Design of smart public transport assist system for metropolitan city Chennai

Kanthavel, R.; Sangeetha, S.; Keerthana, K.P.

doi:10.1016/j.ijin.2021.06.004

Cited by 31 publications

(12 citation statements)

References 1 publication

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“…After entering into the DSM and improving their arrangement and after the second interview with the expert team, sub-tasks 53, 48, 38,32,18,16,42,41,40,25,24,23,22,11,10, and 52 have had fewer errors, which indicates the reduced human error and increased reliability.…”

Section: Step 7 Recalculating the Error Of Terminal Conductor Tasks A...mentioning

confidence: 99%

“…Modern control systems alone are not enough to secure rail transportation systems such as railways and subways; rather, these systems require optimal use by employees as well. 10 Technical examination and fixing possible defects of the train before using it and passengers boarding is one of the important tasks in the railway, which is the responsibility of the terminal conductor. In this regard, any negligence and human error can lead to accidents such as injury to passengers, collision of two trains, etc.…”

Section: Introductionmentioning

confidence: 99%

“…Human resource, as the most important factor in the operations in urban railways, has the task of controlling and monitoring the train structure and equipment. Modern control systems alone are not enough to secure rail transportation systems such as railways and subways; rather, these systems require optimal use by employees as well 10 …”

Section: Introductionmentioning

confidence: 99%

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Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

Fakharzadeh,

Fakoor Saghih,

Bohlouri

et al. 2024

Quality & Reliability Eng

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As one of the most important reasons of irreparable losses at work, human error is still a significant problem in spite of the rapid technological advancement and reduced role of humans in the systems set up and control. Therefore, with the aim of reducing human error, this study presents a new method to improve human reliability using the hybrid approach of SPAR‐H and DSM. For this purpose, the number of 53 tasks was specified for the terminal conductor using Hierarchical Task Analysis (HTA). Then, the error related to each task was calculated utilizing the Standardized Plant Analysis‐Risk Human (SPAR‐H) method, and based on the expert team's opinion. Next, the terminal conductor's tasks were entered into the DSM along with the error numbers and dependencies between tasks, and the most optimal arrangement of tasks was obtained by coding in MATLAB software. Finally, by using the SPAR‐H method, the error of the terminal conductor was calculated based on the new tasks arrangement and compared with the primary state. Based on the obtained results, the 30% increase in reliability shows the significant contribution of the optimal arrangement of tasks in reducing human error. The proposed method of this study helps managers to reviewing the task structure in high‐risk processes as an effective strategy to reduce human error.

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Section: Step 7 Recalculating the Error Of Terminal Conductor Tasks A...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

Fakharzadeh,

Fakoor Saghih,

Bohlouri

et al. 2024

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…There are still holes in the research because of the small sample size and the use of limited clinical data. There was no comparison to clinical trials in this study [ 29 , 30 ]. In the future, we hope to verify and mine more accurate and effective detection models based on AI-based clinical diagnosis and prediction and provide decision support and aid for correct diagnosis and treatment of this condition through more comprehensive clinical data analysis.…”

Section: Literature Studymentioning

confidence: 99%

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis

Sangeetha

Kumar

Deeba

et al. 2022

Computational and Mathematical Methods in Medicine

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As a result of the COVID-19 outbreak, which has put the world in an unprecedented predicament, thousands of people have died. Data from structured and unstructured sources are combined to create user-friendly platforms for clinicians and researchers in an integrated bioinformatics approach. The diagnosis and treatment of COVID-19 disease can be accelerated using AI-based platforms. In the battle against the virus, however, researchers and decision-makers must contend with an ever-increasing volume of data, referred to as “big data.” VGG19 and ResNet152V2 pretrained deep learning architectures were used in this study. With these datasets, we could train and fine-tune our model on lung ultrasound frames from healthy people as well as from patients with COVID-19 and pneumonia. In two separate experiments, we evaluated two different classes of predictive models: one against pneumonia and the other against non-COVID-19. COVID-19 can be detected and diagnosed accurately and efficiently using these models, according to the findings. Therefore, the use of these inexpensive and affordable deep learning methods should be considered as a reliable method for the diagnosis of COVID-19.

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“…The same method of protection cannot be used for prolonged sessions. These factors made IoT devices appealing targets for hackers, putting our lives in jeopardy from unforeseen dangers [ 4 ]. Using the terms “lightweight” and “adoption” to create strong security solutions could be one realistic way to handle these IoT complexity issues [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Multilayered Neural Network-Based Intrusion Detection System in the Internet of Things Network

Sangeetha

Mani

Maheshwari

et al. 2022

Computational Intelligence and Neuroscience

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A large array of objects is networked together under the sophisticated concept known as the Internet of Things (IoT). These connected devices collect crucial information that could have a big impact on society, business, and the entire planet. In hostile settings like the internet, the IoT is particularly susceptible to multiple threats. Standard high-end security solutions are insufficient for safeguarding an IoT system due to the low processing power and storage capacity of IoT devices. This emphasizes the demand for scalable, distributed, and long-lasting smart security solutions. Deep learning excels at handling heterogeneous data of varying sizes. In this study, the transport layer of IoT networks is secured using a multilayered security approach based on deep learning. The created architecture uses the intrusion detection datasets from CIC-IDS-2018, BoT-IoT, and ToN-IoT to evaluate the suggested multi-layered approach. Finally, the new design outperformed the existing methods and obtained an accuracy of 98% based on the examined criteria.

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Design of smart public transport assist system for metropolitan city Chennai

Cited by 31 publications

References 1 publication

Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis

Design and Analysis of Multilayered Neural Network-Based Intrusion Detection System in the Internet of Things Network

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