Intelligent Car with Voice Assistance and Obstacle Detector to Aid the Disabled

Gulati, Ujjwal; Ishaan,; Dass, Rajeshwar

doi:10.1016/j.procs.2020.03.383

Cited by 12 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Throughout the testing, pulse sensors were put to the test on a few tiny circuits. When data is sent to the server, the outcome is shown in a graph [20,21]. How to display your heart rate is shown in Figure 13.…”

Section: Resultsmentioning

confidence: 99%

[Retracted] Health Monitoring of Employees for Industry 4.0

Ayyalraj

Balamurugan

Golie

2022

Journal of Nanomaterials

View full text Add to dashboard Cite

On a daily basis, young agers engage in a range of activities. There are numerous things to do, such as attending class, participating in a group project, and going grocery shopping, to mention a few. If a student becomes ill, he or she must visit the clinic for treatment and a note of discharge. Researchers contribute using IoT to display health status in order to decrease the likelihood of becoming unwell. Young agers can use this tool to see if their pulse rates are normal or not. Young agers can see their pulse rate by using the IoT to display their health status. This tool will also assist pupils in reaching their full potential and improving their personal health by determining their optimum pulse rate. Young agers will always keep a healthy lifestyle in order to function in the society. This tool can also serve as a reminder to kids that good health is essential for survival. This method can be used to detect whether a person’s pulse rate is normal while exercising, according to the findings of this study. Such application can be applied in Industry 4.0 in order to evaluate young employee’s health condition to produce better industry outcome.

show abstract

Section: Resultsmentioning

confidence: 99%

[Retracted] Health Monitoring of Employees for Industry 4.0

Ayyalraj

Balamurugan

Golie

2022

Journal of Nanomaterials

View full text Add to dashboard Cite

show abstract

“…This ontology allows for easy adaptation to different contextual situations and as-yet-unknown IoT devices and services. The integration of Arduino with the IFTTT site can be achieved by following the steps in [17].…”

Section: The Proposed Using Eupont Ontology In Send Responding Alert ...mentioning

confidence: 99%

Towards Enhancement EUPont Ontology for Smart Home

Salem

2024

IJSTS

View full text Add to dashboard Cite

Smart homes are characterized by the integration of technology and services using home networking, with the goal of improving the overall quality of life. When designing these intricate systems, it is important to consider the experiences and needs of the occupants. Smart homes consist of various devices that offer comfort, security, convenience, energy efficiency, and promote intelligent living. These devices communicate and interact with each other, forming a connected ecosystem. In order to ensure prompt assistance during emergencies such as fires, medical emergencies, or distress calls, interactivity and technology within smart homes should enable emergency service providers to quickly respond. To achieve this, a modeling language that supports the semantic aspect is employed, allowing for modeling that closely aligns with end user requirements. This language typically utilizes the concept of ontology. However, the use of ontologies in smart home design is still limited in current research. As a result, this paper aims to enhance the EUPont ontology by integrating Arduino devices and implementing an algorithm that simplifies the analysis of detected alarm signals and user decision-making. The execution of this algorithm relies on the definition of several SWRL rules (Semantic Web Rule Language).

show abstract

“…A VCS is installed in AVs to capture users' voice commands and securely store data for later use. The voice user interface method is used in AVs, utilizing a user mental model to identify the exact voice commands [15]. Artificial intelligence and the big data analysis process are used in AVs to fetch related data for identification.…”

Section: Introductionmentioning

confidence: 99%

Improving Autonomous Vehicle Controls and Quality Using Natural Language Processing-Based Input Recognition Model

Anjum

Shahab

2023

Sustainability

View full text Add to dashboard Cite

In contemporary development, autonomous vehicles (AVs) have emerged as a potential solution for sustainable and smart transportation to fulfill the increasing mobility demands whilst alleviating the negative impacts on society, the economy, and the environment. AVs completely depend on a machine to perform driving tasks. Therefore, their quality and safety are critical concerns for driving users. AVs use advanced driver assistance systems (ADASs) that heavily rely on sensors and camera data. These data are processed to execute vehicle control functions for autonomous driving. Furthermore, AVs have a voice communication system (VCS) to interact with driving users to accomplish different hand-free functions. Some functions such as navigation, climate control, media and entertainment, communication, vehicle settings, vehicle status, and emergency assistance have been successfully incorporated into AVs using VCSs. Several researchers have also implemented vehicle control functions using voice commands through VCSs. If a situation occurs when AV has lost control due to malfunctioning or fault in the installed computer, sensors and other associated modules, driving users can control the AV using voice notes to perform some driving tasks such as changing speeds, lanes, breaking, and directing the car to reach a safe condition. Furthermore, driving users need manual control over AV to perform these tasks in some situations, like lane changing or taking an exit due to divergence. These tasks can also be performed with the help of voice commands using VCSs. Therefore, finding the exact voice note used to instruct different actuators in risk situations is crucial. As a result, VCSs can greatly improve safety in critical situations where manual intervention is necessary. AVs’ functions and quality can be significantly increased by integrating a VCS with an ADAS and developing an interactive ADAS. Now, the driver functions are controlled by voice features. Therefore, natural language processing is utilized to extract the features to determine the user’s requirements. The extracted features control the vehicle functions and support driving activities. The existing techniques consume high computation while predicting the user command and causing a reduction in the AVs’ functions. This research issue is overcome by applying the variation continuous input recognition model. The proposed approach utilizes the linear training process that resolves the listening and time-constrained problems and uncertain response issues. The proposed model categorizes the inputs into non-trainable and trainable data, according to the data readiness and listening span. Then, the non-distinguishable data were validated by dividing it into the linear inputs used to improve the response in the AVs. Thus, effectively utilizing training parameters and the data decomposition process minimizes the uncertainty and increases the response rate. The proposed model has significantly improved the exact prediction of users’ voice notes and computation efficiency. This improvement enhances the VCS quality and reliability used to perform hand-free and vehicle control functions. The reliability of these functions ultimately improves the safety of AVs’ driving users and other road users.

show abstract

Intelligent Car with Voice Assistance and Obstacle Detector to Aid the Disabled

Cited by 12 publications

References 3 publications

[Retracted] Health Monitoring of Employees for Industry 4.0

[Retracted] Health Monitoring of Employees for Industry 4.0

Towards Enhancement EUPont Ontology for Smart Home

Improving Autonomous Vehicle Controls and Quality Using Natural Language Processing-Based Input Recognition Model

Contact Info

Product

Resources

About