Ambient acoustic event assistive framework for identification, detection, and recognition of unknown acoustic events of a residence

Pandya, Sharnil; Ghayvat, Hemant

doi:10.1016/j.aei.2020.101238

Cited by 40 publications

(16 citation statements)

References 39 publications

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“…In the late 1940s, scholars started to discuss the notion that the efficacy of leadership is decided by how an individual behaves [39]. The researchers analyzed habits and their effects on successful interventions such as the followers' development and happiness rather than looking for characteristics [40].…”

Section: Behavioural Theorymentioning

confidence: 99%

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

et al. 2021

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Successful leaders are facilitators who specifically target skilled and committed workers. Studies in organizational psychology and the research on an organization's actions suggest that management styles and staff motivation are key factors of business performance or failure. This study aimed to study the influence of leadership on the performance of employers in the education ministry and higher education of Somaliland and to define four types, namely, autocratic, transformational, democratic and transactional leadership. This study analyzed the effects of leadership styles on employee efficiency. The final findings have shown that the autocratic leadership model has a detrimental effect on the department's efficiency,

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Section: Behavioural Theorymentioning

confidence: 99%

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

et al. 2021

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“…AI is widely used in drug discovery and development, largely to find new uses of existing drugs, optimize their effectiveness, and much more [ 14 , 15 , 16 , 17 , 18 ]. Research has been done using AI models to detect adverse event under-reporting to ensure patient safety and integrity of the generated data [ 19 ].…”

Section: Recent Ai Contributions In Healthcarementioning

confidence: 99%

“…Long gone are the times when the discovery and development of drugs such as vaccines, etc., were considered very long and extremely hazardous processes. With the introduction of machine learning algorithms and AI robots, the process has become much quicker and safer as the machine learning algorithms handle the initial research grunt work, and other heavyweight processes such as identification of predictive biomarkers, target validation, etc., are also easily achieved using different machine learning models [ 17 ]. They can also analyze and then predict alternatives to the current paths followed for therapy, especially in multifactorial diseases or even create individual responses to the therapeutic drugs, such as cancer patients [ 18 ].…”

Section: Recent Ai Contributions In Healthcarementioning

confidence: 99%

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions

Pandya

Thakur

Saxena

et al. 2021

Sensors

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The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medical Things), genetic intelligence algorithms, smart immunological methodologies, etc., has made this process easier. These technologies can observe relations and patterns that humans do and recognize patterns that are unobservable by humans. Furthermore, these technologies have also enabled us to understand better the different types of cells in the immune system, their structures, their importance, and their impact on our immunity, particularly in the case of debilitating diseases such as cancer. The undertaken study explores the AI methodologies currently in the field of immunology. The initial part of this study explains the integration of AI in healthcare and how it has changed the face of the medical industry. It also details the current applications of AI in the different healthcare domains and the key challenges faced when trying to integrate AI with healthcare, along with the recent developments and contributions in this field by other researchers. The core part of this study is focused on exploring the most common classifications of health diseases, immunology, and its key subdomains. The later part of the study presents a statistical analysis of the contributions in AI in the different domains of immunology and an in-depth review of the machine learning and deep learning methodologies and algorithms that can and have been applied in the field of immunology. We have also analyzed a list of machine learning and deep learning datasets about the different subdomains of immunology. Finally, in the end, the presented study discusses the future research directions in the field of AI in immunology and provides some possible solutions for the same.

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“…In developing countries, such as India, along with the physical efforts of doctors, nurses, and the paramedical staff, the government has utilized digital technologies in a variety of ways, such as "Aarogya-Setu app, " which can assist citizens in identifying near-by COVID-19 patients using Bluetooth and GPS based remote tracking technologies. However, looking at the impact and the spread of coronavirus, fellow researchers need to put more effort into designing and developing COVID-19 solutions (3)(4)(5)(6)(7). It is a fact that fellow researchers have proposed various innovative approaches to deal with the current precarious situation, including automatic sanitizer systems for the disinfection of medical equipment and individuals, thermal scanning guns, and many more.…”

Section: Introductionmentioning

confidence: 99%

COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks

Pandya

Sur

Solke

2021

Front. Public Health

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The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach—The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings—The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.

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Ambient acoustic event assistive framework for identification, detection, and recognition of unknown acoustic events of a residence

Cited by 40 publications

References 39 publications

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions

COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks

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