as unlocked notification. Microphone and speaker connect to the Raspberry Pi through usb port and Bluetooth. This system used Google Assistant as its VUI to control the smart door contactless. The user can give the command to the system through microphone to control the output of the system. The purpose of this project is to invent the smart door with IoT technology that help prevent the spread of Covid-19 at the workplaces. © The 2022 International Conference on Artificial Life and Robotics (ICAROB2022).
ABSTRACT
The year 2020 will always be remembered as the year of a global pandemic. With many places gradually emerging out of lock-downs, the thought of concerted existence amid COVID-19 is being revisited. One such problem is the use of elevators in any building, use of elevators in the times of COVID can be very risky in the transmission of virus. Based on this hypothesis, this paper presents a methodology for maintaining sanitization and security, by incorporating facial recognition in elevators. These elevators are designed to work using voice commands making them completely contactless, also this system includes a thermal sensor to measure the body temperature of every user and notify everyone around them. Using all these different sensors embedded in machine, the device can do much more than an ordinary elevator and can act as a modern smart device that is capable of solving all the problems single handedly. The key aim of this research paper is to demonstrate how various modules function together to accomplish a common goal: to render the experience of moving between floors smart and sanitary during COVID. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.