Google Assistant Research Articles

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network.

Robotics is one of the most emerging technologies today, and are used in a variety of applications, ranging from complex rocket technology to monitoring of crops in agriculture. Robots can be exceptionally useful in a smart hospital environment provided that they are equipped with improved vision capabilities for detection and avoidance of obstacles present in their path, thus allowing robots to perform their tasks without any disturbance. In the particular case of Autonomous Nursing Robots, major essential issues are effective robot path planning for the delivery of medicines to patients, measuring the patient body parameters through sensors, interacting with and informing the patient, by means of voice-based modules, about the doctors visiting schedule, his/her body parameter details, etc. This paper presents an approach of a complete Autonomous Nursing Robot which supports all the aforementioned tasks. In this paper, we present a new Autonomous Nursing Robot system capable of operating in a smart hospital environment area. The objective of the system is to identify the patient room, perform robot path planning for the delivery of medicines to a patient, and measure the patient body parameters, through a wireless BLE (Bluetooth Low Energy) beacon receiver and the BLE beacon transmitter at the respective patient rooms. Assuming that a wireless beacon is kept at the patient room, the robot follows the beacon’s signal, identifies the respective room and delivers the needed medicine to the patient. A new fuzzy controller system which consists of three ultrasonic sensors and one camera is developed to detect the optimal robot path and to avoid the robot collision with stable and moving obstacles. The fuzzy controller effectively detects obstacles in the robot’s vicinity and makes proper decisions for avoiding them. The navigation of the robot is implemented on a BLE tag module by using the AOA (Angle of Arrival) method. The robot uses sensors to measure the patient body parameters and updates these data to the hospital patient database system in a private cloud mode. It also makes uses of a Google assistant to interact with the patients. The robotic system was implemented on the Raspberry Pi using Matlab 2018b. The system performance was evaluated on a PC with an Intel Core i5 processor, while the solar power was used to power the system. Several sensors, namely HC-SR04 ultrasonic sensor, Logitech HD 720p image sensor, a temperature sensor and a heart rate sensor are used together with a camera to generate datasets for testing the proposed system. In particular, the system was tested on operations taking place in the context of a private hospital in Tirunelveli, Tamilnadu, India. A detailed comparison is performed, through some performance metrics, such as Correlation, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), against the related works of Deepu et al., Huh and Seo, Chinmayi et al., Alli et al., Xu, Ran et al., and Lee et al. The experimental system validation showed that the fuzzy controller achieves very high accuracy in obstacle detection and avoidance, with a very low computational time for taking directional decisions. Moreover, the experimental results demonstrated that the robotic system achieves superior accuracy in detecting/avoiding obstacles compared to other systems of similar purposes presented in the related works.

Home Automation with Intruder Detection and Energy Control

In previous project we made a home automation system, where we can control our appliances through Blynk app and Google assistant with the help of IFTTT. As an extension we will provide feedback to user whether the appliance is on or off. We will also use sensors like LDR for measuring light intensity in this project to make it smart. We will also include security system where in we have sensors to doors and windows and give buzzer along with an alert message to the user. On a whole we will provide a smart home automation system.

Использование технологий искусственного интеллекта для дистанционного обучения

The article describes some practices of voice recognition technologies based on artificial intelligence to improve the educational process in a remote format. This is relevant to modern remote education environment. The author presents an analysis of existing approaches to the use of artificial intelligence technologies in the educational process. Elements of artificial intelligence in a specialist software make the educational process more modern and convenient both for the learner and the teacher. One of the implementations for a natural user interface is a voice-user interface, which recognizes words to understand spoken commands and to answer questions, it converts the text into speech. The author has carried out an analytical review of implementations of specialized applications for Yandex assistant in which, the voice interface is used to improve children's language skills. Algorithm development of an application for Google assistant which uses voice recognition technologies and artificial intelligence for for teaching a foreign language is described. The application can be used in the educational process for teaching academic English; it also allows to increase English vocabulary, train the construction of grammatically correct scientific expressions, and memorize scientific language patterns.

IMPLEMENTATION AND ANALYSIS OF SMART REFLECT EMPLOYING IOT

This paper reports the design and development of a cutting edge smart mirror. It represents a prominent interface for the ambient environment. It presents the functioning of the smart mirror. The project mainly focuses on providing an easy and interesting entity for dwelling a place. The introduced smart mirror is operated employing raspberry pi and will be coupled to the real world through the internet. It comprises of a raspberry Pi, led, monitor, Speaker, two way mirror, acrylic glass. It will foreground some fundamental amenities like date, weather, and time. Moreover it performs advanced functions like Google assistance, Google photos. Smart mirrors are widely used in North America and US countries to attract a large number of customers in retail shops and also in hospitals to display useful information, Further many applications can be implemented in Smart Mirror. Solar energy can also be used to power up raspberry Pi. Touch screen technology is added, and can attract more and more people towards its outstanding feature. The smart mirror is newfangled technology that helps users to access mirrors like a feature in mobile phones.

Object detection YOLO-v4 based smart car system with an integrated Virtual Assistant

Car accidents are a serious social problem that often results in both life loss and financial loss. Most car accidents are caused by a lack of safe distance between cars and also the awareness of the driver. To relieve this issue, in this paper we propose a real-time object detection and safety system. The proposed system consists of two units: a real-time object detection unit and a safety alarm unit. The system is supposed to apply in a normal driving scenario. As for the safety alarm module, it consists of three states: to detect the object; to calculate the safety factor; to determine the driving conditions. To justify the proposed system, a real experiment is conducted. The results show that the system can appropriately signify driving states: safe, dangerous, and warning. By the given experimental results, it implies that the system is feasible and applicable in real-time applications. The objective of this project is to detect objects in real-time and pass information to the user based on the data taken by object detection. The information can be provided to warn the user or to just inform the user based on the result of the sensors. The YOLO algorithm helps to design the output of the sensor based on the necessity of the user. The google assistant allows the user to provide voice commands. The car is integrated with all the above-mentioned.

REFLECTO – A SMART MIRROR STRUCTURE WITH A CONTEXTUAL ASSOCIATION OF INTERNET OF THINGS

Two of the most valued qualities in the modern-day society are punctuality and presentation. The mission helps to develop the above-mentioned personalities. We have developed an artificial intelligence-based smart mirror that helps in reminding the user about their day to day schedule while they spend their time in front of the mirror. This way the user is ensured of comfort in accessing the basic services with a minimum hinderance. The basic function that our prototype is assumed to carry out is to display user their personalised information like date, time, weather forecast, upcoming holidays or saved events and news bulletin. Face recognition feature is also added in order to identify the user using the camera placed behind the mirror. Because of the face recognition feature the mirror will be able to display personalised data that the identified user wants to know. Reflecto can be easily built by using a two-way mirror, concealed LED screen, microphone and camera to make it interactive. The mirror’s functionalities have been extended by integrating it with Google assistant to access IoT devices that have been enabled with home automation.

Voice Controlled Home Automation

Home automation is highly required and helpful nowadays, because people under their work pressure they may not remember to turn off the electrical appliances in the house. It leads to wastage of electricity and power. In modern era power consuming is more important and needed one. This project helps us to ON or OFF the electrical appliances through remote process in remote place. People in their workplace they can control the home gadgets using this system. Everyone has a mail service nowadays every apps requires mail authentication. The mail has its own assistant called google assistant through this assistant we can control the appliances by speech recognition famously called voice recognition or through text in assistant. Electrical appliances are connected by Relay and connected to the network to access it in remote place. For our every command in google assistant it gives us a reply of what is the status. We can set the commands to perform those operations. Only for those specific commands it will perform actions.

Prototype Smart Home Pengendali Lampu Dan Gerbang Otomatis Berbasis IoT Pada Sekolah Islam Pelita Insan Menggunakan Microcontroller Nodemcu V3

Current technological developments have penetrated into human life, such as the development of a smart home called a smart home, that can provide convenience, comfort, safety and efficiency for users. Internet of Things (IoT) can be used in smart homes to control electronic equipment such as lights and home gates. This research designed an automatic controller and light gate based IoT (Internet of Things) smart home system using a NodeMCU microcontroller with a prototype method that aims to save electricity, make it effective and efficient, and make it easier for schoolkeepers to turn on lights and control the gate automatically through the Google assistant. The results of this study are in the form of an automatic light and gate control system using the Google assistant application based on the Internet of Things Using a NodeMCU v3 microcontroller. Can be concluded with the automatic light and gate control system using the google assistant application by giving commands to the google assistant connected to the NodeMCU V3 microcontroller, it can make it easier for school administrators to make efficient and efficient lights or gates using the google assistant application and can facilitate school administrators to maintain the security of the Internet-based school of Things.

Smart home automation using IFTTT and google assistant

The project on the whole revolves and works on voice-based control of devices based on Google Assistant. Google assistant is an Artificial Intelligence platform that provides voice command to make calls, to surf Internet, to set alarm, to set reminders and to open some applications on mobiles. The main objective of this voice automation is to reduce electricity and productive usage of electricity. We build an application that controls any kind of devices using natural voice commands. By this application we can operate or regulate devices from anywhere in the area of our internet range which created an interface between application devices and google assistant. The command lines that are received by google assistant are uploaded to microcontroller and the microcontroller node MCU operates the devices which are connected to set of relays over power supply according to the commands given by the user. The communication between the application devices and microcontroller are established by Wi-Fi (Internet). The status of the devices is visible in cloud dashboard for our confirmation on device functionality either is it turned On or turned Off.

Google assistant, she loves me

Although modern technologies have made life simpler, it has also intensified the complexity of psychopathology. The adoption of the Internet and its numerous artificial intelligence software products into morbid delusions is gaining more momentum. Clinicians must be alert about patients with delusions getting ideas and feedback from the social context in which they live. Here, we discuss a case about a young, single, high-school graduated male, with schizoid personality traits, socially withdrawn, dependent, sexually inhibited with a poor level of occupational and social functioning, who has developed erotomanic delusion with Google Assistant.

Speech and gesture recognition interactive robot

Robots tend to be intellectual and cooperative with the expansion of Industry 4.0, Robots intermingle with humans naturally. They can work collectively with humans. The old training technique was appropriate for the manufacturing work through the human-robot alliance. Extremely trained staff is required for the traditional teaching processes. The paper focus is a normal mode of online coaching and it is pragmatic to errands like soldering, canvas, and imprinting. It offers an online training technique through a combination of dialogue and sign. To express speech and gesture, an Accelerometer and Google assistant are used. In conclusion, an information procedure is engaged to cope-with the combination transcript into the correlative automaton commands. Pragmatism in addition to the efficacy of the planned method was demonstrated by five topics without automaton training skills. Outcomes show that the online automaton training scheme can effectively impart machine exploiters.

Hey Google! will New Zealand vote to legalise cannabis? Using Google Trends data to predict the outcome of the 2020 New Zealand cannabis referendum

BackgroundNew Zealand held a referendum on the legalisation of recreational cannabis in October 2020. Polls preceding the referendum provided contrasting outcomes. We investigated whether internet search data from Google Trends could provide an alternative estimate of the referendum outcome. MethodsWe assessed various methods for accessing Google Trends data, downloading search probability data for google.com searches from New Zealand via trends.google.com, PyTrends and Google Trends Extended for Health. We used daily data for the three months prior to the final referendum date, and hourly data for the final week. We defined two smaller time frames each from daily and hourly data, allowing comparisons over the entire time frames, and progressively closer to the end. Using the selected keyword combination of ‘cannabis referendum yes/no’ we calculated the proportions of ‘yes’ and ‘no’ searches for each time frame/data source combination, aiming for a prediction within 2% of the final result. ResultsData from different sources varied slightly. The method used to aggregate search probabilities over the selected time frame (mean/median) resulted in changes in the predicted outcome for hourly-, but not daily data. On 20 October we predicted the ‘no’ vote at 51.9%–55.4% for daily-, and 60% for hourly data when aggregated using the median, but only 49% for mean hourly data. Hourly data performed poorly at predicting the final 51.2% ‘no’ result, while predictions based on mean daily data for the full voting period provided the best prediction, differing by 0.1–0.2%. ConclusionPredictions based on Google Trends data broadly agreed with polling predictions, but the exact method used affected the eventual prediction. While polls are subject to influence from methodological considerations (e.g., sampling), it is clear that Google Trends data can be used to make a prediction, but do not present a magic bullet solution to polling problems.

Hey Google, Remind Me to Write in My Diary: Voice Assistants for Daily Pain Monitoring

Diaries can be important tools to document and communicate pain symptoms. Diary-based assessments can be prone to poor adherence and limitations with biased recall. One strategy to help adherence is to use voice assistant reminders. A sample of 15 community dwelling aging adults used the Google Assistant for reminders to complete pain self-management tasks. One task was a reminder created to write daily in a pain diary. Within the diary, participants could document a change in pain, pain severity, average and worst amount of pain, and pain relief. At follow-up, it was noted that participants adhered to writing most pain characteristics in the diaries, but there were times that each question was not answered. Participant’s pain characteristics varied, which could be a helpful assessment to communicate to health providers for pain management. This feasibility study is preliminary support that voice assistants may help with the daily pain diary completion.

The Role of Artificial Intelligence in the Indian Education Sector

In the present era, artificial intelligence is a buzz word and it has an impact on various sectors like healthcare, e-commerce, education, etc. Most of the mobile users use AI-based voice assistants like Siri or Google assistant. A study about AI reveals that 71% of participants agree that AI allows people to solve difficult issues and to improve life. People use AI-inspired technologies more than they know they are using. It does seem that the future of Artificial Intelligence will very bright. For the overall development of a nation depends mostly upon its education system. Day by day, the role of it in every sector is increasing including education sector. United Nations' goal is to provide quality education to every person and India will play a major role in this goal achievement. India is a developing country and has younger population in comparison to any country. In terms of population, India is the 2nd largest country and the strength of its students is more than the population of the USA. In addition, it is projected that the population of young people in India will be highest in the world by 2030. In India, there is a shortage of teachers. To compensate for this shortage, AI can play a key role in the education sector in India. AI can help teachers, students, and non-teaching staff in different ways and save time and resources. In the present article, it is discussed about the various roles of AI in the Indian education sector such as it can help teachers in preparing lesson plans according to the class and students, help in reducing the work related to non-teaching activities, provide actionable feedback, improving in teaching techniques, etc. AI can also help in various administrative work of an educational institute for example making online exams more secure, computerized grading etc. AI also helps students as supporting tutor, understanding lectures by more practical experience by using VR etc. India also launches many programs to help teachers and students such as “MOOC (massive open-online courses)” and “SWAYAM (Study webs of active learning for young aspiring minds)” and AI can support for success of these types of programs.

Optimizing the usage of voice assistants for shopping

Objectives: To measure the awareness of voice assistants among the consumers and to understand the reasons for consumers minimal voice shopping. To measure the challenges faced by voice shopping in spite of voice assistants’ upward trend and also to understand the attitude behavior and personality of the consumers for adopting and for ignoring voice shopping.Methods / Statistical Analysis: The design used for this study is descriptive and the population that was considered for the study belongs to Chennai, India. The sample taken for the study is 65 respondents and sampling technique used is convenient sampling. Statistical tools namely percentage analysis, correlation, and chi – square analysis is applied. Findings: Most (86%) of the respondents are aware of the voice assistant, but still they were not trained to use it for shopping. Female respondents are hesitant to use the voice assistant for shopping and the reason for ignorance was user voice was not identified and respondents get error message. Respondents feel unsecured in using payment options in voice assistant. Attitude and technology usage plays a major role. From the study, it is evident that the awareness of the existing voice assistants is low and consumer’s behavior is not consistent. Applications / Improvements: Thus to increase the usage of voice assistants for shopping, customer awareness and engagement should be increased and the user can be motivated about discounts and offers and providing secured payment system. Even if people can’t afford voice assistants speakers (like Alexa, Google home), facilities are available in smart phones, even for which the awareness is less. Attitude and technology has to improve a lot so that after creating awarenessand after providing modalities of safety measures to the respondents, usage might improve in future. Keywords: Voice assistant; e-commerce; SEO; online shopping; optimization; Alexa; Google assistant; SIRI

Investigating college EFL learners’ perceptions toward the use of Google Assistant for foreign language learning

ABSTRACT Recent studies on the use of Intelligent Personal Assistant (IPA) for second language (L2) learnring have found that IPAs such as Amazon’s Alexa is useful and motivating for L2 learners and that learners’ language proficiency might influence their perceptions toward IPAs. However, most existing studies focused on the potentials of Alexa and paid little attention to Google Assistant (GA). This study was thus conducted to investigate how L2 learners at different proficiency levels perceive the potentials of GA. Twenty-nine EFL college students were recruited to try various voice commands for an hour in order to investigate learners’ perceptions toward the potentials of GA for language learning. Results of the survey and interview show that these learners enjoyed interacting with GA and considered GA an inspiring tool to learn English. They also found that GA can be useful in improving their speaking and listening skills. They perceived GA’s pronunciation to be quite natural and its utterances to be easily comprehensible. Results also reveal that higher level learners achieved better mutual comprehensibility with GA, whereas lower level learners encountered more challenges due to their mispronunciations. Based on these findings, future research directions and pedagogical suggestions on IPA-assisted L2 learning are provided.

THE ROLE OF VIRTUAL ASSISTANTS WITH CORONAVIRUS DIAGNOSIS AND TREATMENT

SESSION TITLE: Disaster Medicine Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: SARS-CoV-2, novel coronavirus initially detected in Wuhan, China in 2019, has been identified by World Health Organization as a cause of severe acute respiratory distress syndrome in children, adults, as well as the elderly In light of rapid person to person transmission, CDC guidelines have advised to take precautions As companies move to work-from-home, medicine has also moved significantly towards tele-medicine We analyzed the efficacy of virtual assistants, including Apple Siri, Google Assistant, Windows Cortana, and Amazon Alexa in Coronavirus and their ability to diagnose and guide patients based on relevance of symptoms METHODS: Responses from virtual assistant phone applications, Apple Siri, Google Assistant, Windows Cortana, and Amazon Alexa, were tested and analyzed to assess the accuracy of given responses, gauge the overall ability of the virtual assistants to detect the symptoms of COVID-19 and guide patients accordingly The following phrases were utilized: “I have a cough”, “I have a fever”, “I have shortness of breath”, “I feel weak”, “I have diarrhea”, “How do I know if I have Coronavirus?”, and “I think I may have COVID-19 ” Responses were categorized based on level of recognition and sophistication of response and consequently classified as- no recognition, basic recognition with response providing more information on coronavirus and symptoms, and advanced response that evaluated for further symptoms and need for medical assistance RESULTS: While Windows Cortana was able to recognize only the question with the word coronavirus at a very basic level, Google Assistant performed at a higher level and was able to identify symptoms such as cough, shortness of breath, and diarrhea as symptoms of coronavirus and provided detailed information Google Assistant additionally recognized any phrase including “Coronavirus” and “COVID-19” but still gave only information on disease Meanwhile, Apple Siri and Amazon Alexa were able to respond to 2 of the 7 questions at an advanced level at detection of words, “Coronavirus” or “COVID-19” and subsequently initiated an algorithm for the user CONCLUSIONS: While Cortana and Google Assistant functioned at a basic level, both Apple Siri and Amazon Alexa, appropriately identified the level of care needed by asking user to either stay in isolation, contact a medical doctor within 24 hours, or call 911 for emergency services based on answers provided in algorithm CLINICAL IMPLICATIONS: Although artificial intelligence can be an important tool for users in light of a pandemic, there are significant limitations that need to be addressed before we can utilize these to both recognize symptoms and variety of phrases There is also a need for these tech companies to come up with a universal system which can be utilized in a situation like this so that the population at large can benefit from these advances irrespective of the device or platform they use DISCLOSURES: No relevant relationships by Jagadish Akella, source=Web Response No relevant relationships by Vaishali Mehta, source=Web Response No relevant relationships by Rajmohan Rammohan, source=Web Response No relevant relationships by Raghavendra Sanivarapu, source=Web Response No relevant relationships by Najia Sayedy, source=Web Response

Smart Metering System with Google Assistant

This paper presents a unique research problem in the area of automation system by using IoT. The mentioned approach utilizes Google assistant, which is incorporated within Google home which uses voice-controlled inputs and voice feedbacks. This paper discusses a new method to develop a smart energy meter at a distributor level and to make use of this technology to monitor the power consumption of each device individually which can help the user to monitor the electricity usage in real time and thus helps to save electricity and reduce cost on your electricity bill.

Probabilistic Machine Learning Using Bayesian Inference

Machine Learning is a branch of AI (Artificial Intelligence) which expands on the idea of a computational system extending its knowledge about set methodical behaviors from the data that is fed to it to essentially develop analytical skills that can help in identifying patterns and making decisions with little to no participation of a real human being. Computer algorithms help in gaining experience to improve the facility over time for use by both consumers and corporations. In today’s technologically advanced world, Machine Learning has given us self-driving cars, speech recognition software, and AI agents like Siri and Google assistant. This project evaluates how the Beta function came to be and how Stirling’s formula is implemented in calculating the magnitude of this function for large input values. The Beta function can then be used to produce a Beta distribution of probabilities to find whether people will actually watch a video they come across on their recommendations feed or search feed and then using Bayesian inference update the prior set predictions.

IOT BASED SMART HOME ASSISTANT

The world is full of automation and the people living in this world are surrounded with automated systems. Industries, business sectors, even homes are being automated. Operating various home appliances conveniently along with saving energy are the prominent factors possessed by Smart Home. A quick increase is seen in people's needs in order to develop the social economy of appliances present in a house. If we look at the existing system, we have Google home and Amazon echo which provide functionalities such as switching on/off appliances remotely from anywhere. This paper primarily focuses on a smart home system which allows users to control any electrical appliance using their smart phone google assistant. Apart from this the system also helps in keeping a track on air quality, sound and light intensity, temperature and humidity of home. It also provides analysis of the aforesaid parameters using various graphical methods. It starts the appliance itself on detecting human motion and notifies the user about the same so in case if there is an intrusion the user will come to know about the same. It also takes care of user’s safety as it informs about gas leakage and fire detection preventing any major damage. The need for integration is seen in society, as the idea of a Smart home system is still a new research area. Convenience, security, time management, and connectivity act as prominent factors to motivate and build a system like Smart Home. This paper hence provides a detailed inspection on the architecture, procedures, technologies required for a smart home system. The best protocols and technical solution acquired in the IOT Based Smart Home Assistant are discussed in the paper.